Destroying the Jungle Republic: Counterinsurgency Theory and The

Home , Counterinsurgency, Militarism, Napalm, Roger Trinquier

Destroying the Jungle Republic:

Counterinsurgency Theory and the Environment in South Vietnam (1967-1969)

A dissertation submitted to

Kent State University in partial fulfillment

of the requirements for the

degree of the Doctor of Philosophy

Gordon A. Cromley

August 2019

Except for previously published material

Dissertation written by

Gordon A. Cromley

B.S., The Ohio State University, 2005

M.A., Kent State University, 2014

Ph.D., Kent State University, 2019

Approved by

Dr. James Tyner, Ph.D. ___ , Chair, Doctoral Dissertation Committee

Dr. Christopher Post, Ph.D. , Members, Doctoral Dissertation Committee

Dr. V. Kelly Turner, Ph.D. _ ,

Dr. Christopher Blackwood, Ph.D. ,

Accepted By

Dr. Scott Sheridan, Ph.D. _ , Chair, Department of Geography

Dr. James L. Blank, Ph.D. _ , Dean, College of Arts and Sciences

TABLE OF CONTENTS

TABLE OF CONTENTS ...... iii

LIST OF FIGURES ...... vii

LIST OF TABLES…………………………………………………………………………….....xii

ACKNOWLEDGEMENTS...... xiv

CHAPTER 1 – INTRODUCTION ...... 1

1.1 Modern Warfare……………………………………………………………………...... 1

1.2 Research Questions……………………………………………………………………………5

1.3 Dissertation Outline………………………………………………………………………...... 6

CHAPTER 2 – LITERATURE REVIEW ...... 10

2.1 Introduction: What Type of Conflict? ...... 10

2.2 Military Geography and Military Landscapes ...... 13

2.3 Human/Environment Studies ...... 23

2.4 Historical Geographic Information Science ...... 30

2.5 Summary ...... 33

CHAPTER 3 – THE INSURGENCY AND THE JUNGLE IN THE INDOCHINA WARS ...... 34

3.1 Introduction ...... 34

3.2 The Jungle During the First Indochina War ...... 38

3.3 The Jungle During the Inter-War Period ...... 45

3.4 The Jungle During the Second Indochina War ...... 47

3.5 Summary ...... 49

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CHAPTER 4 – SPATIAL DATA COLLECTION AND PRE-PROCESSING...... 51

4.1 Data Sources ...... 51

4.2 Pre-Processing NARA Data...... 52

4.2.1 Pre-Processing HERBO-2 Data………………………………………………………..53

4.2.2 Pre-Processing BASFA Data……………………………………………………….....57

4.2.3 Pre-Processing HES Data……………………………………………………………...63

4.3 Pre-Processing Topographic Map Data ...... 67

4.3.1 Topographic Map Metadata…………………………………………………………....71

4.3.2 Extraction of the Map Image from the Map Sheet………………………………….…71

4.3.3 Geo-referencing the Map Images…………………………………………………..….72

4.3.4 Constructing the Land Cover Map………………………………………………….....74

4.4 Summary………………………………………………………………………………….…75

CHAPTER 5 – CODING ANALYSIS OF U.S. MILITARY FIELD MANUALS ...... 78

5.1 Providing a Baseline for Understanding U.S. Military Action ...... 78

5.2 Content Analysis of Textual Data ...... 79

5.2.1 Textual Sources…………………………………………………………………….…...79

5.2.2 Creating a Code Book…………………………………………………………….…….80

5.2.3 Coding the Textual Sources…………………………..………………………………..81

5.3 Code Count and Code Density Analysis and Results ...... 84

5.3.1 Code Count Queries………………………………………………………………….....84

5.3.2 Code Count and Code Density Results……………………………………...……….…84

5.4 Code Comment Analysis and Results ...... 85

5.4.1 Code Comment Queries………………………………………………………………...85

5.4.2 Code Comment Results…………………………………………………………….…..87

5.5 Statistical Analysis of Code Pairs in Paragraphs Results ...... 92

5.5.1 Definition and Numbers of Code Pairs………………………………………………....92

5.5.2 Code Pairs for Statistical Analysis……………………………………………………...93

5.5.3 Statistical Analysis of Associations of Code Pairs in Paragraphs……………………...95

5.5.4 Summarizing Themes from Qualitative Analysis……………………………………..104

5.6 Conclusions ...... 107

CHAPTER 6 – A SPATIAL ANALYSIS OF HAMLET SECURITY PATTERNS ...... 109

6.1 The Importance of Hamlet Control ...... 109

6.2 The Spatial Distribution of Hamlets Within the Environment ...... 110

6.3 Point Pattern Analysis of Hamlet Security Distributions ...... 111

6.3.1 Point Pattern Analysis…………………………………………………………………114

6.3.2 The Spatial Structure of Hamlet Security.…….…………………………...………….122

6.4 Summary ...... 137

CHAPTER 7 – AN ANALYSIS OF THE IMPACT OF INSURGENCY/ COUNTERINSURGENCY TACTICS ON HAMLET SECURITY ...... 139

7.1 Introduction ...... 139

7.2 Enemy Base Locations and the Environment ...... 140

7.3 The Spatial Relationships of Operation Ranch Hand ...... 148

7.3.1 Spatial Relationships with the Natural and Human Environment………….………....151

7.3.2 Spatial Relationships with the Base Camps Locations………………..………………154

7.4 Point Pattern Analyses of Insurgency and Counterinsurgency Operations...... 154

7.4.1 Impact of Flight Paths on Base Camp Deactivation…………………………………..157

7.4.2 The Pattern of the Insurgent Response to Base Camp Deactivation………………....161

7.4.3 The Relationship Between Hamlet Security and Base Camp Locations……………...163

7.5 Temporal Changes in Hamlet Security...... 167

7.5.1 Global Regression Analysis of Hamlet Security Change… ……………………...171

7.5.2 A GWR Analysis of Hamlet Security Change………………………………………...177

7.6 Conclusions ...... 188

CHAPTER 8 – Discussion of Results and Conclusion ...... 190

8.1 Geographical Warfare ...... 190

8.2 Characterizing the Jungle Environment ...... 190

8.3 Characterizing the Spatial Structure of Hamlet Security ...... 193

8.4 Insurgency/Counterinsurgency Tactics ...... 195

8.5 Longitudinal Analysis of Counterinsurgency Doctrine ...... 196

8.6 Conclusion…..……………………………………………………………………………...197

REFERENCES ...... 198

APPENDICES ...... 209

APPENDIX A – THE CODE BOOK ...... 210

APPENDIX B – PAIRWISE MARKED CONNECTION FUNCTIONS DEFINING THE SPATIAL STRUCTURE OF HAMLET SECURITY PATTERNS, MARCH 1967 TO DECEMBER 1968 ...... 216

LIST OF FIGURES

Figure 3.1 – The location of South Vietnam with respect to its neighboring states in Southeast Asia ...... 46

Figure 4.1 – HERBO-2 flight paths with only the starting location ...... 58

Figure 4.2 – Complete HERBO-2 flight paths, August 1965 to February 1971 ...... 59

Figure 4.3 – The locations of enemy base camps ...... 62

Figure 4.4 – The location of hamlets in the January 1967 dataset...... 68

Figure 4.5 – The location of hamlets in the January 1971 dataset...... 69

Figure 4.6 – The location of hamlets in the January 1974 dataset...... 70

Figure 4.7 – The geo-registered Hue Map Sheet against the outline of South Vietnam...... 74

Figure 4.8 – The forested and mangrove regions (the “Jungle”) of South Vietnam ...... 76

Figure 6.1 – The location of hamlets for January 1967 with respect to the jungle region ...... 112

Figure 6.2 – The intersection of the hamlet region with the jungle region ...... 113

Figure 6.3 – A distribution of 236 Viet Cong controlled and contested hamlets that form the example dataset ...... 116

Figure 6.4 – The marked connection function p11 associating mark 1 points with other mark 1 points in the example over all distances ...... 118

Figure 6.5 – The marked connection function p22 associating mark 2 points with other mark 2 points in the example over all distances ...... 120

Figure 6.6 – The marked connection function p12 associating mark 1 points with mark 2 points where the mark 1 points are the focal points in the example ...... 121

Figure 6.7 – The marked connection function p21 associating mark 2 points with mark 1 points where the mark 2 points are the focal points in the example ...... 121

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Figure 6.8 – The spatial pattern of hamlet security codes in January 1967 ...... 123

Figure 6.9 – The marked connection function for GVN secured hamlets with respect to other GVN secured hamlets with contested hamlets as mark 2 for January 1967…...…125

Figure 6.10 – The marked connection function for contested hamlets with respect to other contested hamlets with GVN secured hamlets as mark 1 for January 1967 ...... 125

Figure 6.11 – The mark connection function for p12 for GVN secured and contested hamlets where the GVN secured hamlets are the focal points for January 1967 ...... 126

Figure 6.12 – The difference in the marked correlation functions, g21–g11, where GVN secured hamlets are mark 1 and contested hamlets are mark 2 for January 1967 ...... 127

Figure 6.13 – The difference in the marked correlation functions, g12–g22, where GVN secured hamlets are mark 1 and contested hamlets are mark 2 for January 1967 ...... 127

Figure 6.14 – The difference in density functions where GVN hamlets are mark 1 and contested hamlets are mark 2 for January 1967...... 128

Figure 6.15 – The marked connection function for VC controlled hamlets with respect to other VC controlled hamlets with contested hamlets as mark 2 for January 1967 ...... 129

Figure 6.16 – The marked connection function for contested hamlets with respect to other contested hamlets with VC controlled hamlets as mark 1 for January 1967 ...... 129

Figure 6.17 – The mark connection function p12 for VC controlled and contested hamlets where the VC controlled hamlets are the focal points for January 1967...... 129

Figure 6.18 – The difference in the marked correlation functions, g21–g11, where VC controlled hamlets are mark 1 and contested hamlets are mark 2 for January 1967 ...... 130

Figure 6.19 – The difference in marked correlation functions, g12–g22, where VC controlled hamlets are mark 1 and contested hamlets are mark 2 for January 1967 ...... 130

Figure 6.20 – The difference in density function where VC controlled are mark1 and contested hamlets are mark 2 for January 1967 ...... 131

Figure 6.21 – The marked connection function for GVN secure hamlets with respect to other GVN hamlets with VC controlled hamlets as mark 2 for January 1967 ...... 131

Figure 6.22 – The mark connection functions of VC controlled hamlets with respect to other VC controlled hamlets with GVN secured hamlets as mark 1 for January 1967 ...... 132

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Figure 6.23 – The Mark Connection Function p12, for GVN secured and VC controlled hamlets where the GVN secured hamlets are the focal points for January 1967 ...... 132

Figure 6.24 – The difference in the marked correlation functions, g21-g11, where GVN secured hamlets are mark 1 and VC controlled hamlets are mark 2 for January 1967 ..... 133

Figure 6.25 – The difference in the marked correlation functions, g12-g21, where GVN secured hamlets are mark 1 and VC controlled hamlets are mark 2 for January 1967 ..... 133

Figure 6.26 – The difference in density functions where GVN secured hamlets are mark 1 and VC controlled hamlets are mark 2 for January 1967 ...... 134

Figure 6.27 – The spatial pattern of hamlet security codes in December 1968 ...... 135

Figure 6.28 – The mark connection functions of VC controlled hamlets with respect to other VC controlled hamlets with VC controlled hamlets as mark 1 for December 1968... 136

Figure 6.29 – The difference in density functions where VC controlled are mark 1 and GVN secured hamlets are mark 2 for December 1968 ...... 136

Figure 6.30 – The mark connection functions of VC controlled hamlets with respect to other VC controlled hamlets with contested hamlets as mark 2 for December 1968 ...... 136

Figure 6.31 – The difference in density functions where VC controlled are mark 1 and contested hamlets are mark 2 for December 1968 ...... 137

Figure 7.1 – The location of North Vietnamese base camps in South Vietnam and active sanctuaries in neighboring countries ...... 141

Figure 7.2 – Location of North Vietnamese base camps in the jungle environment and the Mekong region ...... 143

Figure 7.3 – Location of North Vietnamese base camps with respect to the hamlet areas in January 1967...... 144

Figure 7.4 – Location of active North Vietnamese base camps in South Vietnam and active sanctuaries in neighboring countries with respect to the jungle and hamlet areas for January 1967 ...... 146

Figure 7.5 – Location of active North Vietnamese base camps in South Vietnam and active sanctuaries in neighboring countries with respect to the jungle and hamlet areas for December 1968 ...... 147

Figure 7.6 – The location of the flight path region with respect to the location of the hamlet region for January 1967...... 152

Figure 7.7 – The location of the flight path region with respect to the location of the jungle region...... 153

Figure 7.8 – Herbicide flight paths from July 1965 to January 1967 with respect to the location of North Vietnamese base camps in January 1967...... 155

Figure 7.9 – Herbicide flight paths from January 1967 to December 1968 with respect to the location of active North Vietnamese base camps in December 1968...... 156

Figure 7.10 – Observed and expected cumulative density functions for all base camps given the covariate, distance to the nearest flight path...... 158

Figure 7.11a – Observed and expected cumulative density functions for active base camps given the covariate, distance to the nearest flight path ...... 160

Figure 7.11b – Observed and expected cumulative density functions for neutralized base camps given the covariate, distance to the nearest flight path ...... 160

Figure 7.12 – The bivariate O–ring Statistic for the density of added camp locations (mark 2) pattern of sites at different distance rings with respect to deactivated camp locations (mark 1)...... 162

Figure 7.13 – The marked connection function where Enemy Base Camps in January 1967 are the antecedent pattern and VC controlled hamlets are mark 1 and non-VC controlled hamlets are mark 2 ...... 164

Figure 7.14 – The marked connection function where enemy base camps in January 1967 are the antecedent pattern and GVN secured hamlets are mark 1 and non-GVN secured hamlets are mark 2 ...... 165

Figure 7.15 – The marked connection function where enemy base camps in January 1967 are the antecedent pattern and contested hamlets are mark 1 and non-contested hamlets are mark 2 ...... 165 x

Figure 7.16 – Hamlets within 20 kilometers of an enemy base camp in January 1967 ...... 169

Figure 7.17 – Hamlets within 20 kilometers of an Enemy Base Camp in December 1968 ...... 170

Figure 7.18 – Hamlets that switched with respect to VC control between January 1967 and December 1968 ...... 172

Figure 7.19 – A twenty kilometer square grid partition of South Vietnam...... 173

Figure 7.20 – Pattern of the standardized residuals for the OLS regression model ...... 176

Figure 7.21 – The spatial pattern of the intercept term in geographically weighted regression...... 179

Figure 7.22 – The spatial pattern of the standard errors of the intercept term in the geographically weighted regression…...... 180

Figure 7.23 – The spatial pattern of the ABDDiff coefficient in the geographically weighted regression…………….…………………………………………….……………181

Figure 7.24 – The spatial pattern of the standard errors of the ABDDiff coefficient in the geographically weighted regression...... 182

Figure 7.25 – The spatial pattern of the PForest coefficient in the geographically weighted regression...... 184

Figure 7.26 – The spatial pattern of the standard errors of the PForest coefficient in the geographically weighted regression ...... 185

Figure 7.27 – The spatial pattern of the AFlyDen Coefficient in the geographically weighted Regression ...... 186

Figure 7.28 – The spatial pattern of the standard errors of the AFlyDen coefficient in the geographically weighted regression ...... 187

LIST OF TABLES

Table 4.1 – The Data Fields Contained in the HERBO-2 NAS Dataset ...... 55

Table 4.2 – The Data Fields Contained in the BAFSA Dataset ...... 61

Table 4.3 – Monthly Count of Recorded Hamlets for Hamlet Evaluation System ...... 66

Table 4.4 – The Link Coordinates for Geo-Referencing the Hue Map Sheet ...... 73

Table 5.1 – Table Design for Database of Field Manual Codes ...... 82

Table 5.2 – Code Counts and Code Densities in U.S. Military Field Manuals, 1940 and 1967 ... 86

Table 5.3 – Actor Code Usage in U.S. Military Field Manuals in 1940 and 1967 ...... 88

Table 5.4 – Activity Code Usage in U.S. Military Field Manuals in 1940 and 1967 ...... 89

Table 5.5 – Setting Code Usage in U.S. Military Field Manuals in 1940 and 1967 ...... 90

Table 5.6 – Raw Activity-Setting and Actor-Setting Code Pairs in 1940 and 1967 Field Manuals ...... 93

Table 5.7 – Codes Mapped to Trinquier’s General Categories of Actors, Activities, and Settings ...... 94

Table 5.8 – Example Odds Ratio and Risk Anaylsis for the Patrol-River Code Pair ...... 96

Table 5.9 – Statistical Associations Among Activities, Actors, and Urban Setting Codes in 1940 and 1967 ...... 99

Table 5.10 – Statistical Associations Among Activities, Actors, and Non-Urban Setting Codes in 1940 and 1967 ...... 101

Table 5.11 – Statistical Associations Among Actions, Actors and Operations Area Codes in 1940 and 1967 ...... 102 xii

Table 5.12 – Statistical Associations Among Activities, Actors, and Lines of Communication Codes in 1940 and 1967 ...... 103

Table 5.13 – Statistical Associations Among Activities, Actors, and State Codes in 1940 and 1967 ...... 105

Table 6.1 – The Number of Hamlets Associated with each Security Type ...... 124

Table 7.1 – Number of Enemy Base Camp Locations by Month ...... 145

Table 7.2 – Marked Connection Function Values for VC Controlled Hamlets With Respect to Base Camp Locations ...... 167

Table 7.3 – Marked Connection Function Values for GVN Secured Hamlets With Respect to Base Camp Locations ...... 168

Table 7.4 – Summary of OLS Results ...... 175

Table 7.5 – Summary of Spatial Error Regression Results ...... 177

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ACKNOWLEDGEMENTS

I would like to thank several groups of people. First, I would like to thank my committee members: Dr. Christopher Blackwood, Dr. Christopher Post, Dr. V. Kelly Turner. I would also like to thank my advisor Dr. James Tyner. The second group of individuals which I would like to thank are my family: My parents Drs. Robert and Ellen Cromley, my Grandmother Lois

Krajcovic, Uncle Steve and Aunt Jan. I would also like to thank Pete, John and Bill Findley as well as the entire Lucci’s Place crew for added support. I would like to thank two professors from my time at The Ohio State University: Dr. Nathan Rosenstein and the late Dr. John

Guilmartin. Had it not been for Dr. Guilmartin’s Vietnam War history class that I took fall quarter of 2003, I would not have had the inspiration for the subject material which formed the foundation of first my master’s thesis and now my dissertation. Finally, I would like to thank my friends Pete and John Findlay with whom I have spent many nights watching sports to take a break while working on my dissertation.

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CHAPTER 1 - INTRODUCTION

1.1 Modern Warfare

On February 2nd, 1962, the first U.S. fixed-wing aircraft loss by U.S. forces in South

Vietnam occurred. The aircraft, a C-123B Provider, was part of the Operation Ranch Hand defoliation contingent (Hobson 2001). All three crew members were listed as ‘Killed in Action’

(KIA) despite the fact that the flight was a scheduled training mission. The aircraft which was stationed at Tan Son Nhut crashed near Route 15 between Bien Hoa and Vung Tau. As a result of the crash, all future Operation Ranch Hand missions would be flown with a fighter escort

(Hobson 2001). This loss, seemingly insignificant, was part of the massive U.S. commitment to counterinsurgency operations in South Vietnam during the Second Indochina War (the Vietnam

War). Operation Ranch Hand was one of many U.S. military initiatives that was specifically directed at suppressing the growing insurgency in that country.

In addition to the defoliation program of Operation Ranch Hand, the United States also deployed Special Forces advisors to operate in the field and act as focal points for counterinsurgency forces against the Viet Cong insurgents. The Vietnam War was a new type of war with which the United States had little experience except for its colony in the Philippines.

The Vietnam War represented a new paradigm, built around the interplay of technology, direct and indirect military action, and how modern societies interact with such conflicts. Although the

Vietnam War was studied extensively by scholars at universities across the world during the

1 conflict, the geographic literature did not contain much research on the conflict at the time. The nature of insurgencies and research on the effects of counterinsurgencies and wider conflicts on the environment have taken new importance through the current and ongoing Global War on

Terror.

The September 11th terrorist attacks, have increased geographic inquiry into how conflict reinforces geopolitical relationships (Gregory 2004), and how conflict impacts the resilience of socio-environmental processes (Tidball and Krasny 2013). The questions raised by the War on

Terror and the new technologies and doctrines that have emerged from this conflict have made scholars reexamine earlier conflicts, specifically the Vietnam War, as important pathways in the evolution of forces that have created today’s current conflicts.

The Vietnam War was a conflict in which the environment played an important role in the conduct and execution of operations and has been considered as a reference point in the development of American military policy (Belcher 2012), and also as a moment in which our understanding of how the environment is used in warfare changed (Zierler 2011). Military doctrine from the current Global War on Terror finds its origins in the U.S. experience in

Vietnam (Belcher 2012) and developing methods to counter the insurgency there led to changes in how the military viewed the environment (Zierler 2011). The Vietnam War was unlike the major conflicts of the 20th Century in which the U.S. was involved because it was a war without fronts and therefore a conflict where civilians and soldiers mingled on a daily basis in urban and primarily rural settings.

This meant that the soldiers and civilians fighting this conflict had to rethink how they understood and constructed the operational landscape. This was a conflict where militarily occupying the most territory did not necessarily equate to victory. It was a war where enemy

2 soldiers were often the least important of military targets (Tyner 2009). This new type of conflict is called guerre moderne (modern warfare), a term name coined by the French military theorist, Roger Trinquier. The name emerged from his experiences during the French Indochina

War (1946-1954) to describe the evolution of conflict from World War II to one in which the civilian sphere and military sphere were inextricably blurred (Trinquier 1964). The French

Indochina War, which was fought in the very same locations as the American experience over a decade earlier, in Trinquier’s view offered a paradigm shift to the French military as the Vietnam

War was a paradigm shift for the U.S. Army (Trinquier 1964). In this type of conflict it was not the extraordinary aspects of military endeavor that were the most important, but the most banal and mundane tasks that had the most impact.

During the Vietnam War it was almost as if the environment, the landscape on which the battles and skirmishes of the war were fought (this will be called the battlespace in this research), was also viewed as an enemy. Vast herbicide programs were inaugurated to tear down the jungles that were linked with the Viet Cong insurgents. The alteration of the landscape in this conflict extended beyond the direct military modification of the landscape for the conduct of specifically military operations. Because modern warfare also included a political component, the war was also fought through the means of economic development and every new improvement to the rural landscape such as a road, or agricultural field or rebuilt hamlet was seen as another tool for fighting the insurgency in South Vietnam.

The U.S. Vietnam War was not just a doctrinal successor to the French conflict but it was also a technological successor. Whereas the French had used Airborne Forces as a unidirectional vertical fix for battlefield mobility against the insurgent forces, the American forces introduced extensive use of the helicopter to offer a more advance bidirectional vertical fix so that troops

3 could be extracted as rapidly as they were inserted for a military operation (Tolson 1973). From an observational standpoint, the French utilized aerial reconnaissance to provide daily updates for battlefield commanders such as at Dien Bien Phu (Fall 2002). For the United States, their

Vietnam War occurred as space reconnaissance methods, spurred by the Cold War, were being developed to maturity; the first Landsat satellite was launched before the close of the conflict.

Collectively the Vietnam Wars offer a case study over several decades in which the interplay between tactics and technology can offer insights into the co-evolution of these two aspects of warfare.

Current research into military landscapes studies how the landscape is patterned, how it is represented, and how it is experienced within the context of the military (Woodward 2014). The research proposed here is situated at the confluence of military geography and human/environment research. Military geography is being reoriented towards analyzing ‘virtual landscapes’, organizational changes within state militaries, and how non-state militaries engage with the landscape and post-military landscapes (Woodward 2014). Human/environment research has also recently investigated post-conflict landscapes (Tidball and Krasny 2013).

The Vietnam War also witnessed the advent of computer-based modelling and simulation of a conflict while it was occurring. The data collected during the variety of analysis programs from the Vietnam War document a critical period in the evolution of the modern military, and these data have only begun to be investigated using spatial analysis.

This research will investigate how the landscape is understood during the execution of military operations. The datasets that this study will use allow for an in situ analysis of the role of landscape in guiding the conflict. As such this research recognizes the linkages between political processes and environmental processes using the French ‘school’ of counterinsurgency

(Trinquier 1964) to interpret human/environment relationships during the conflict. For example, how did military doctrine for counterinsurgency operations define the ‘jungle’ environment?

Environment types such as ‘jungle’ are treated the same around the world, although jungles in one part of the world might function differently than jungles in another part and might therefore require alternative military responses.

1.2 Research Questions

A combination of qualitative and quantitative methods are used to answer the research questions of this study:

Question 1 – How did military doctrine for counterinsurgency operations define the

‘jungle’ environment? Environment types such as ‘jungle’ are treated the same, although jungles in South America might function differently than jungles in Southeast Asia and might therefore require very different military responses to be properly utilized. A sub-question asks if as U.S. doctrine evolved during conflict, did the understanding of the ‘jungle’ and it’s centrality to understanding these operations change over time. A content analysis of how U.S. military handbooks evolved between World War II and the Vietnam War will be used to answer this question.

Question 2 - How was the spatial structure of military/political control of hamlet population organized? If modern warfare was more concerned with the control of population than that of territory, it is important to understand how the spectrum of hamlet security was implemented over space.

Question 3 – What is the potential for using recent spatial-analytical methodologies to assess the impact of insurgency and counterinsurgency doctrines employed in the conflict? By

5 examining the data regarding insurgency operations related to enemy base camp locations and counterinsurgency operations related to the herbicide operations, to what degree can recent spatial-analytical methods such as GIS and point pattern analysis ascertain the level of success of these operations with respect to the control of the hamlet population.

To study the political/environmental relationships imbedded in these questions, this research proposes a mixed-method approach. The first approach uses a theoretically informed, content analysis of the field manuals from World War II and the Vietnam War eras written about counterinsurgency operations. This investigation should reveal how U.S. military institutions understood the physical environment within the context of these operations. The second component of this dissertation will integrate spatial datasets compiled during the Vietnam War to assess the spatial relationships between insurgency and U.S. counterinsurgency operations during the conflict. While quantitative analysis was used during the conflict, those investigations did not include the methods currently available for analyzing spatial data. Such a spatial analytical perspective was not possible at the time of the conflict. The purpose of this study is to develop a methodological framework for analyzing these historical datasets. The questions are used to verify the output of the suite of analyses. If the analyses are properly specified, then the results should align with the historical narrative. In addition to data directly derived from government archives, a ‘jungle’ land cover will be created using geo-tiffs of military topographic maps to assess the spatial relationship between the landscape and insurgency/counter-insurgency tactics.

1.3 Dissertation Outline

This dissertation is composed of eight chapters. This first chapter has introduced the main research questions. This introduction has also presented the growing discussion within

6 geography of the impact that military/militarism has on landscapes, and it has described how counterinsurgency theory has impacted landscape change. Methods developed in ecology can be used to increase our understanding of how counterinsurgency (COIN) operations can influence human and environmental landscape change.

The second chapter reviews the literature in the relevant fields on which this dissertation is built, and then identifies gaps in the literature and situates the placement of this research project within geography. In this chapter, I first address the growth and evolution of military geography and critical military studies since the start of the 21st century and trace how many of the themes and theories originate during the process of decolonization that occurred during the

Cold War. This includes a review of how HGIS has been used to chronicle military operations during the colonial period (Cromley 2016). The discussion will then move from examining military landscapes to a more in depth treatment of the nature-society literature relating to coupled human-environmental systems. Finally, relevant literature from ecology, specifically the literature on ecosystem functioning and ecotone research, will be presented.

The third chapter provides a historical analysis of the evolution of the role that the jungle played during the conflict in Southeast Asia. This chapter also provides a historical narrative of how the French military and later, the U.S. military understood the jungle environment in

Southeast Asia. This chapter then describes how the jungle was transformed into a weapon by the communist insurgents over the course of the conflict from 1945-1973 to overcome the great disparity between the logistical characteristics of the belligerent forces.

The fourth chapter discusses the characteristics of the spatial datasets acquired from the

National Archives, and the preprocessing methods used to prepare these datasets for the subsequent analyses. First, the spatial data associated with the HES system are processed for

7 later analyses regarding the evolution of counterinsurgency measures to control the rural population in South Vietnam. The herbicide data are used to understand where the U.S. forces were directly altering the landscape and if that landscape alteration was where the previous data suggested that it should be (were these areas that were controlled by the insurgents against whom the U.S. was conducting landscape modification operations). Enemy base data are collected so that changes over time in the North Vietnamese locations of their supply and training sites can be documented. Finally, a land cover dataset is prepared from geo-tiffs that will be used to determine the amount and location of forested land cover.

The fifth chapter examines the changes U.S. military doctrine with respect to insurgency and counterinsurgency tactics. A codebook of terms used in these manuals is prepared. The subsequent content analysis of this textual data tries to address specific issues such as understanding how specific types of land cover influenced COIN operations to the benefit or detriment to the insurgents. U.S. field manuals also are examined to determine how friendly forces should deal with particular landscapes when executing COIN operations.

The sixth and seventh chapters present different point pattern analyses related to hamlet security issues. Chapter Six examines how the spatial organization of different types of hamlet security match with the spectrum of security codes that range from VC controlled to those hamlets secured by the South Vietnamese government. Chapter Seven then links the insurgency tactics of base camp location and the counterinsurgency defoliation program with the overall changes in hamlet security for the period from January 1967 to December 1968.

The eighth and last chapter provides a discussion of the three research questions and relates the findings back to a discussion of counterinsurgency theory as espoused by Roger

Trinquier. Finally, this chapter provides a conclusion and situates the research within geography.

It suggests future, new avenues of research with regards to the relationship between 21st century types of military action and its impact on human and environmental landscapes.

This project has the potential to provide important contributions to several fields within geography. The first is the potential to offer new theories for military geography, which has often been critiqued as being theory poor in that most methods used in military geography are taken from outside of the discipline and from other subfields because the subfield itself has not created methods specifically for the study of conflicts (Woodward 2005). The structure of this study provides an historical example of the role of the environment in insurgent operations and the importance that conflict and militarism have in mediating human/environment relationships.

The second contribution is to provide further insight into the Vietnam War. This conflict continues to be a source of tendencies for insurgency policies worldwide. A greater understanding of the spatial metabolism which can be characterized as the ‘operational tempo’ or pace, intensity and scale of operations of this conflict will help us better situate the relevancy of counterinsurgency policy and landscape change during the Vietnam War.

CHAPTER 2 – LITERATURE REVIEW: LANDSCAPES OF CONFLICT

2.1 Introduction: What Type of Conflict?

Landscape, as Mitchell (2008) reminds us, has a complicated lineage. In Mitchell’s

(2008) update of Lewis’ (1979) classic discussion of the American cultural landscape, his fifth axiom tells us that the landscape is, at its core, a materialization of power. Yet, as Mitchell explains, “This power operates in many ways and many places, from corporate boardrooms to city halls, from kitchen tables to consultants’ reports and from the opinion mills of think tanks to streets marked by protest” (Mitchell 2008, 43). While Mitchell approaches his understanding of the relationship between landscape and power from a fundamentally civilian perspective,

Woodward (2014) notes that landscape analysis also has a long tradition within the domain of military geography.

Military geography is an area of research that has a complicated relationship with geographers (Barnes 2008). As such, many scholars who engage with the ‘domain’ of this subfield do so while also situating themselves within alternative subfields. To discuss issues in military geography and to identify as having specific expertise in this area of study while also separating oneself from the direct linkages with the military-industrial-academic complex as articulated by Barnes (2008), scholars have developed new names for their expertise while placing their research along different ideological lines (Rech et al. 2015). However, in Keegan’s classic text, A History of Warfare (1994), the military is shown to have direct connections with

cultural, political, and economic forces in society. As such, geography has entered into a new stage where the undertones of militarism and militarization are implicit with any particular research study. The research in this dissertation is located at the nexus between spatial analysis, military geography and political ecology.

Although one may get lost in the minutiae of the different topics related to conflict and militarization currently being studied, one must not forget that all things relate to the discussion of power, and how power is articulated in society and in the environment. While much of

Western military discourse in the 20th century leads directly or indirectly to the influential

German philosopher Carl von Clausewitz (Keegan 1994), warfare in the 21st century has moved away from many standard military theories. Some of these theories may be based on new technological paradigms (Shaw 2013, 2016) while others are based on reinterpretations of our natural world (Kosek 2011), but all are based on the fundamental changes in information created to inform populations (Goodchild 2006). From a military perspective, this has led to a paradigm shift (Gregory 2004; Smith 1992; Smith 2001) where the Vietnam War and not the Second

World War can be understood as being paradigmatic of the forces governing the functioning of militarized forces in the 21st century.

In the early 1960’s (coincidentally in the same decade as the emergence of the environmental movement), Roger Trinqiuer a French military officer with immense experience fighting in the French Indochina War and later in the Algerian War wrote a treatise (1964) arguing for the adoption of new tactics and training for an evolutionary change in warfare that emerged in the aftermath of the Second World War. Unlike the earlier notion of warfare as being ‘front’ oriented, where military conflict operated as parallel but distinctly separate entities from a ‘civilian’ society, Trinquier (1964) argued that warfare had become an “interlocking

system of actions—political, economic, psychological, military—that aims at the overthrow of the established authority in a country and its replacement by another regime” (Trinquier 1964).

In essence, the control of territory became less of the key to victory as in the past and the control of populations became paramount. As such, the landscape of conflict changed in a manner similar to Mitchell’s (2008) revised axioms for reading the landscape – especially that in modern war “no landscape is local” (Mitchell 2008, 38). When dealing with conflict in the 20th century, Tobler’s First Law of Geography can and does breakdown. Violence is no longer territorially bound in a traditional sense. Conflict is both everywhere (Gregory 2004) and nowhere. Trinquier notes that the destruction of the enemy forces is not the essential element of modern warfare rather, “In seeking a solution, it is essential to realize that in modern warfare we are not up against just a few armed bands spread across a given country, but rather against an armed clandestine organization whose essential role is to impose its will upon the population”

(Trinquier 1964, 8-9).

To destroy this armed clandestine organization, Trinquier (1964) underscores several important concepts: detailed and systematic intelligence information of the human environment and of the natural environment, a centrally organized counterinsurgency structure that can react in a decentralized manner at the required scale of intervention, and an ability to integrate civilian and military entities into a politico-military structure that responds in all manners to the insurgency. Because of this fundamental differentiation between armed political conflict in the

21st century as opposed to earlier paradigms through these core concepts, an understanding of the specific nature of these geographies must be linked to an understanding of the interrelations between insurgency and the environment of insurgency within the geographic context. As control of the population and the destruction of an insurgent’s base of support lies at the core of

the discussion of insurgent warfare, this literature review will highlight relevant research from military geography, nature and society, and GIS that links this research to the fundamental control of populations.

2.2 Military Geography and Military Landscapes

The geography of insurgency has an established literature in geography and related fields

(Lohman and Flint 2010). A geographic understanding of insurgency (synonymous with revolutionary warfare) dates back to the time frame of the Vietnam War (McColl 1969).

Fundamentally, these early articles highlight the spatial patterns of insurgencies as the logic behind their functioning. McColl (1969) argues that “regardless of the variables, a primary objective of each movement was the capture and control of state territory and the eventual creation of an ‘insurgent state’ system.” We can therefore understand the primary goals of the insurgency to create what political scientist Bernard Fall termed, “a parallel structure” (Fall

1963) through which Trinquier’s clandestine organization could develop a counterclaim to sovereignty. This sovereignty is based on several factors. First, the objective of these conflicts was national and social change. Second, as the insurgent territory expands, emphasis is placed on political and social activity instead of military action, and the insurgent state highlights the government’s inability to control territory and protect the populace (McColl 1969).

Within the geographic literature there are several common themes that provide insight into how these processes are understood. First is the body of literature in military geography specifically engaging with military landscapes, particularly the interplay between cultural and social geography and the effects of militarization. Second is the attempt by geographers to examine Lasswell’s (1941; 1962) Garrison State Hypothesis. Third is the geographic literature

that discusses the biopolitics of governmental control. As military geography transitions into other disciplines, some pertinent research may not be directly produced by self-described

‘military geographers’, particularly the biopolitical portions that deal directly with our understanding of the nature of the geographic discourse on counterinsurgency.

With the continued presence of the Global War on Terror, a critical engagement with militarism has become an important component of geographic research (Rech et al. 2015;

Woodward 2014). It has become a research area that has developed in complexity as well as breadth as the earlier research agenda that focused on improving military policy and capabilities

(Galgano and Palka 2012) has changed to one that provides a critical investigation for understanding the role that the military plays in society (Woodward 2005). With this growth in complexity and scale, military geography has emerged as a subfield that addresses several key areas of geographic inquiry: spatiality, place, environment and landscape (Woodward 2014).

These four dimensions follow very important research paradigms within the field. They also draw from different methodological and ontological frameworks reinforcing the importance of understanding military geography in its entirety. The prevalence of the military’s presence within society permits the metaphor of military terms and functions to provide a more intuitive conceptualization of abstract geographic processes.

Unlike other subfields, military geography was earlier critiqued for lacking theory and cohesion as an independent subfield, but military geography has matured and has begun to develop a theoretical structure with respect to its research topics (Woodward 2005). However, current research in geography is examining how the U.S. military during the 20th century engaged in projects to increase their control over populations in areas occupied by the U.S. military. Understanding the ‘human terrain’ of theaters of operations became essential for the

U.S. military during World War II and in the immediate post-war era as the United States moved towards a global posture (Lee, Barnes and Wainwright 2015). This research not only informs our understanding of such activities but also provides examples with which to operationalize social theories and concepts. They specifically outline the evolution of a particularly U.S. vision of the world that highlights the foundations of how the U.S. military interpreted and understood geographical intelligence (Barnes 2006).

Barnes (2006) argues that the Office of Strategic Services (OSS) utilized geographic knowledge to operationalize Latour’s concepts of ‘centres of calculation’, ‘translation’ and

‘action at a distance’. This process, which began during World War II, has only increased with the onset of the Cold War (Barnes 2008; Barnes and Farish 2006; Farish 2015; Lee, Barnes and

Wainwright 2015). The role of specific canons of research in regional and quantitative geography can be understood as closely connected processes between academic inquiry and U.S. geopolitical concerns for providing intelligence and models through which to project U.S. power and influence across the globe as part of the deepening Cold War (Barnes and Farish 2006;

Farish 2015).

The encyclopedic nature of these ventures (Clout and Gosme 2003) sought to provide a firm foundation of operational intelligence for potential theaters of conflict. Even specific sub- disciplines in geography such as Soviet Geography emerged out of these processes (Oldfield,

Matless and Swain 2011). In addition to regional geographies, cultural geographies (Farish

2004) as well as urban geography (Farish 2003) developed parallel lives where ostensibly civilian research could be integrated into military calculations. These calculations of threat of conflict have now become operationalized as security in locations such as cities (Graham 2010;

2012). While human geography provides a wealth of geographical intelligence on the human

terrain, physical geography was also operationalized to create knowledge of environmental processes in different regions of the world.

Geologic maps of key locations, such as the Overlord invasion beaches (Rose et al. 2006) and studies of potential landing sites for Sea Lion invasion beaches (Rose and Willig 2004) were developed to provide accurate information related to operational and tactical mobility of military forces. Additionally, specialized maps were prepared to provide detailed intelligence for military planners such as suitability analysis for airfield sites (Rose and Clatworthy (2007) across the globe. Indeed, the development of and recent scholarship in geography in the 20th century underscores the implicit collaboration of the discipline with providing integrated geographic intelligence which is extremely important in the developing counterinsurgency practices.

Building off this groundwork, geography is now examining the implications of military intervention in nation/state building. In several case studies (Attewell 2015; Lopez 2015), researchers are applying social theory to understand the intricacies of the military’s creation of social infrastructure to stabilize communities that are under military occupation. For example, drawing upon theory from Foucault, Attewell (2015) argues that the United States Agency for

International Development (USAID) development program in South Vietnam represented governmental interventions in the actions, or ‘conduct of conduct’ of South Vietnamese citizens.

Additionally, Attewell (2015) highlights how nation-building infrastructure included the creation of police infrastructures that spread an institutional infrastructure into the Vietnamese countryside.

Likewise, Lopez (2015) studied the modernization mission in Haiti by the United States military in the early 20th century up until the 1930’s. In this case study, the purpose is to underscore the outcomes of U.S. policy as the result of unrest on the part of the civilian

population to the tactics employed by the military led mission. As Lopez (2015) highlights, “In calling upon a specific moment, in unpacking this geographically specific humanitarian history, there emerges a less-eloquent narrative of humanitarianism that holds in its interstices the deep violence of militarism that is deeply tied to geographical imaginaries” (Lopez 2015, 2250).

These studies highlight Trinquier’s discussion of direct intervention in populated areas operating at the nexus of the intersection between police operations, propaganda efforts and social programs (Trinquier 1964).

The development of these practices suggest a more thoroughly integrated understanding of the relationship between the military and civilian society. Particularly within the realm of modern warfare the main thrust of all politico-military effort is to integrate both spheres into an aggregate system whereby there is no institutional separation between either set. A useful framework with which to understand this organization is the Garrison State hypothesis.

The narrative of the collaboration with military leadership and experts is the underlying thesis of Laswell’s Garrison State Hypothesis (1941; 1962). This hypothesis argues that through the development and application of technology, society in the 20th century will give way to military experts or a security apparatus which will control the means of social and economic production underscoring a deepening link between civilian and military spheres. Such a link directly permeates research in geography (Bernazzoli and Flint 2010), but can also be understood implicitly in research illustrating the extension of military reach into areas that had previously escaped state-military control (Lackenbauer and Farish 2007). Additionally, a discussion of this hypothesis has been extended to characterize less direct forms of military control over the functioning of civilian institutions.

A current issue in the National Football League (NFL) is the discussion over the appropriateness of protesting during the national anthem before football games. As Vasquez

(2012) argues, the increase in popularity of American Football can partly be attested to the support of American military institutions. It is not coincidental that during the latter years of

World War II, one of the premier college football programs in the U.S. was the U.S. military academy at West Point, New York. Additionally, this program’s pre-eminence was maintained until the mid-1950’s. But, despite the decline in the prestige of West Point’s football program, the military lineage in college football continued. Many preeminent college coaches in the second half of the 20th century as well as important NFL figures learned football through military programs during the World Wars. Additionally, military terminology such as the ‘draft’ are operationalized to provide specific connotations towards individuals who are signed to play in the NFL. For the beginning of an individual’s career any agency or free market practice is subjugated to the imposition of a military style selection process. Indeed in events such as the combine or Senior Bowl, NFL players are subjected to physical and mental evaluation processes similar to the draft board.

Since the end of the 19th century, the role of population in military calculations has become increasingly important (Howard 2005). However, the form in which population roles are understood has changed. During the period of mass European conscript armies, population was seen as a matter of national security as national armies were recruited only from national citizens. Any decline in the cohorts of military age males in a country would mean a corresponding decline in the overall military potential of that country (Horne 1977). The post-

World War II military environment changed that dynamic. To European military thinkers, population began to be understood in the context of the number of potentially dangerous colonial

subjects. Particularly in Algeria, colonial authorities began to fear the increasing size of cohorts of military age males as those numbers represented an increasing threat to their position in their colonies (Evans 2012).

These notions regarding regulating population tie directly into counterinsurgency theory that began in the early 1960s. Military theorists, particularly in the French school of counterinsurgency, understood that in modern war a dualism emerged where the traditional criteria for victory were not often enough to defeat the enemy. The mobilization of the population for the military as well as political objectives was extremely important to the successful conclusion of a counterinsurgency conflict (Trinquier 1964; Belcher 2012). Similarly, all legitimate social institutions during a conflict would have a subversive parallel structure within the structure of the insurgency. This dualism provides a useful concept for understanding civilian/military interactions in which the institutions of society are now being contested by both groups, and duplicate hierarchies are being created so that each can provide for the complete needs of the citizen.

Trinquier (1964) also noted that counterinsurgency requires special kinds of intelligence.

Unlike conventional military conflicts where information regarding the scope of the enemy forces and the terrain including communications centers and lines of communication is sufficient, counterinsurgency intelligence requires more sophisticated information regarding local population and social networks. Subjecting spatial representation to mathematical modelling – what Crampton (2011) calls “calculable space” - was an important factor in developing an adequate counter-intelligence apparatus (Trinquier 1964). The Vietnam War, unlike previous wars, represented a counterinsurgency conflict built on computer information.

Woodward (2014) notes that digital landscapes have become an increasingly important areas of

study in critical military studies. The Vietnam War represents a point of departure for contemporary analysis of a conflict using computer modelling. Not only were computers utilized to collect and process data, but they were also used to develop predictive models to aid in the doctrine of the United States military (Barnes 2008). The Vietnam War was comprehensively modelled and these models could then be used to study policy (Milstein 1974). Despite the warnings of geographers in the 1990s regarding the use of geospatial technology in the conduct of war (Smith 1992) during and in the aftermath of the First Gulf War, big data analysis of complex military operations using geo-referenced information had in fact already been 20 years old. Much of what geographers are now discussing with respect to counterinsurgency operations

(Belcher 2012) must be framed within the backdrop of policymaking under a modelled reality

(Barnes 2008).

Perhaps one of the most important developments for examining violence in a societal context was the incorporation of the work of French philosopher Michel Foucault and the Italian philosopher Giorgio Agamben into the discipline in the 1990s. Political geography was extremely important in linking the theory behind Foucault’s work into the geographic literature

(see Cramption and Elden 2006) - specifically discussing how institutions create frameworks that encourage communities or large groups of people to self-govern in the best interests of those institutions. This concept aligns with Trinquier’s methods in discussing processes to combat counterinsurgency (Trinquier 1964).

However, while political geography was the initial entry-point into geography, other subfields have benefitted from Foucault’s insights. Foucault’s theories regarding the disciplining and regulating of society tie directly into an understanding of military institutions and structures.

Foucault argued that various practices which emerged over time to protect European populations

were then used to control society (Foucault 2007). The practice of securing the population to prevent the spread of disease and creating districts under the responsibility of district leaders was repurposed to be used as a tool to reinforce authority (Foucault 2007). Later, this type of curfew was specifically incorporated into French counterinsurgency doctrine (Trinquier 1964).

Additionally, Foucault’s engagement with populations (Legg 2005; Philo 2001) highlights an understanding and articulation of the type of control amongst populations required for the successful execution of counterinsurgency warfare. Likewise, the writings of Agamben

(1998) can also be linked to the progression of activities in counterinsurgency operations. In

Homo Sacer (1998), he argues that “today it is not the city but rather the camp that is the fundamental biopolitical paradigm of the West” (Agamben 1998, 181). To define ‘the camp’

Agamben tells us “…the camp is the new, hidden regulator of the inscription of life in the order”

(Agamben 1998). Similarities can be then drawn between the function of the camp in

Agamben’s articulation of biopolitics and the social and territorial paradigms of McColl’s

Insurgent State, as well as Trinquier’s conception of modern warfare by understanding the camp as being a functional representation of the concept of the base network in the writings of McColl and Trinquier. Recent work in articulating the camp centers on problematizing this concept in all its forms (Minca 2005, 2015).

Additionally, military landscape also changes with respect to scale. Especially within the field of geography, scale plays an important role in framing spatial processes. Likewise,

Trinquier (1964) argues for the incorporation of scale as well as time in the creation of counterinsurgency plans. Military landscapes that are studied at the level of the battlefield often engage in discourses of remembrance of specific engagements and locations (Hurt 2010). The main focus of this type of inquiry is an attempt to understand the underlying political discourse

behind the construction of these landscapes (Gregory 2004). At a larger scale, military geographies are examined to understand urban development and morphologies (Farish 2003).

Studies also suggest that landscape features that can be perceived as being non-military have their origins based upon military necessity (Coaffee et al. 2009). Memorial landscapes have also been understood to portray a particularly militaristic undertone if not overtone in their construction, most notably at the National Mall in Washington, D.C. (Doss 2008; Savage 2009).

There are limitations to this framework. First, military structures often operate as a ‘black box’ which makes data collection often difficult to perform (Woodward 2005). Data regarding military operations is often withheld for security reasons for a period of time in order to protect intelligence advantages that permit a better functioning of military processes. Second, many of these military operations rely on civilian perspectives and norms to provide a context for these processes.

Research in military geography has been acknowledged as being biased towards supporting military goals (Woodward 2005). Critical military studies as defined by Rech et al.

(2015) is a much larger field than military geography that focuses on research challenging the authority of military institutions. In terms of landscape analysis much of what has been done relating to military landscapes has borrowed from other traditions within geography such as

Marxist and Feminist critiques that study the masculinization and marginalization that military institutions can create (Enloe 2007). Military geographers also use concepts from political ecology and human/environment interactions to develop frameworks for analyzing the influence that military actions have on the environment (Peluso and Vandergeest 2011).

Woodward (2005) suggests that military geography has often been hampered because the nature of military operations necessitates that data about military functions are not often

available. Although data may be initially confidential, over time datasets, especially those compiled for evaluating the success of programs have been made publically available. The datasets that will be used in this research are comprehensive and exist for a number of years.

The second issue is that military landscape and environment studies tend to understand the military from a civilian perspective in which the civilian ways of seeing and understanding the world form the lens to investigate the military viewpoint regarding these processes. Other than a few discussions (Belcher 2012; Belcher 2014; Clout and Gosme 2003), there has been very little investigation of the systematic doctrine encoded in field manuals that discuss specifically how the military views all aspects of its functioning. Most military geography studies understand military landscapes from a standpoint of policy instead of doctrine. Policy being how the military interacts with the outside world, and doctrine being how the military functions internally.

Despite the extensive studies into the link between military institutions and geographical institutions, there is a continuing debate on the role that geography plays in the supporting the military (Tyner 2009; Wainwright 2016). What has emerged from a geographic analysis of the functioning of the military is the permanent and growing awareness of the interconnections between the military and civilian spheres. The evolution of academic scholarship in this area has led to the development and implementation of new concepts and theories regarding the needs and requirements of government institutions.

2.3 Human/Environment Studies

Critical studies analyzing the influence that military operations had on the environment go back at least to the early 1970s (Lacoste 1973; Bowd and Clayton 2013). The environment is

understood not merely as a setting for military operations, but also as a place providing the raw materials with which to conduct military conflict (Le Billon 2001). Likewise landscape provides an important dimension for understanding how military functions are articulated in the natural environment (Muir 1999). In this relationship between military function and the environment, the environment guides and influences military functioning and military functioning can metabolize and alter environmental landscapes. Keller (2009) analyzed how the environment directly influenced military action, while other studies analyze how military functions directly influence the landscape (Peluso and Vandergeest 2011). Such influences can either be related to

‘preserving’ the environment (Peluso and Vandergeest 2011) or as part of environmental degradation (Bennett 2001; Davis 2007). Site specific studies have led to further issues regarding national environmental policies with respect to military controlled areas and their conversion to wildlife preserves (Havlick 2011).

Landscape interpretation uses the elements of a morphology that can be in effect ‘read’ using specific axioms as guidelines for interpretation (Mitchell 2008). Within the context of military landscapes, research has developed along similar conceptual lines, but also branched out into other areas of inquiry (Woodward 2014). Being able to define definitively a military landscape is difficult, and how to construct such an entity has been debated within the literature

(Pearson et al. 2010). Traditional methods used by military geographers attempt to create typologies around categorizations of military processes (Pearson 2012) Landscape in these methods is understood from the standpoint of tactics in ‘traditional’ military doctrine, utilizing concepts in which a Clausewitzian understanding of the landscape is described (Clausewitz

1984). In such an interpretation, the environment is understood as aiding offensive or defensive

operations. These methods are also not necessarily used in a positive reference towards actual military action, although landscape is used along traditional lines of military inquiry.

The spatial/chorological revolution in geography that occurred in the late 1950s and developed through the 1960s moved geography away from a regional perspective that had integrated the environment into research on regions (Turner 2002). Implicit within the regional framework had been an understanding that environmental determinism played a role in shaping the spatial dispersion and functions of the human settlements within that region. The quantitative revolution, however, did not place as much emphasis on the environment as it did in developing new statistical methods for analyzing societal infrastructure. Human-environment geography only gained momentum in the late 1980s as the environment became more of a social priority for research. Developing out of this new research was a greater understanding of how social systems are integrated with and influence the environment at multiple scales through multiple teleconnections. The relationship and delineation between the ‘natural’ world and ‘human’ world has been at the core of ecosystems science since its inception (Tansley 1935). While organisms can exhibit social interactions, only humans have exhibited political interactions and more specifically military interactions. Although military interactions are limited to the human sphere, military terms have been used as metaphors to describe a variety of natural processes from weather fronts to invasive species. These interconnections suggest that military geography is a study not only of human processes but also has the potential to provide insight into human interaction with ‘natural’ processes as well.

There is also a divide between human-environment studies within geography and similar studies within the field of ecology. Human-environment studies often do not define the term

‘ecology’ as an ecologist would. Walker (2005, 78) defined ecology as “the study of the

interrelationships between living organisms and their physical environment.” Whereas an introductory textbook on ecosystem science frames ‘ecology’ by discussing the ecosystem as

“the interacting system made up of all the living and non-living objects in a specified volume of space” (Weathers et al. 2013, 3). A key difference then is that in ecology, the study area is defined as a ‘specified volume of space’. This places the framing of the ecosystem in the hands of the ecologist and it implicitly denotes the role that the researcher has in setting the boundaries for nature. In addition, ecologists specifically use the term ‘space’ to define the area of study whereas human-environment geographers use the term ‘physical environment’ instead. In ecology, there is no delineation between what in geography is often termed the ‘natural’ environment and the human environment.

Over time both approaches are converging as ecologists now draw from not only the social sciences but also the humanities to provide inspiration for research (Jax 2010).

Particularly in studying ecosystem functioning, ecologists are interested in understanding the conceptual processes that lead societies to construct particular ‘frames’ (Jax 2010). Current research suggests that our understanding of how human society interacts with ‘natural’ systems is increasingly taking into account the complexity of such relationships (Ostrom and Cox 2010).

There is a continued interest in understanding the specific mechanisms that guide social change and environmental change particularly to stabilize such systems. While military geography has historically been interested in how the environment supported military operations, current research is expanding into the various types of stochastic events that military functioning has on the landscape.

Scholarship in political ecology and related fields has over the past two decades been firmly engaged with understanding the complex interactions between conflict, society and the

environment (Le Billon 2001; Peluso and Vandergeest 2011). Building off a discussion of resources as a driving force behind conflict (Le Billon 2001; Peluso and Vandergeest 2011), there have been studies of the utilization of environmental factors to understand the spatial patterns of conflict (Buhaug et al. 2009; Detges 2014; Koubi et al. 2014). Yet, while there is a strong engagement with natural resources, for this study, an understanding of the relationship between forest and/or jungle cover is the most relevant.

The notion of “tropicality”, which is a term also in military geography (Woodward 2014), should be understood within the context of how we imagine the tropics (Savage 2004). This imagining of landscapes and their processes can be thought of as an early attempt at defining ecosystem functioning (Bowd and Clayton 2003). Peluso and Vandergeest (2001; 2011) highlight how the geographical imaginations of the environments in Southeast Asia facilitated the manipulation of forested environments underlie the discourses used to frame how these areas are brought under governmental control. Peluso and Vandergeest (2001; 2011) use the term

‘conflict timber’ to highlight strategies used to impose governmental control over forested areas through the militarization and securitization of forest management practices.

McElwee (2016) has specifically discussed the role of such environmental policies in managing forested areas under communist rule in Vietnam. However, McElwee provides little discussion of the role or processes surrounding the specific use of defoliants as counterinsurgency methods that were used during the Vietnam War. However, there is a growing body of literature that directly addresses the role of counterinsurgency in land use/land cover change (Roberts 2016; Castro-Nunez et al 2017). Roberts (2016) analyzed the impacts of the panoply of defoliation tactics during the Vietnam War in the region of the A Luoi Mountains, highlighting the impact that such activity had on the structure of the sylvosystems in the region.

Castro-Nunez et al (2017), found that the area of insurgency and conflict is spatially stationary.

It is not spatially dynamic and contains a large temporal footprint as the armed-conflict continues over many years. This static, low intensity conflict provides numerous ways of assessing its presence as a driver of land cover change over time.

The field of environmental security has furthered our understanding of the causal links between forest-cover and armed-conflict (de Jong et al. 2007). The three general pathways for causal links between changes in forest cover and armed conflict are: natural resource scarcity

(Homer-Dixon 1994), competition and accessibility (Peluso and Watts 2001), and opportunities for concealment of activities (Collier and Hoeffler 2004). These three concepts indicate several other more broad scale patterns of governance that are drivers of these pathways. These are a weak state presence, valuable natural resources for financing the infrastructure of military forces, population grievances, and displacement of a civilian population by forces attempting to expand territorial control (Collier and Hoeffler 2004, Rustad and Binningsbo 2012, Rustand et al 2008, de Jong et al 2007). However, while these principles may hold true for certain types of insurgencies, the setting for this study possesses some unique differences.

The insurgent forces of the Viet Cong and North Vietnamese Army (NVA) represented a unique organizational structure (Pike 1966). Using Mao’s doctrine of Dau Tranh (Karnow 1984) the conflict in South Vietnam was designed to break down divisions between the military and civilian sphere and the population controlled by the Government of South Vietnam (GVSN) and that under the control of the National Liberation Front (NLF). The communist forces could at any time devolve from cohesive military formations and blend into the population and the environment for an indeterminate period of time.

Other locations where the relationship between counterinsurgency and forests have been studied include Cambodia and Burma (Rustad et al. 2008), South Sudan (Gorsevski, Geores and

Kasischke 2013), Rwanda (Ordway 2015), Colombia (Albertus and Kaplan 2012; Castro-Nunez et al. 2017) and Turkey (van Etten et al. 2008). Although significant changes in regions affected by insurgences have been documented, these changes can be attributed to depopulation or reduced agricultural production (Aide and Grau 2004; Hecht and Saatchi 2007). The specific mechanisms that drive changes in forest cover are often not caused by direct violence or direct counterinsurgency techniques such as defoliation spraying, napalm or mechanical deforestation.

Instead the drivers behind such changes are driven by socio-economic practices. The context of how forested cover is utilized in specific cases as a driver in environmental outcomes has lead several researchers (Harwell 2010; Baumann and Kuemmerle 2016; Castro-Nunez et al. 2017) to argue that many studies fail to capture the complexity of such conflicts and their peculiarity as events.

The bulk of this research supports Trinquier’s (1964) assertions that forested regions play an important role in facilitating the development of an armed clandestine organization. Yet,

McColl (1969) notes that a focus on the countryside and remote regions should not be misconstrued as the control of these areas being the reason for these insurgent groups being there. Rather, they have been forced into these areas in an effort to continue the fight in an attempt to build up enough strength to reassert control over population centers once the insurgent state has developed enough aggregate strength. The interest in analyzing and studying the extent, duration and development of insurgent conflicts has grown with the proliferation of such conflicts and the development of computer modelling techniques and statistical methods. The final section incorporates these concepts under the umbrella term of Historical Geographic

Information Science (HGIS) although they are not confined to this specific subfield of

GIScience.

2.4 Historical Geographic Information Science

HGIS is one of a plethora of specific application areas in geographic information science that developed in the late 1990s (Gregory and Healey 2007). As a tool for analyzing the spatial relationships of physical remains, GIS was seen early on as an important resource that could be used in areas relating to historical and archeological research (Chapman 2006). Three advantages of using GIS in historical research have been identified by Gregory (2003). First, spatial database development can integrate disparate data sets through their geo-registration with respect to the surface of the Earth. Archives represent a vast source of data that can be interpreted and integrated into a GIS database for understanding the spatial dimensions of historical events that might have eluded modern scholars (Gregory and Healey 2007). Second, a

GIS approach permits data to be visualized using maps and other geo-visualization techniques such as animations and virtual landscapes. Third, GIS allows different types of spatial analysis in which the coordinate locations of the features under investigation are an explicit part of the analysis. This is related to the concept of calculable space mentioned earlier.

During his time as Secretary of Defense for the Kennedy Administration and later the

Johnson Administration, Robert McNamara was often referred to as the ‘human computer’

(Burleigh 2013). More than anyone else, McNamara represented the technological “buy in” of the U.S. military to fight the conflict using their overwhelming technological superiority. This was manifested not only in the equipment used to fight the conflict but also in the sophisticated programs to gather and process intelligence. The Vietnam War represents the first instance of

contemporary generated computer data that can be processed for use in today’s computing environment with a minimum of reformatting. In a discussion relating the use of GIS to military activities during the First Gulf War, it has been claimed that: “The development of sophisticated computerized cartographic technology has in the last year, definitively altered the way in which modern warfare is fought and staged and the way it is consumed by a global public transformed into video voyeurs. By comparison, academic advocacy of GIS seems deliriously detached”

(Smith 1992, 257). This statement ignores the programs from the Vietnam War that impacted the policies for conducting that conflict as well. GPS came of age in the First Gulf War but digital data processing and mapping were used much earlier by the military.

GIS has also changed the ways in which geography is perceived by other fields. The epistemological foundation of GIS were developed concurrently with the Vietnam War during the 1960s. These foundations have been contentious since the explosion of the use of this technology in the last decade of the 20th Century (Chrisman 1999). Again, the advent of the Gulf war opened up a wide discussion as to the implications of geospatial technologies on society through their applications (Pickles 1992). Current critical research in historical geography also discusses the links between geography and military innovation in intelligence during the Cold

War (Barnes 2008).

From the perspective of HGIS, the Vietnam War datasets represent a large data source to understand better the development of this conflict. However, these data have issues similar to the standard ones that arise in HGIS applications. While the source data are digital instead of existing as physical textual copies, one must still carefully process these data as they contain many errors. As an epistemological element, HGIS should seek to strike a balance between quantitative and qualitative methodologies. In the construction of the database for the HGIS

used here, the epistemology of historical discourse must also be accounted for to show an accurate expression of the historical events being recorded. Historical data are not always spatially accurate and these spatial inaccuracies must always be accounted for in a GIS (De Moor and Wiedemann 2001; Knowles 2008). Database construction has long been acknowledged as an important component in regional analysis (Berry 1964), and regional analysis of temporal events can show patterns that are often missed using conventional methods of historical analysis.

Special attention must be taken to account for the practices surrounding not only the encoding of the original data files but also the fundamental structure of the spatial data. One must consult whatever metadata exists regarding the data carefully during the preprocessing steps to ensure that the integrity of individual features is maintained during the preprocessing steps. One must also be familiar with earlier forms of cartographic representation and understand how to modify these spatial formats into outputs that can be interpreted by today’s geospatial software (Gregory and Healey 2007). Modern benchmark geographic surveys like WGS 1984 had not been completed yet and the researcher has to be aware of other surveys to ensure that all relevant data layers align properly in relation to each other.

Modern scholarship involving the analysis of conflict often makes use of quantitative data (Rustad et al. 2008). The development of the Armed Conflict Location and Event Dataset or ACLED (Raleigh et al. 2010) is but one instance of attempting to quantify violence for spatial and statistical analysis. Quantitative analysis during the Vietnam War represents an earlier attempt at developing quantitative data sources for statistical analysis of violence. Yet, as has been noted by Appy (2003), the Vietnam War effort to provide sound spatial data can be called into question in some instances. However, despite the issues with these questions, the spatial data collected during the Vietnam War provided a basis for decision making (Burleigh 2013;

Kalyvas and Kocher 2009). It is in this instance that these data provide important tools for understanding the Vietnam War; they provide a unique perspective at a particular geographic scale that is the core scale at which the historical narrative of these studies is often conducted

(Karnow 1984).

2.5 Summary

Earlier studies have approached the interrelations between landscape and military policy during the Vietnam War mainly from a standpoint of direct action on the landscape (Zierler

2011). Very little attention has been paid to the abundance of data collected during the Vietnam

War, although there is an emergence of research in human ecology and political science

(Kalyvas and Kocher 2009) as well as in ecology (Robert 2016) that has revisited these data sources to understand issues of sovereignty (Kocher, Pepinsky and Kalyvas 2011) as well as landscape change in specific ecological areas (Robert 2016). This literature review illustrates how Trinquier’s concepts for modern war can be grounded in current research in geography and affiliated fields. This study will also perform empirical analyses that integrates textual and spatial data into a more holistic approach. This research project will be more comprehensive, not just to understand what happened during the conflict but how the definitions of ‘jungle’ used by the U.S. military influenced outcomes.

CHAPTER 3 – THE INSURGENCY AND THE JUNGLE IN THE INDOCHINA WARS

3.1 Introduction

The discursive underpinnings behind the U.S. doctrine in South Vietnam has been characterized as militant tropicality (Clayton 2013). This militarized form of ‘tropicality’ highlights the ways in which the environment and mode of combat were discursively constructed by Western institutions. This chapter builds on these concepts of Clayton (2013) to develop the historical narrative further and to situate it within the context of the dissertation. The jungle as both a physical region and a place name played an important role in the history of conflict in

Indochina. From the earliest period of colonial exploration and expansion, the jungle highlands in Tonkin (North Vietnam) became areas of constant skirmishing against external incursions and internal dissidents (Porch 1991). Vietnam has often been characterized as two rice bowls connected by a carrying stick, with the twin rice growing deltas of the Mekong River in the

South and the Red River in the North serving as the focal points of French colonial administration (Windrow 2004). Particularly in the North, the expansive Red River Delta served as the center of gravity for French colonial administration with the delta area serving as the focal point of French economic development.

During the campaign in Tonkin (1883-1885) to establish French suzerainty over most of

North Vietnam, fighting quickly gravitated towards the forested highlands surrounding Lang

Song to the east and the highlands around Son La to the west. It was these areas in Tonkin that

France spent the remaining decades prior to World War I pacifying. Many French soldiers such as Hubert Lyautey and Joseph Gallieni (Lyautey later incorporated Morocco into the French

Colonial empire while Gallieni became the foremost French colonial soldier of the era and later played a pivotal role in the battle of the Marne during World War I) spent their formative years developing tactics to deal with operations in this difficult environment. From an ethnographic standpoint, the wooded uplands in Vietnam were inhabited by different ethnic groups. The

Vietnamese occupied the deltas and various Montagnard populations inhabited the uplands.

The intermittent campaigning that occurred in French Indochina in these areas was suited to the military technology of the era. Possessing few roads and even fewer railroads, these uplands could only be penetrated by infantry with limited logistical and artillery support. Like most of the colonial forces during this period, French troops were composed of locally recruited forces around a core of French professional regulars which by the turn of the 20th century consisted of colonial troops and foreign legionnaires (Porch 1991). In terms of administration, the French colonial bureaucracy was much less pronounced in these areas. Dien Bien Phu, later to be the site of a major battle during the French Indochina War, contained only a dirt track, RP

41, and was occupied by only a junior functionary from the French colonial administration

(Windrow 2004). During this period, the uplands were often viewed as much more desirable postings because these locations usually had milder climates than those in the delta areas and along the coast (Porch 1991). French ground forces were characterized as being able to operate with equal efficiency to local insurgents in these regions (Porch 1991).

The development of public works projects during the colonial period was meant to materially integrate the disparate regions of the colony as well as create a closer association between colonizer and colonized (Del Testa 1999). The development of railway transportation

35 in French Indochina forms a key element in Indochina’s colonial history. The first period of construction aligns with the period of attempted cultural assimilation. Prior to the 1920’s French policy was purposefully directed at assimilating colonial peoples (Betts 1961, 1985). Yet, as Del

Testa (1999) argues, during the 1920’s there was a turn away from assimilationist policies towards directing a more exclusionary policy towards the Indochinese population. It is against this backdrop in the change of socio-political climate within Indochina that the development of

Tropicality (Bowd and Clayton 2003; Bowd and Clayton 2013) occurred in the French colonial context.

Within the nexus of material, social, and technological changes there emerged a greater division between colonizer and colonized in French Indochina (Bowd and Clayton 2003; Bowd and Clayton 2013; Del Testa 1999). The slow diffusion of military technology into Indochina also meant that the French occupation force in Indochina was less advanced than their French

European counterparts. Despite the lack of its presence, the technology and means of governance were sufficient and suitable for incorporating more parts of Tonkin under the control of the colonial bureaucracy. While the period of the interwar years witnessed a dramatic change in military technology, many colonial forces were not modernized along the lines of their French counterparts in Europe. The French troops that surrendered to the Japanese in March of 1945 were not up to date with the technological changes that occurred during the Second World War.

However, the period from 1945-1954 witnessed a marked change in how French forces operated within the jungle environment.

Like other colonies during the Second World War, Indochina stayed loyal to the Vichy government. Under General DeGaulle’s leadership, the reconquest of all of France’s colonies was a major aspect of Free French policy. While attempts at bringing Vichy colonies under Free

French control was met with strong resistance, the 1942 allied invasion of French North Africa brought that French colony under allied control. By early 1945, Gaullist forces had turned their eyes towards reclaiming French Indochina from Vichy forces. By this point in the war, the continued Japanese presence in Indochina was viewed as being collaborationist. The Japanese overthrow of Vichy forces in March, 1945 could have been an advantage for Gaullist designs in

Indochina. Instead, the reoccupation of Indochina turned into one based on the liberation of occupied territory from an Axis power.

The French forces that were able to escape the Japanese attack retreated into the

highlands bordering Tonkin to fight a rear-guard action as they further retreated into Nationalist

China (Logevall 2012). In an attempt to bolster resistance to Japanese troops in Indochina, the

British intelligence forces in British India, Force 136, in collaboration with French forces began

to parachute operatives into Laos and northern Vietnam to create maquis forces to operate

against the Japanese. In addition to these forces operating along the periphery of the Red River

Delta, the Viet Minh emerged as another anti-Japanese guerilla group. The Viet Minh were led

by Ho Chi Minh with Vo Nguyen Giap as the director of their military forces. The Viet Minh

operated along the Chinese border between Cao Bang and Lang Son. The U.S. Office of

Strategic Services (OSS) (the U.S. equivalent of the British intelligence forces) parachuted a

team into northern Tonkin to link up with and provide an advisory capacity to the Viet Minh

who were important in locating downed U.S. airmen.

The destruction of the French garrison in the spring of 1945 by the Japanese can be

viewed from two different perspectives. First, from a political and cultural perspective,

historians have spoken of how the defeat of the French forces broke the ‘spell’ of French

colonialism in Indochina (Logevall 2013). The Japanese occupation of the various colonies in

Southeast Asia during the Second World War represented a political and cultural paradigm shift. It represented a tangible example of an Asian military that displayed military superiority over a Western military. The Japanese occupation also initiated nascent national political organizations to aid in the political agenda of the Japanese occupation of these colonies

(Logevall et al. 2013).

Second, from a military perspective, the destruction of the French garrison removed that unique relationship with the local areas that long serving colonial forces would often develop.

In a three volume study of the last commander of the French Far Eastern Expeditionary corps,

General Paul Ely summarized the lessons learned from the Indochina War. He found that a key element that was attributed to the defeat of the French military in Southeast Asia was the lack of any developed native affairs officers to provide intelligence to the French military (Croizat

1966). Citing the example of the Arab Bureau officers that had been developed by Lyautey and were reinforced by SAS formations during the Algerian War (1955-1962), the study argued that in Indochina, there was no local intelligence organization to provide the type of local knowledge and accurate terrain intelligence that could have been key to the execution of military operations early in the conflict. The destruction of the Indochina garrison by the

Japanese had subtle consequences for the forces that arrived in 1945 to regain control of the colony.

3.2 The Jungle During the First Indochina War

The force that was assembled to retake French Indochina from the Japanese was a

French corps structured and designed for combat in the European theater, not the Pacific theater of operation (Jackson 2005). The battle corps consisted of two combat infantry divisions, a

38 battle group from the French second armored division, and a brigade of naval troops.

Additionally, a commando formation known as the Light Intervention Corps (CLI) was deployed that consisted of a series of commando formations. However, the complexion of the re-conquest changed when the Japanese surrendered to end the Second World War.

Immediately, the Viet Minh began to fill the power vacuum created by the Japanese surrender

(Fall 1961). The struggle for the French now shifted to retaking military and political control from native guerilla units who viewed their task as one of liberation from colonial rule.

As described by Jackson (2005) the French force was not equipped to wage the kind of colonial conflict against poorly armed and equipped insurgents. As previously mentioned, this force was equipped to fight a conventional battle in the European theater of the Second World

War. The force did not contain the requisite number of troops nor the requisite types of troops to deal with the rapidly expanding network of the Viet Minh. Between the surrender of the

Japanese and February 1946 when the first French forces re-entered North Vietnam, the Viet

Minh had time to establish their administration, train their military forces, and subdue other non-communist, nationalist groups in the region. Ho Chi Minh declared Vietnam’s independence from colonial rule in September, 1945. Fall (1961) noted that the French had lost the first round of the Indochina War before it even started. For the French, the Viet Minh now formed an insurgency against their rule.

Operating along best practices, the French forces first occupied the Saigon area in the

South and the Red River Delta around Hanoi in 1946. However, unlike in the latter half of the

Indochina War, at this time, there was no distinct delineation between areas controlled by the

French versus those controlled by the Viet Minh. After the French occupied the Red River

Delta region, the Viet Minh moved to jungle sanctuaries in the highlands west of the delta

region near the Chinese border. The period from 1946-1948 witnessed French attempts to

bring the entirety of Indochina again under control of French forces. From 1947-1948 several

operations, notably “LEA” and “CEINTURE” were launched to re-acquire the population

centers outside of the Red River Delta. Between 1948 and 1950, French forces reoccupied the

border outposts from the earlier colonial periods and attempted to maintain freedom of

maneuver throughout the highland regions in Tonkin.

However, unlike the previous units stationed in Indochina, these formations did not possess the earlier outlook on fighting in these locations. Unlike their predecessors, these troops were dependent upon a centralized logistical system that was bounded by the rivers, roads and airfields throughout Indochina. Infantry forces were mechanized and became more dependent upon the poor road infrastructure. In many ways modern, mobile equipment became a liability in the rugged terrain possessing poor road infrastructure. Also, unlike earlier eras, the infantry soldier’s equipment advantage which existed at the end of the 19th century had eroded by the early 1950s. Instead of being individually aggressive and being willing to respond effectively to ambushes (Porch 1991), French forces during the French Indochina War rarely ranged outside of close air support or artillery/tank support.

Infantry unit organizational structure followed this transformation (Jackson 2005). By

1953, the only forces that were capable of fighting the Viet Minh in the jungle environment of the regions around Tonkin were the GCMA (Counterguerilla forces) and parachute formations

(Jackson 2005, Pissardy 1982). These forces adopted the earlier traits of relying on what equipment could be carried by the individual soldier or pack animals, operating aggressively, and being willing to move off the roads into the jungles.

Additionally, from 1948-1950, the French began the slow process of separating the Red

River Delta from the rest of Tonkin. At that time, the French commanding officer in the North,

General Alessandri, attempted to seal off the Red River Delta from Viet Minh to restrict their access to the delta’s rice crop. Also, as the war dragged on, the French army chief-of-staff

General Revers arrived to conduct an in-depth tour of the theater and develop a report on strategic considerations. In alignment with the changing ways in which the French were engaging with the jungle environment, the Revers Report advocated the withdrawal of French troops to an area around the Red River Delta to regain the maneuverability of the French troops that were distributed along the border posts.

The destruction of French forces along Colonial Route 4 which ran parallel to the

Chinese border connecting Cao Bang to Lang Son accelerated the French abandonment of these jungle areas to the Viet Minh. It was with the arrival of General de Lattre in 1950 that the

French position permanently shifted to one that understood the jungle as an overt domain of the

Viet Minh. Embarking on an ambitious construction plan, de Lattre attempted to seal the delta area off from the rest of Tonkin with an series of concrete fortifications known as the de Lattre line that were more reminiscent of the Maginot Line than earlier techniques of colonial warfare.

Here was an attempt to delineate the natural environment into separate regions of political and military control: similar to Agarwal’s notion of ‘Environmental Governance’.

It is against this backdrop of successive retreat from the jungle highlands of Indochina to the open river valleys and deltas by French forces, that in 1953 the political scientist Bernard Fall first traveled to French Indochina to conduct field research for his dissertation. As a veteran of the French military during the Second World War, Fall was given extraordinary access to the

French military then fighting in Indochina. Over the next 14 years, Fall would become one of

41 the leading research experts in Southeast Asia and an outspoken critic of American and South

Vietnamese policy during the late 1950s and early 1960s. His letters home to his future wife formed the core of his first book The Street Without Joy (Fall 1961). Arriving during the latter end of the conflict, the French forces were on the defensive and many outposts had been surrounded by Vietnamese forces as the Viet Minh moved into northern Laos.

To resupply these forces, French forces had become increasingly reliant on areal resupply to reinforce these outposts. An excerpt from Bernard Fall’s book relays his experiences on a trip to resupply such a location:

“Squeezed in with the pilots and the French navigator, I could look about the countryside. It’s really too beautiful for words; the lacework of the little dikes with their rice paddies, the dark green patches of fields hidden behind bamboo clusters, and trees; then the jagged limestone cliffs rising steeply out of the dishpan flat plain and suddenly, like a carpet of blue-green velvet--the jungle. This whole change of scenery takes place in less than ten minutes. With the last of the rice paddy behind us the whole landscape sort of turns silent. No trace of human activity, no foot-paths, draft animals, roads. ‘Viet territory,’ says the navigator over the intercom. (Fall 1961, 108)”

Here, the image of the jungle has been transformed. It is described in a dialectical relationship to that of the delta. While the delta is ordered and peppered with man-made structures indicating the presence of inhabitants even if none could be seen, the mountainous periphery of Tonkin was described as silent, devoid of human activity and monolithic in appearance. Fall’s navigator even goes as far too arbitrarily describe the entirety of this land cover as ‘Viet territory’. This scene is interesting as it provides an insight into the role that technology played in the reimagining of the jungle environment.

From the perspective of the French military, the landscape outside of the delta area was impenetrable to modern mechanized forces and largely devoid of infrastructural development.

Only in the few open valleys or areas with airfields could the French maintain their full military

42 apparatus. This image was realized with the development of the fortified air-land base at Na San in 1953. As the Viet Minh forces began to overrun the highlands in western Tonkin, smaller

French outposts retreated to these larger bases that could be supplied by air. Na San was able to withstand repeated enemy assault and to maintain a French force entirely by air. As the Fall excerpt indicates, by the final phase of the French Indochina War, aerial resupply became the preferred method for resupplying French outposts.

As Fall was conducting his field research in Indochina, a new commander-in-chief for

Indochina arrived in Saigon. General Navarre who was to oversee the final battles of the

Indochina War decided to take the airbase concept used at Na San and utilize this concept to protect Laos from Viet Minh invasion. Navarre’s lack of knowledge of the specific characteristics of the geography of the theater of operations was seen as a positive and observers thought that he would bring a new way for dealing with the difficulties of fighting in Indochina.

Instead, Navarre was to fall in the same trap as all previous commanders, trying to draw the Viet

Minh into a conventional ‘pitched battle’ where the Viet Minh regular forces would be annihilated by superior firepower.

Yet again, the jungle played an important part in deciding the methods of French operational deployment. The valley surrounding Dien Bien Phu was considered as ideal for the construction of an airbase. First, this valley was remote from the Red River Delta and could only be resupplied by the French through aerial resupply. It was felt that the logistical complexities that faced the French would also face the Viet Minh and they would not be able to resupply their own forces because of the same issues of fighting in the jungle far away from their logistic bases.

Secondly, it was felt that heavy weapons could not be transported into such a remote region and

43 that the size of the valley would allow the French to maneuver units and artillery to secure the area surrounding the base.

Unfortunately for the French, the Viet Minh logistic structure was designed to operate in this jungle environment (Schrader 2015). Instead of relying on mechanized transportation and heavy vehicles, the Viet Minh logistic structure was able to decentralize and work outside of

Western logistical infrastructure. The inability of the French forces to adapt to the unique environment offered by jungles of Southeast Asia was a leading cause of their defeat in

Southeast Asia. It must be noted, however, again by Fall (1961), that linking the Viet Minh specifically to the jungle as ‘Viet territory’ is also incorrect.

By the fall of 1953, despite the massive preponderance of troops and defensive structures such as the de Lattre line in the Red River delta, the Viet Minh has succeeded in infiltrating these locations as well. By the summer of 1954 in the aftermath of the Geneva Accords, most of

Tonkin had been infiltrated by insurgents including the Red River Delta. Additionally, other areas such as the coastal plain between Quang Tri and Hue and the central highlands around An

Khe had all been infiltrated by the Viet Minh. Yet, when the United States took over as the main supporter for the nascent Republic of South Vietnam, there was again this framing of the jungle as the environment of the insurgent.

However, the French Military’s the framing of the jungle during the Indochina War through a discourse of Tropicality homogenized the cultural landscape within the region (Croizat

1966; Clayton 2013; Roberts 2016). Large segments of the Viet Minh cadre and insurgents hiding within these jungles had similar stereotypes to Western forces and only opted to utilize the development of these locations as base areas as a stratagem when the initial attempts to

44 control the population centers against overwhelming French military superiority failed (McColl

1969).

3.3 The Jungle During the Inter-War Period

The 1954 Geneva Accord created the state of South Vietnam as the part of Indochina along the coast that was south of the 17th parallel; it was bordered in the interior by Cambodia in the south, then Laos to the north and finally North Vietnam was its neighbor above the 17th parallel (see Figure 3.1). It comprised the colonial administrative region of Cochin China and the southern half of Annam. It was also a state that contained interior highlands in its central and northern reaches and the delta region of the Mekong River in the south.

It is a little discussed issue in research relating to conflict in Indochina that during the

French Indochina War, the base areas for the Vietnamese led Viet Minh in fact lay in locations that were predominantly populated by Montagnard populations. While many Montagnard were strongly anti-communist as evidenced by the T’ai support of the French, rarely do scholars directly address the mismatch between specific populations and perceived areas of security.

When Ngo Dinh Diem came to power in 1955, he set about structuring his state around a

Catholic Vietnamese conception of South Vietnam. Of the roughly 900,000 Catholic

Vietnamese, many were resettled in the central highlands area from North Vietnam after the partition to bring the highland region under the perceived control of the South Vietnamese government.

Prior to the militarization of U.S. aid in the early 1960’s, the foreign policy of the United

States towards South Vietnam evolved around state building (Carter 2008). State building in

South Vietnam initially focused on the police apparatus and civil service with attempts at

Figure 3.1. The location of South Vietnam with respect to its neighboring states in Southeast Asia.

improving infrastructure. However, Fall (1961) has noted that rural officials by the end of the

1950s and beginning of the 1960s were being assassinated at an alarming rate. Unlike during the period of the earlier conflict, where the French tried to isolate the Red River Delta through the creation of a massive defensive network, the South Vietnamese government with American support sought to devolve this form of defensive structure and decided that the level of intervention should occur at the hamlet level.

Beginning in 1959 with the Agroville program, the South Vietnamese government attempted to move the population into areas of easier access, closer to communications networks that could be easily reached by government forces. This program was met with universal opposition, and even within the South Vietnamese government there was an attempt to halt this program. Only a few years later, a more ambitious program known as the Strategic Hamlets program sought to relocate and concentrate the entire population of rural South Vietnam into specially constructed and secured hamlets. This program which was meant to isolate the population of rural South Vietnam from the nascent Viet Cong movement further contributed to the destabilization in the countryside. As American involvement became more focused on supporting the massive U.S. military buildup (Carter 2008), the focus of development shifted towards infrastructure issues in the major ports and cities of South Vietnam.

3.4 The Jungle During the Second Indochina War

It is against the backdrop of increasing American investment in the rapidly urbanizing coastal areas of South Vietnam, that the Jungle re-emerges as a trope within the counterinsurgency discourse. As Anerican strength lay in the cities along the coast, communist

47 supply routes converged from two basic locations. The first, and perhaps most famous was from the series of supply arteries collectively known as the Ho Chi Minh Trail that stretched from southern North Vietnam into southern Laos and northern Cambodia to supply base camps along the Vietnamese frontier.

This supply network went through the mountainous jungle-covered spine of Indochina.

Aerial attempts at interdiction of the Ho Chi Minh trail (Karnow 1994) provide an important narrative of how the jungle was used as a means of camouflaging the intricate road network.

However for the general public, the prominence of this road often overshadows an equally important transportation network that was used to supply communist forces that were closer to the core of South Vietnam in the Saigon Area: the Sihanouk Trail. This trail based at the lone major saltwater port in Cambodia, Sihanoukville, provided the communist insurgency with close access to a saltwater port which moved supplies to their staging areas more quickly than the Ho

Chi Minh trail.

Although Clayton (2013) highlighted the utilization of defoliants as an example of

Militant Tropicality, the history of the defoliation programs somewhat negates his argument.

The initial use of defoliants in South Vietnam was lobbied for by Diem and the South

Vietnamese Government (Buckingham 1982). From a policy perspective, there was always a concern that the utilization of chemical defoliants could have a negative social impact as much as a positive tactical advantage (Buckingham 1982). Furthermore, contemporary research into understanding the nature of the jungle in which the conflict was being fought recognized the complexity of the ecosystem environment (Westing 1971). Yet it was understood that spraying would not create a landscape that would more approximate a European landscape (Westing

1971). From the mid-1960s forward, there was a consistent and international attempt to study

48 not only the ecological effects of the conflict on the jungle, but to also understand the ethical, legal and environmental ramifications of such activity (Westing 1972).

The development of the term “ecocide” (Galston 1968; Johnstone 1971; Zierler 2011) reflects a recognition that the utilization of these methods of warfare was opening a pandora’s box for future conflicts and was also placing the destruction wrought on the environment on par with the genocide of World War II. Lacoste’s (1973) article on geographical warfare noted but one instance of academic research in the international outcry against the tools and tactics of the

U.S. military in combatting counterinsurgency warfare. Defoliation fundamentally was understood as a means of increasing force efficiency as it made the environment more visible and interpretable to counterinsurgent forces (Buckingham 1982).

3.5 Summary

While the Viet Minh and later Viet Cong became known as expert jungle fighters and the jungle and the night were acknowledged as belonging to the insurgents, the development of this understanding was not innately a part of the insurgency. As discussed in the French military document of lessons learned from the Indochina War (Croizat 1966), the Viet Minh had been ethnic Vietnamese from the delta regions of Vietnam. The communist forces were generally not part of the Montagnard populations of the highlands of Vietnam. This meant that the communist insurgents willingly went into the jungle to learn how to survive in these locations and were willing to endure the hardships that resulted from having their base camps within these areas

(Croizat 1966).

This stands in stark contrast to the forces arrayed against them. These forces were generally not comfortable straying beyond artillery range or from even the most rudimentary

49 road networks available. Even though the French possessed airpower and were able to utilize it to some effect, French forces were one dimensional, only sticking to axes of movement, while the Viet Minh were two dimensional and used the entirety of the landscape within which to maneuver (Croizat 1966). Likewise, the American forces and their South Vietnamese allies built their reliance on conventional military mobility, and even with the deployment of helicopters to improve troop maneuverability, they were never able to develop the cross-country mobility of the communist insurgents.

CHAPTER 4 – SPATIAL DATA COLLECTION AND PRE-PROCESSING

4.1 Data Sources

The data for this study are based on the specific research questions outlined in the

Chapter One that guide the framework of this research. These questions investigate the spatial structure of military/political control of hamlets and the interplay of insurgent and counterinsurgent operations during the Vietnam War. One insurgent strategy, establishing operational base camps from which to infiltrate and convert the population will be matched against a counterinsurgency strategy aimed at restricting the mobility of the insurgents and aiding in the destruction of their base camps. Both strategies operate to a large degree within the jungle environments of forested highlands and lowland mangrove stands.

Because the operations vary in their type, the data were collected from a variety of sources. They can be broken into two main data types: geo-referenced tabular data collected from the section on the Vietnam War of the National Archives and Records Administration

(NARA), and land cover data derived from U.S. Army topographic maps drawn from the Perry-

Castaneda Collection at the University of Texas and Texas Tech University. The NARA data were downloaded on June 13, 2016 and pre-processed over a series of later dates during January and February 2017. The land cover data were downloaded and pre-processed during August to

October, 2017. The pre-processing of the original data sets enabled the various data layers to be integrated into a comprehensive GIS in ArcMap 10.4 in preparation for the analysis stage.

4.2 Pre-Processing NARA Data

The NARA data that were downloaded for this dissertation consist of three separate datasets. The first dataset is the Herbicide Data Files (HERBO-2). These data files contain data regarding the United States Military’s defoliation program known as Operation Ranch Hand.

The second NARA dataset is from the Hamlet Evaluation System File (HES). These data contain information from a program developed to analyze the level of communist penetration in

South Vietnam at the basic social and political structure - the hamlet. The final dataset used from the NARA website is the Enemy Base Area File (BASFA) which was developed to analyze communist base areas during the conflict.

The NARA data files contain data processing characteristics that are similar and data characteristics that are different for each dataset. These datasets were written in formats that were not compatible to current processing systems. All data therefore had to be converted from these earlier formats. The software used to construct these databases is called the National

Military Command System (NMCS) Information Processing System or NIPS. This software was developed in conjunction with IBM in the 1960s. These data were coded in the Extended Binary

Coded Decimal Interchange Code (EBCDIC) format that was used before the introduction of the

American Standard Code for Information Interchange (ASCII) format. Some of the downloaded

NARA data had already been converted from EBCDIC and were stored as files formatted in

ASCII. All remaining EBCDIC data files were converted into the ASCII format using the Kirix

Strata program which is a data management program. These data were then further pre- processed by converting the raw character data from these data files and translating them into a tabular database using Microsoft Excel. The character length for each column was provided in the metadata for each dataset.

While these aspects of data processing represent similarities between the three datasets, when spatially projected, each dataset represented a specific type of spatial data - point, line, or polygon. The HERBO-2 spatial data were encoded as lines representing flight tracks of the aircraft spraying runs. The HES spatial data were encoded as points representing the location of each individual hamlet. Finally, the BASFA spatial data were encoded as polygons to represent the position of enemy base areas. The specific spatial structure of these different data encodings presented different challenges in data pre-processing to create useable geospatial data for analysis. The methodology for the pre-processing of each set of files are discussed in the next sections.

4.2.1 Pre-Processing HERBO-2 Data

The Operation Ranch Hand defoliation campaign ran from 1962 to 1970, but the time period covered in the HERBO-2 dataset extends only from 1965 to 1970. The HERBO-2 data represented a unique issue. There were in fact four different data files that covered the same program. Each data file represented a different attempt at processing the original data. Of the four data sources, the HERBO-2 National Academy of Sciences (NAS) data was chosen because the flight information had already been converted to ASCII and had undergone other preliminary processing.

The metadata associated with the file were used to identify the specific data fields used for storing the geospatial coordinates representing the flight tracks and the other attribute information regarding each track. Table 4.1 presents the data fields associated with the NAS dataset. The HERBO-2 NAS file uses a data structure similar to the spaghetti data model used by the SYMAP computer mapping program developed in the 1960s at the Harvard Spatial

Laboratory (Chrisman 2006). In this data model each record contains the geographic coordinate

53 of a point feature where either the flight path started, stopped, or changed direction. Each flight path consisted of more than one record. Sometimes during the flight, the defoliation stopped at a certain location and was then restarted at another location. Thus the entire flight path could consists of one or more sub-paths. The coding for the different actions that could occur within a flight path is given in the field called Mission Control Log. Each record code contains two characters; the first character is a number (starting with the number ‘1’) and the second character is a letter (starting with the letter ‘A’) for each new path, the code ‘1A’ denoted the starting point of the flight path. The next point in the line denoted by the code ‘1B’ would then either represent the end of the spraying line or indicate a change in direction of the spraying run. A simple straight line path is composed of only two vertices with the codes ‘1A’ and ‘1B’ respectively. If the spraying mission included changes in direction, then additional records are needed. A flight that changed direction once would contain records with the coding ‘1A’, ‘1B’, and ‘1C’ respectively. For each additional change of direction the next letter of the alphabet would be used after the ‘1’. When a flight includes multiple spray runs that are not connected, the number character is incremented to ‘2’. For example, a flight path consisting of two sub- paths, each with no change in direction would have the following codes for the four records of the path – ‘1A’, ‘1B’, ‘2A’, ‘2B’. Spraying missions in the data are composed of as many as six disconnected spraying runs in one mission.

To aid in the pre-processing this dataset, an additional field, called PathID, was added to indicate the records that belonged to an individual flight path. This field was necessary because a mission could have more than one flight path and there was no existing field in the original data to designate individual flight paths. In conjunction with the information in the Mission

Control Log field, all individual records were grouped by the PathID field into a series of

54 individual flight paths. Any flight path that at any point only contained one record for any sub- path was removed from the dataset, so only flight paths that had enough points to be converted into a line feature were used. If there were multiple sub-paths, any sub-path with only one point was then removed and placed in a separate file. A total of 643 records were removed representing 637 potential flight paths.

Table 4.1 The Data Fields Contained in the HERBO-2 NAS Dataset

Field Location Information Contained 1 Date of Flight 2 Changed Mission Flag 3 Combat Tactical Zone 4 Mission Number 5 Province Code 6 Number of Aircraft Scheduled 7 Number of Aircraft Airborne 8 Number of Aircraft Actually Delivered 9 Type of Defoliation Agent 10 Number of Gallons of Defoliant Agent 11 Type of Mission 12 Flight Path Length 13 Area Sprayed (Hectares) 14 Area Sprayed (Acres) 15 Listed Area 16 Helicopter Abort Code 17 Mission Control Log 18 UTM/Military Grid Coordinate

As mentioned previously, each record contained the UTM coordinates denoting the location of each point. However, the UTM coordinates were given using the Military Grid

Reference System (MGRS) developed by the United States Military. MGRS coordinates are stored in the compact form of a single field using a grid reference designed to allow easy

55 analysis with 7.5 minute topographic maps. Building off the UTM system, the MGRS partitions the surface of the earth into a series of 100,000 meter square quadrangles within each UTM grid zone. A MGRS coordinate is a code that concatenates the UTM grid zone number with an

MGRS quadrangle code, and X and Y displacement values from the origin of the MGRS quadrangle. The MGRS quadrangle code consists of a column letter (A–Z, omitting I and O) followed by a row letter (A–V, omitting I and O). The number of digits associated with the X and Y displacements determines the spatial resolution of the coordinate; each digit increases the spatial resolution by a factor of 10. For example, an MGRS coordinate code of 49QAS890255 can be read as: ‘49Q’ identifies the UTM grid zone, ‘AS’ identifies the MGRS quadrangle within the UTM zone, ‘890’ is the X-displacement and ‘255’ is the Y-displacement. Three digits for the displacement means that the spatial resolution is 100 meters.

The first step in the pre-processing used an EXCEL spreadsheet to convert each MGRS coordinate into its corresponding UTM (X,Y) coordinate. The UTM (X,Y) coordinates were then separated into two different spreadsheets because South Vietnam is split over UTM zones

48 and 49. Each of these spreadsheets was then imported into ARCGIS 10.4 as data files in a data layer that used the Indian 1960 datum for UTM Zone 48. The ‘Convert (X,Y) to Points’ command was used to convert the data table of Zone 48 coordinates into a map representation of points in a theme layer. The theme layer was then converted into a shapefile, and this shapefile was reprojected into another shapefile as geographic coordinates (longitude, latitude) using the

Indian 1960 Datum. Two new fields were added to the attribute table to store the longitude and latitude values. The attribute table was then exported as a comma-delimited text file. Next the base layer was converted to the Indian 1960 Datum for UTM Zone 49 and the two text files were merged together and then imported into EXCEL as a new spreadsheet. In EXCEL the

56 spreadsheet was sorted by the PathID field so that all flight paths were put back in their original order. This spreadsheet was them imported back into ARCGIS and converted into a shapefile having geographic coordinates using the Indian 1960 Datum.

These procedures were also followed to construct a shapefile of the 643 single points associated with the flight paths with incomplete data (Figure 4.1). No further pre-processing of these points is needed. However, the next step for the full flight paths was to use the ‘Points to line’ command in ARC TOOLBOX to link together the individual points using the PathID into a shapefile of linear features. The full set of 7097 flights paths across all years is presented in

Figure 4.2.

4.2.2 Pre-Processing BASFA Data

The Enemy Base Area File (BASFA) data were recorded for the years from July 1967 to

July 1971. This specific database represented part of a larger system known as the Operation

Analysis System (OSPANAL). The data used in the construction of this database came from data that had been compiled by the Military Assistance Command Vietnam (MACV). The data contained in NARA consisted of one file that, similar to the HERBO-2 data, had been already translated into ASCII. In the layout of this file, each record corresponds to a year in which the enemy base camp existed. Therefore, one camp could have from one to six records depending upon how long it was in operation.

The metadata associated with the file were used to identify the specific data fields used for storing the geospatial coordinates of the polygon vertices representing the area covered by each enemy base camp, the centroid of that camp and other attribute information regarding that camp. Table 4.2 presents the data fields associated with the BAFSA dataset. Because the thematic information could change from year to year for a given camp while the location

Figure 4.1 HERBO2 flight paths with only the starting location.

Figure 4.2. Complete HERBO-2 flight paths, August 1965 to February 1971.

59 information remained the same, the first step in pre-processing was to separate the geometry from the other attributes into two different spreadsheets. Because of the scale of the analysis

(see Chapter 7), it was decided that the enemy base camps would only have a point representation. The polygon outlines of the camps may be useful for a very local, site specific analysis but that is not the focus of this research. The geometry spreadsheet contained then only a field for the base camp identification number and the coordinate location information.

Although the metadata states that the centroids were represented by UTM coordinates, these coordinates were again formatted in the MGRS notion. However, unlike the other NARA data sources that used only the MGRS format, the BASFA dataset also encoded the camp centroids using geographic coordinates. The (lat, long) coordinates were encoded in one field as aabbccdeeeffggh where: aa is the number of degrees of latitude, bb is the minutes within a degree latitude, cc is the seconds within a minute of latitude, d is the hemisphere north (N) or south (S) of the equator, eee is the number of degrees of longitude, ff is the number of minutes within of a degree of longitude, gg is the number of second within a minute of longitude, and h is the hemisphere east (E) or west (W) of the prime meridian. Because the coordinates were already given in latitude and longitude the pre-processing was less than for the HERBO-2 data.

The next step in the pre-processing these geographic coordinates again used an EXCEL spreadsheet to separate the encoding first into its six different components; then a decimal degree encoding was achieved by dividing the minutes by 60 and the seconds by 3600 and adding these values to the number of degrees.

Table 4.2 The Data Fields Contained in the BAFSA Dataset

Field Location Information Contained 1 Base Area ID Number 2 Province/Country Code 3 Viet Cong Military Region 4 Approximate Center of Mass in UTM Coordinates 5-13 UTM1-UTM9 – Vertices in Area Boundary 4 -24 Combined Campaign Plan Priority for Each Year 25 Date First in a Base Study Area 26 Current Date of UTMs 27 Current Status 28 As of Date for the Current Status 29 Date of Last Update 30 Latitude and Longitude of Center of Mass 31-39 LL1-LL9 = Lat,Long Vertices in Area Boundary 40 Year of Action and Condition Data 41-42 Actions and Conditions for January 43-44 Actions and Conditions for February 45-46 Actions and Conditions for March 47-48 Actions and Conditions for April 49-50 Actions and Conditions for May 51-52 Actions and Conditions for June 52-53 Actions and Conditions for July 54-55 Actions and Conditions for August 56-57 Actions and Conditions for September 58-59 Actions and Conditions for October 60-61 Actions and Conditions for November 62-63 Actions and Conditions for December

The resulting spreadsheet of coordinates was imported into ARCGIS and the ‘Convert

(X,Y) to Points’ command was again used to convert the data table of coordinates into a map representation of points in a theme layer. The theme layer was then converted into a shapefile,

61 having the Indian 1960 Datum. Figure 4.3 displays the spatial distribution of the enemy base camps.

Figure 4.3 The locations of enemy base camps.

Next, the attribute spreadsheet was processed in which all temporal data were combined into one record in the table so that all of the attributes associated with a camp could be joined to the point shapefile of camps in a one-to-one relationship. The attribute spreadsheet was then imported as a comma-delimited text file into ARCGIS 10.4 and attached to the base camp shapefile. The final step was then to export the enemy base camp centroids with their full set of attributes into a new shapefile.

4.2.3 Pre-Processing HES Data

The hamlet evaluation data were collected for the time period from 1967-1974. The

South Vietnam government began to measure the security of its population in 1963 (NARA,

2011). However, their program was not very systematic in its approach to measure security in the countryside. A joint South Vietnamese-United States reporting system replaced this early program in 1964 and was designed to reflect only military security, administrative control, and pacification progress with the greatest emphasis placed on military security. In 1967, weaknesses in the joint reporting effort led the U.S. Secretary of Defense to request the Assistant

Secretary of Defense for Program Analysis and Evaluation (ASDPA&E) to prepare a better system of reporting. The resulting U.S. Hamlet Evaluation System (HES) then became the only official system in January 1967 (NARA 2011).

The Hamlet Evaluation System (HES) is a monthly data base that reported the security of

South Vietnamese villages and hamlets from North Vietnamese and Viet Cong encroachment and interference. The evaluation of the level of security came from political, economic and military data about each village or hamlet. Hamlets in some districts were identified as geographic areas defined by surveyed boundaries that were contiguous throughout a village. In other regions, hamlets could be identified only as an area of massed population without clearly

63 delineated boundaries (NARA 2011). Hamlets were used for internal village administration, and the number of hamlets within a given village was fluid and could fluctuate over a period of time based on the administrative needs of the village. A village administered on average five hamlets, but the number often varied greatly. As a legal entity with administrative autonomy, the village is the basic building block for rural administration in Vietnam.

Only data on the hamlets were processed for this analysis as they provided the fundamental social unit. Analyzing the insurgency at the hamlet level would provide as close a measure as possible of understanding the reach that the insurgency had at the finest scale of the population. As Trinquier argues, the controlling the population is the fundamental goal of modern warfare, not the larger territorial agglomerations (Trinquier 1964). Although HES data includes information on villages, this information was removed during the pro-processing process.

Unlike the previous two data sources which contained the entire temporal extent of the data in a single file, the hamlet data were in separate files for each year. There is also variation between individual files in terms of the comprehensiveness of the databases. The hamlet evaluation data represent 85 months of evaluated hamlets. These data are broken into two

‘iterations’ of the hamlet evaluation system. The first which covered the period 1967-1970 is notated as HAMLA. The second starting in 1970 and initially running concurrent with HAMLA but extending until 1974 is notated as the HES format. The different iterations were the result of an attempt to overcome supposed biases in the scoring by U.S. advisors in the HAMLA data.

ASDPA&E developed the Hamlet Evaluation System 1970 file (HES 70). In this newer iteration,

U.S. advisors were to supply only facts and not to make subjective judgments. Based on these facts, scoring was then constructed by the system.

Both sets of hamlet evaluations were first translated from EBCDIC to ASCII before geocoding could occur. The Kirix Strata program was used to perform this conversion and then used to export the data month by month as .txt files. After exporting, there were 85 text files for which each record in the HAMLA datasets was given as an unbroken block of characters of 195 characters in length and each record in the HES datasets was 372 characters in length. Next each file was imported into an EXCEL spreadsheet, and the records were subdivided in the proper fields using EXCEL’s ‘column breaks’ feature. The breaks were inserted based upon the NARA documentation for the data. The resulting tables were then saved as .xls files to allow for interoperability with ArcGIS 10.4 for further data processing.

The HAMLA data varied in the number of hamlets from month to month (see Table 4.3) but it maintained an overall spatial coverage of all South Vietnam from 1967-1970; in contrast, the HES data also varied in its spatial coverage. Starting in 1971, often only the First Military

Region, MR I, had any reported data. However, as the years progress, the number of hamlets surveyed slowly increases such that by January 1974, the last month recorded under the system, the greatest number of hamlets are shown having survey data (see Table 4.3).

Similar to the HERBO-2 datasets, the combined hamlet data were also geo-referenced using the

Military Grid Reference system. The hamlet data unlike the HERBO-2 data contained fewer geocoding steps as individual hamlets were merely represented as point data instead of line segments that had been recorded as a series of points. Because all geospatial data for an individual feature was encoded in a single line of data, this necessitated fewer steps in the geo- referencing process. The basic steps follow the same procedure used to pre-process the HERBO-

2 data. The individual geospatial codes that had been concatenated were separated into individual data fields in EXCEL, and followed a similar steps where each individual record was

Table 4.3 Monthly Count of Recorded Hamlets for Hamlet Evaluation System Month, Year Number of Recorded Hamlets Month, Year Number of Recorded Hamlets January, 1967 11,979 August, 1970 2,874 February, 1967 12,055 September, 1970 2,917 March, 1967 12,218 October, 1970 2,923 April, 1967 12,301 November, 1970 2,922 May, 1967 12,427 December, 1970 2,913 June, 1967 12,672 January, 1971 2,910 July, 1967 12,751 February, 1971 2,917 August, 1967 12,775 March, 1971 2,913 September, 1967 12,774 April, 1971 2,906 October, 1967 12,783 May, 1971 2,912 November, 1967 12,849 June, 1971 2,912 December, 1967 12,857 July, 1971 14,084 January, 1968 13,012 August, 1971 14,157 February, 1968 13,012 September, 1971 14,223 March, 1968 12,987 October, 1971 14,359 April, 1968 12,982 November, 1971 14,391 May, 1968 12,973 December, 1971 14,407 June, 1968 12,991 January, 1972 5,525 July, 1968 13,006 February, 1972 5,561 August, 1968 13,044 March, 1972 5,589 September, 1968 13,075 April, 1972 5,587 October, 1968 13,059 May, 1972 5,588 November, 1968 13,043 June, 1972 5,613 December, 1968 13,095 July, 1972 6,208 January, 1969 1,559 August, 1972 6,210 February, 1969 1,559 September, 1972 6208 March, 1969 1,561 October, 1972 6203 April, 1969 1,412 November, 1972 6295 May, 1969 1,348 December, 1972 6375 June, 1969 1,278 January, 1973 12,952 July, 1969 1,272 February, 1973 13,115 August, 1969 1,275 March, 1973 13,324 September, 1969 1,235 April, 1973 13,318 October, 1969 1,232 May, 1973 13,475 November, 1969 1,226 June, 1973 13,469 December, 1969 1,227 July, 1973 13,621 January, 1970 2,145 August, 1973 13,702 February, 1970 2,337 September, 1973 13,727 March, 1970 2,395 October, 1973 13,784 April, 1970 2,668 November, 1973 13,891 May, 1970 2,671 December, 1973 14,038 June, 1970 2,733 January, 1974 16,751 July, 1970 2,854

66 converted so that the coordinates were expressed in either a UTM 48 or UTM 49 zone coordinate.

The data were then imported into ArcGIS 10.4 so that the two UTM zones could be combined into a common set of geographic coordinates using the Indian 1960 datum. These procedures were the same for each month of data. Figure 4.4 displays the typical spatial coverage of a HAMLA month whereas Figure 4.5 displays the limited spatial coverage of many

HES months. Figure 4.6 presents the spatial coverage of hamlets for January, 1974 – the last month of the program and the most spatially extensive.

4.3 Pre-Processing Topographic Map Data

The jungle (or forested) land cover data for South Vietnam were created using the United

States Army topographic map series L507. This map series represents 85 maps that covered all of the Indochinese Peninsula Covering Vietnam, Cambodia, Laos, Thailand and portions of adjoining countries. Of these maps, 23 of them were used to provide coverage of South Vietnam itself. These maps were downloaded from two sources, the Perry Castañeda Map Library at the

University of Texas and the Vietnam Center and Archive at Texas Tech University. These maps provide a complete coverage for the entire area of South Vietnam compiled at the same time period 1954 when South Vietnam became a state in accordance with the Geneva Convention of

1954.

Figure 4.4 The location of hamlets in the January 1967 dataset. Hamlets located in the water regions exist on islands. A few hamlets located in Cambodia and Laos had improper military grid codes.

Figure 4.5 The location of hamlets in the January 1971 Dataset. Hamlets located in the water regions exist on islands.

Figure 4.6 The location of hamlets in the January 1974 dataset. Hamlets located in the water regions exist on islands. A few hamlets located in Cambodia and Laos had improper military grid codes.

4.3.1 Topographic Map Metadata

The L507 map series were compiled at a scale of 1:250,000. The maps were in a UTM projection using the Indian Datum 1954. Each map was annotated at its four corners with the latitude and longitude of the respective corners so that the degrees and minutes could be ascertained and used in the geo-referencing of each map. The spatial coverage of each map was a 1½ degrees of longitude by 1 degree of latitude rectangle except for a couple map sheets involving islands. In addition to a verbal place name identifier, each map also had a spatial reference identifier. For example, the map sheet identified as Hue had a spatial identifier of NE

48-16. The number 48 refers to the UTM grid to which the map belongs. The first two letters of the spatial identifier are a reference that gives the position of the sheet within set of four contiguous maps within a section of the UTM grid. The last two digits are an X reference. In addition, a map legend provided a description of the land use categories depicted in each map.

The date that the map was compiled was also given for each map as 1954.

4.3.2 Extraction of the Map Image from the Map Sheet

Each map was first imported into Adobe Photoshop and was processed in the following steps. All map sheet files came in a jpeg format. Second, each file was then cropped along the boundaries of the map removing the text descriptions from the map itself so that the only the map surface would later be processed in ArcGIS 10.4. The latitude and longitude coordinates in degrees and minutes that were given in the lower left of the map on the map sheet, were incorporated into the resulting file name of the cropped map. An example of this file naming system is CropNE48-16_10630_16.jpg which was the file name given to the Hue map sheet.

The geographic coordinates were attached to the spatial reference identifier for ease of

71 processing in the next step. The lower left coordinate of the map sheet was 106o30’’ longitude and 16o latitude. The new map files were also saved as jpeg files.

4.3.3 Geo-referencing the Map Images

Each file was then brought into an ArcGIS 10.4 map project file as a raster image for geocoding. The map sheets themselves were projected into UTM coordinates using the Indian

1954 system. The project file, however, was in the Geographic Coordinate System (GCS) Indian

1960; GCS coordinates were used so that map sheets from different UTM zones could be merged into a single system similar to what was done with the HES data. The geocoding process used the geo-referencing function in the ArcToolBox toolkit. Geo-referencing is a process in which selected control points in the source map image are assigned their corresponding coordinate in a map layer having an Earth-based coordinate system such as a UTM or a GCS so that the local coordinates of the map are correctly positioned on the surface of the Earth. All source map images were geo-referenced to the map layer of GCS Indian 1960. First, a source map file is selected for geo-referencing using the drop down menu in the geo-referencing toolbar. The spatial extent of the rasterized map was then recorded. This spatial extent corresponds to the four corners of map because of the way it was cropped in the extraction process. Although the map sheet itself is in a UTM coordinate system, the X and Y coordinates of the map image are given in a local system based on the number of columns and rows in the raster image. For the cropped rasterized map for Hue, there were 4380 columns and 3022 rows; thus, the X and Y coordinates of the four corners of the map image starting with the lower left corner and proceeding counter-clockwise to the upper left corner are (-0.5, -3021.5), (4379.5, -3021.5),

(4379.5, 0.5), and (-0.5, 0.5) respectively.

The next step was to enter the geographic coordinate in the map layer to be assigned to each reference point. Normally, during the geocoding process, the cursor is used to click on three or more locations to create the control points based on a visual inspection of the source map and the corresponding map coordinates are then located. This process can be an error prone method and was not used. Instead for each source map, a link table having four links was created and the four corners of the image are used as the control points. The coordinates of the four corners of the map image are typed in the columns for the X Source and Y Source in the link table. Table 4.4 shows this process for the Hue map image. Because the GCS coordinate for the lower left corner of the map had been encoded in the name of each raster file, this permitted an easy identification of the geographic coordinates for each control point. Although the coordinate in the name was given in degrees and minutes, this information was converted to decimal degrees before it could be typed into the link table. Thus, although the name of the map image was CropNE48-16_10630_16 the lower left corner was entered as 106.50 and 16.00 in the

X Map and Y Map columns respectively in the first link row. The full link table for this map is given in Table 4.4.

TABLE 4.4 The Link Coordinates for Geo-Referencing the Hue Map Sheet Link X Source Y Source X Map Y Map 1 - 0.5 - 6512.5 106.50 16.00 2 4379.5 - 6512.5 108.00 16.00 3 4379.5 0.5 108.00 17.00 4 - 0.5 0.5 106.50 17.00

Once all four points had been fully entered into the geo-referencing menu, each reference link was activated and the raster image was automatically geo-referenced. This image was then saved as a jpeg and a 1 was adjoined to the name of the new file to distinguish it from its non- geo-referenced counterpart. Figure 4.7 displays the geo-referenced image of the Hue map sheet.

This process was completed for each map until the full map series over the entire extent of South

Vietnam was geo-referenced.

Figure 4.7. The geo-registered Hue Map Sheet against the outline of South Vietnam.

4.3.4 Constructing the Land Cover Map

The next step was to extract the forested land cover from the other land covers in the map. Two possible methods exist for this extraction. As a digital image, it could be classified as any other digital image can using remote sensing classification software based on the numeric values associated with each raster unit. The data classification tool in ArcGIS 10.4 was tested on

74 the Hue image. An initial classification was easily obtained but the classification was confused by all of the lettering and contour lines on the image. A substantial amount of post-processing was required to correct the misclassifications. The alternative approach was to on-screen digitize the boundary of the forested land cover. This required a substantial of amount of time to prepare one digitized image. However, it did not need much as much post-processing as the remote sensing classification approach. Overall, far less time was needed in the on-screen digitizing approach with more accurate results so this method was used to digitize the remaining maps.

After, each map was digitized, it was merged with the previously digitized maps using the MERGE command from ArcToolbox. Next, the merged maps were dissolved into one seamless map using the DISSOLVE command in ArcToolbox. After all 23 forested land cover maps were merged and dissolved, a complete forested map of South Vietnam was obtained (see

Figure 4.8). The jungle land cover in this map includes both the forests of the interior highlands as well as the mangrove areas in the southern lowland area as both provide the dense canopy often used for insurgent sanctuaries. .

4.4 Summary

These data represent inherent data processing issues that are common when dealing with

HGIS studies. Often times much pre-processing must be done, whether converting textual data into digital representations through rubber sheeting of scanned images or manual entry of data, or in processing the pre-ASCII data structures found in several of the archived datasets from

NARA. The key aspect in processing these datasets was to identify the projection system that each dataset used, and then through each data transformation step ensure that the data would be

Figure 4.8. The forested and mangrove regions (the”Jungle”) of South Vietnam.

76 able to be displayed accurately within that projection system. The processing of these data will allow for the combination of these datasets while preserving their correct spatial position in relation to each other. Such processing is required to develop point patterns that can be analyzed for the first set of spatial analyses in this study.

CHAPTER 5 – CODING ANALYSIS OF U.S. MILITARY COUNTERINSURGENCY FIELD MANUALS

5.1 Providing a Baseline for Understanding U.S. Military Action

Standardization is an important concept in the military. With the evolution of mass militaries beginning in the 19th century, the need to standardize all aspects of how a military functioned, including soldier’s uniforms, became of utmost importance for managing the mass conscript armies deployed to fight the myriad wars from the 1860s on such as the American Civil

War (MacPherson 1988). Manuals provide the individual soldier in the modern U.S. military with information on how to execute a given task or operation properly (Bowden 2017, 239). The spectrum of tasks can range from ceremonial functions to equipment maintenance to counterinsurgency operations. While individuals may under given circumstances depart from standardized practices as outlined in military field manuals, these documents provide an important baseline for how individuals would handle the execution of their mission.

Qualitative research using textual data has contributed to geographical analyses of conflict. Bolton (2015), for example, performed such an analysis to understand the role of landmines in autonomous killing. In this dissertation, a content analysis of U.S. military field manuals provides insight into how U.S. military standards discussed the various geographic settings where counterinsurgency actions would take place during the Vietnam War and whether the field manuals incorporated counterinsurgency doctrines such as those developed by Trinquier

(1964).

The qualitative analysis of the content of the U.S. military field manuals has three primary aims. The first goal was to assess the occurrence frequency of codes describing actors, activities, and settings. Second, it was important to document changes in the meaning of codes over time between the two field manuals. Finally, the analysis sought to identify the contexts in which codes were used by measuring associations of terms describing actors, activities, and settings. This third analysis involves studying the co-occurrence of terms within the paragraph as the contextual unit of analysis and the change in co-occurrence of codes over time. The fundamental question that this chapter tries to answer is whether insurgent forces are conceptually linked with a particular type of land cover in U.S. military counterinsurgency field manuals

5.2 Content Analysis of Textual Data

Processing the textual data involved several steps. First, the textual sources were identified. Next, a code book was developed, tested and refined. Then, the sources were coded.

Finally, the codes were analyzed to meet the three aims of the qualitative study.

5.2.1 Textual Sources

Two field manuals—one from the era prior to and one during the study period—provided the base texts for the qualitative analysis in this dissertation. The Marine Corps Small Wars

Manual published in 1940 and reprinted by the Navy (Department of the Navy 1990) was developed from the Marine Corps experience fighting in Middle and South America during the first decades of the 20th century. The Department of the Army’s Field Manual on

Counterguerrilla Operations published in 1967 (Department of the Army 1967) was developed to provide a framework for the conduct of such operations at the brigade level. While it is

79 understood that individual commanders would not always follow these manuals to the letter and would take into account other information, the documents reflect the current military doctrines and institutional frameworks within which operational decisions were made. During the battle of

Hue in 1968, for example, Marine Corps commanders consulted urban warfare field manuals to develop a plan of counterattack in response to the Tet Offensive (Bowden 2017, 239).

5.2.2 Creating a Code Book

Content Analysis is an important method for extracting underlying relationships and concepts from textual data (Bernard and Ryan 2010). For this study, the French counterinsurgency strategy described in Modern Warfare (Trinquier 1964) was used to develop a set of codes representing specific types of actors, activities, and settings that were important in counterinsurgency doctrine. Trinquier’s book was used as a source text for the creation of the code book for two reasons. First, he had extensive experience fighting in counterguerilla operations in Southeast Asia during the French Indochina War (1946-1954) and then in Algeria

(1955-1962) during the conflict there (Trinquier 1964). Second, he later served as an advisor to various U.S. counterinsurgency initiatives in South Vietnam, particularly the Phoenix Program

(Davidson 1991).

Actor, activity, and setting codes were developed to represent the variety of situations discussed by Trinquier in counterinsurgency operations. Codes are often interpreted in a text in two ways. First, the individual word itself may be found within a text, called an in vivo code.

Codes such as “Patrol,” “Base” or “Ambush” are examples of codes that might be present in this form as the words “patrol,” “base,” or “ambush” within a paragraph. The second way of coding applies a code to a set of words that in a paragraph even though the words of the code do not directly appear. For example, the code “Population Center” was used to code the words “capital

80 city.” The code list or code book was then compiled and organized with a definition of each code and examples to aid in the identification of individual codes within each text (Appendix

A).

Once the code book was developed, a test was made using the first chapter of the Marine

Corps Small Wars Manual (Department of the Navy 1990). This test led to the addition of some new codes and the aggregation of others into more generalized codes. For example, codes such as “River” and “Rear Area” were added. The initial code book contained a variety of codes representing various types of settlement. After the test, it became clear that the code “Population

Center” would better represent the idea of fixed settlements as settings where actors engaged in military operations and this general code was adopted.

The revised final code book was then used to re-code the same chapter and the two attempts were compared to assess how well the revisions captured concepts within the text.

After this, the revised code book was sufficiently representative of the counterinsurgency concepts of interest and was used to code both field manuals in their entirety.

5.2.3 Coding the Textual Sources

When coding a document, the textual unit of analysis must be defined. For this study, the paragraph was chosen as the unit of text. If a code appeared at least once within a paragraph, a record of the appearance of the code in the paragraph in a particular field manual was made. A comment was added, if appropriate, providing additional information on the meaning of the code. For example, a “Transportation Hub” might be a port or an air base. The comment field was used to note this information.

Varieties of software programs are available for coding and analyzing qualitative data

(Bernard and Ryan 2010). For this study, a Microsoft Access database was created to record and

81 analyze codes in the field manuals. Microsoft Access is a general-purpose relational database software program that is widely available and has been used for qualitative analysis of text

(Meyer, Gruppe and Franz, 2002).

Three tables were created in the Access database. The first table consisted of two records describing the field manuals used as textual sources and included the author, title, date, and place of publication, and a publication identifier. The other two tables, one for each field manual, shared the same structure so the tables could be merged easily. Each of these tables had eight fields (Table 5.1).

Table 5.1 Table Design for Database of Field Manual Codes

Field Name Field Type Field Size Example

RECID AutoNumber 29

REFNO Text 25 NAVMC2890

OBSID Long Integer 10601

SECTION Long Integer 1

PAGE Long Integer 6

PARAGRAPH Long Integer 1

CODE Text 45 Population Center

COMMENTS Text 80 Cities are important features

The RECID was the unique identifier for each code entry. The REFNO represented the manual number for the field manual where the code appeared. The SECTION field referenced the chapter or section of the field manual. The PAGE number referenced the page where the code was found. The PARAGRAPH was the finest level of documentation representing the fundamental textual unit for a given code. Although section and page numbers were printed in the document, the coder assigned paragraph numbers from one to the maximum number of

82 paragraphs on the page. If a paragraph stretched over to the next page, all of the codes found in the paragraph were coded to the section, page, and paragraph for the page where the paragraph began.

A look-up table listing all of the codes in alphabetical order was created to facilitate accurate and rapid data entry. This table was linked to the CODE field to create a pull-down menu from which the desired code could be selected. Any comments were entered in the

COMMENT field. As noted, comments were meant to provide a further characterization of the recorded code. For example, the code “Population Center” might have a comment such as

“City” or “Capital city” or “Village.” If more than, one code was found in a single paragraph, that paragraph would have as many records in the database table as different codes found. This table structure made it easy to enter data and to develop queries to assess the frequency of codes and their co-occurrence in the same paragraph. If a paragraph contained no text that could be coded with an appropriate term from the code book, that code “None” was entered in the Access database as the sole record for the paragraph. Every paragraph in the Access database for a manual was coded.

Once both field manuals had been completely coded in the database, tables underwent post-processing so the data could be analyzed using different techniques. First, an additional field, the observation identifier or OBSID, was created for each record. OBSID is a unique paragraph identifier created by concatenating the SECTION, PAGE, and PARAGRAPH fields similar to the way the U.S. Census creates unique identifiers for various census areal units such as tracts, blocks and block groups. For example, OBSID 10601 for the Marine Corps field manual identifies the code as appearing in Section 1, Page 6, and Paragraph 1. This variable was created after the coding of the documents so that the coder would not have to determine in

83 advance the number of sections, pages, and paragraphs in each document. The OBSID field made it easy to create a summary table listing the paragraphs as rows and the codes as columns by creating a query in Access. The cells of this table contain 0’s and 1’s indicating whether a particular code appears in a particular paragraph.

5.3 Code Count and Code Density Analysis and Results

5.3.1 Code Count Queries

Simple information can provide meaningful insight to understand textual data. In the case of the field manuals, the first step to understand the concepts within the texts was to tabulate the code counts. To tabulate the coded data, the query function in Access was used to list each code in the table of records and provide a count of the number of times the code appeared in the entire document. Separate queries were created to produce the code counts for the table for the

1940 manual and the table for the 1967 manual.

5.3.2 Code Count and Code Density Results

Almost all of the codes in the code book appeared at least once in both field manuals, but there were two exceptions (Table 5.2). The code “Peasant” appeared in the 1940 manual but not in the 1967 manual; “Rear Area” appeared fifty-two times in the 1967 manual but was not found in the 1940 manual.

Similarities and differences in the density of codes per paragraph in the 1940 manual and the 1967 manual were assessed. One of the first similarities apparent in Table 5.2 is the overall paucity of codes relative to the size of the field manuals. In both years, only half of the paragraphs had a code which is why “None” was the most prevalent code. In the 1940 manual, other than the “Patrol” code, all codes appeared fewer than 100 times. More than half of the codes had fewer than 20 instances within the text. Results were similar for the 1967 field

84 manual. The “Guerilla Unit” was the only code to appear more than 100 times. The sparsity of codes in text is a challenge in analysis of textual data (Lowe 2003, 5).

Differences can also be seen in the density of actor, activity, and setting codes in general.

Twenty-three of the 42 individual code densities were greater in the 1967 manual than in the

1940 manual (all three major categories were denser in the 1967 manual). Excluding “None”, setting codes as a category accounted for the greatest numbers of codes in 1940 and in 1967. In the 1940 manual, activity codes were more frequent than actor codes. In the 1967 manual, however, actor codes were more frequent than activity codes mainly due to the emphasis on

“Guerilla Unit”. Based on raw code counts, the text of the 1940 manual focuses more on activities and settings related to counterinsurgency operations while the 1967 manual focuses more on actors who play a role in executing counterinsurgency operations in various settings.

5.4 Codes Comment Analysis and Results

5.4.1 Code Comment Queries

To assess possible changes in the usage of codes from 1940 to 1970, two additional

Access queries were created. One query was created for each field manual database table. Each query selected a code and returned all of the comments associated with particular code entries, which had been entered in the COMMENT field of the table when the text was coded. Only comments for the selected code appeared in the query result. By changing the selected code, comments could be extracted from the large database table one code at a time.

Table 5.2 Code Counts and Code Densities in U.S. Military Field Manuals,1940 and 1967 Code Count Code Density Code Count Code Density Code 1940 1940 1967 1967 Actors 287 0.2186 317 0.4385 Foreign Government Force 70 0.0533 33 0.0456 Police 57 0.0434 29 0.0401 Government Officials 40 0.0305 5 0.0069 Guerilla Units 37 0.0282 150 0.2075 Regular Military 37 0.0282 36 0.0498 Main Force Unit 13 0.0099 4 0.0055 Government Sympathizers 10 0.0076 7 0.0097 Insurgent Sympathizer 9 0.0069 18 0.0249 Auxiliary Force 4 0.0030 28 0.0387 Political Cadre 4 0.0030 2 0.0028 Foreign Enemy Forces 2 0.0015 2 0.0028 Peasants 2 0.0015 0 0.0000 Regional Unit 1 0.0008 3 0.0041

Activities 378 0.2879 215 0.2974 Patrol 168 0.1280 29 0.0401 Civilian Activity 78 0.0594 22 0.0304 Outpost 33 0.0251 15 0.0207 Ambush 27 0.0206 21 0.0290 Gridding 17 0.0129 5 0.0069 Police Operation 16 0.0122 20 0.0277 Propaganda 9 0.0069 11 0.0152 Intervention Action 6 0.0046 15 0.0207 Interval Action 5 0.0038 19 0.0263 Grid Action 3 0.0023 2 0.0028 Counterinsurgency Sweep 2 0.0015 3 0.0041

Settings 464 0.3534 314 0.4343 Country 90 0.0685 77 0.1065 River 74 0.0564 12 0.0166 Line of Communication 63 0.0480 36 0.0498 Theater of Operation 54 0.0411 8 0.0111 Wilderness Area 43 0.0327 7 0.0097 Population Center 31 0.0236 20 0.0277 Territory 29 0.0221 4 0.0055 Base 27 0.0206 21 0.0290 Transportation Hub 20 0.0152 10 0.0138 Road 18 0.0137 10 0.0138 State 17 0.0129 5 0.0069 Rural Area 8 0.0061 3 0.0041 Nation 7 0.0053 11 0.0152 Hinterland 5 0.0038 10 0.0138 Urban Area 3 0.0023 5 0.0069 Zone 2 0.0015 44 0.0609 Rear Area 0 0.0000 52 0.0719

None 660 0.5027 358 0.4952 Total Number of Codes 1,129 0.8599 846 1.1701 Total Number of Paragraphs 1,313 723 Note: The greater code density for the two years is highlighted in bold.

5.4.2 Code Comment Results

The comparison of the comment fields for the codes from each of the three categories reveals that in all three categories, the usage of some codes changed between the two field manuals. Words and their meanings change over time. As such, we cannot understand terms as being trans-historical or maintaining a fixed meaning over time. An important aspect of understanding these field manuals is to understand the changes in usage between the two periods of these field manuals. Additionally, these codes often represent a group of related terms. As discussed earlier in this chapter, the code “Population Center” was used to cover a variety of different terms. Changes in the code usage can also mean changes in the presence of specific terms that are grouped under these larger codes.

For example, “Transportation Hub” is found 20 times in the 1940 manual while in the

1967 manual it is only found 10 times. The code comments reveal that the transportation hubs referred to in the 1940 manual are mostly ports, which makes sense given the association of the

U.S. Marine Corps with the Navy. In fact, 13 of the 20 instances of this code relate to the role that ports would play in the presence of a military force in a foreign country. Six times

“Transportation Hub” indicates an airfield. Yet, in the 1967 field manual, all ten instances of

“Transportation Hub” relate to airfields, reflecting the importance of air operations to counterinsurgency efforts at this time. This change in usage means that there could be instances when the terminology between the two field manuals might appear interchangeable but would have different meanings.

To address this aspect of the texts, three tables have been assembled to summarize and compare the code comments for activity, actor, and setting codes between the two years to develop an understanding of whether or not usage evolves or remains fixed amongst the various

87 codes. The tables reveal that some codes were found in only one manual. Other codes changed somewhat in usage from one manual to the other. For the remaining codes, the usage was consistent between manuals.

Table 5.3 compares usage for all actor codes between the two field manuals. Of the 13 codes, “Peasant” was only present in the 1940 manual. Six codes—“Auxiliary Force,” “Foreign

Government Forces,” “Government Officials,” “Government Sympathizers,” “Insurgent

Sympathizers,” and “Regular Military”—had somewhat different usages between the 1940 and

1967 field manuals. Five of the six actors for which usage changed are codes for

Table 5.3 Actor Code Usage in U.S. Military Field Manuals in 1940 and 1967

Actor Code Code Usage 1940 Code Usage 1967

Auxiliary Force Armed civilians to assist police Paramilitary force used for defensive purposes

Foreign Enemy Forces Provide guerilla support Provide guerilla support

Foreign Government Forces Interaction of forces with local Internal structure of forces population deployed in counterinsurgency

Government Officials Must be viewed as independent No general theme and legitimate

Government Sympathizers Important intelligence source Aid government forces

Guerilla Unit Do not follow conventions of Do not follow conventions of regular military forces regular military forces

Insurgent Sympathizers Provide intelligence for insurgents Important target of often in rural areas counterinsurgency operations

Main Force Unit Comparable to regular military Comparable to regular military

Police Important as first line force must Important as first line force must be supported by military be supported by military

Political Cadre Direct insurgency Direct insurgency

Regional Unit Weaker than main force units Weaker than main force units

Regular Military Standing military that must Must be well led and be able to shoulder burden of conflict engage guerilla forces

Peasants Ambiguous segment of population Not present in 1967 manual

88 counterinsurgent forces while those that remained consistent referred primarily to insurgent forces. This suggests that, between the two field manuals, the conceptualization of counterinsurgent forces in military doctrine changed. How the insurgent forces were conceptualized remained static.

Table 5.4 compares the usage of activity codes in the 1940 and 1967 manuals. In this code category, two codes—“Counterinsurgency Sweep” and “Grid Action”—were better described in the 1967 manual than in the 1940 volume. The codes “Gridding,” “Outpost,”

“Patrol,” and “Police Operation,” all have different usages in1940 and 1967.

Table 5.4 Activity Code Usage in U.S. Military Field Manuals in 1940 and 1967

Activity Codes Code Usage 1940 Code Usage 1967

Ambush Important in counterinsurgency Important in counterinsurgency

Civilian Activity Just as important as military activity Just as important as military activity

Counterinsurgency Sweep None Clear away insurgents

Grid Action None Understand local surrounding

Gridding Subdividing territory Subdividing territory and creating close cooperation of institutions in each grid

Interval Action Support local forces as mobile Support local forces as mobile reserves reserves

Intervention Action Used to destroy guerilla units and Used to destroy guerilla units and act independently act independently

Outpost Vulnerable locations to observe Vulnerable locations of static surrounding area defense

Patrol Mobile contingents of troops to Mobile contingents used to secure observe terrain that must be settings and locate guerilla properly organized and well led

Police Operation Highly variable must be done by Used for riot control and various local personnel types of information gathering

Propaganda Varying means to control Varying means to control population population

The remaining codes stay consistent in usage between manuals. Two of the three codes under activities are those that Trinquier (1964) labelled as ineffective counterinsurgency tactics—“Outpost” and “Patrol”. Both codes for ineffective activities decreased in frequency

Table 5.5 Setting Code Usage in U.S. Military Field Manuals in 1940 and 1967

Setting Codes Code Usage 1940 Code Usage 1967

Base Fixed locations of great material General term for fixed locations that strength support different activities and are in varying settings

Country Location of conflict that must be Country hosting friendly military whose complexity must be forces understood by friendly forces

Hinterland Remote part of country Remote part of country requiring more support for little gain

Line of Communication Protection important in hinterland and Protection important in hinterland wilderness area and wilderness area

Nation Nations gain specific legal protections Issues pertaining to newly in international community independent states of various governmental systems

Population Center Generally viewed as being bases of Generally viewed as being bases of support for government support for government

Rear Area None Supposedly secure areas

River Play multiple roles in operations Play multiple roles in operations

Road Better maintenance aids Better maintenance aids counterinsurgents counterinsurgents

Rural Area Backwards not well connected Difficult to defend

State International sovereignty Sub-unit of country

Territory Setting of activities Binding of population and land

Theater of Operation Must have good battlefield Area of operations intelligence, command and control

Transportation Hub Primarily seaports some airbases Airfields

Urban Area Large populations good to station Large populations more easily forces controlled

Wilderness Area Heavily vegetated safe areas for Mountainous terrain good defensive guerilla area can be thickly vegetated

Zone Neutral Zone Arbitrary designation for area of military operations

90 between 1940 and 1967, suggesting a shift in how these two types of activities where characterized within the counterinsurgency doctrine

Table 5.5 compares the usages for codes categorized as settings. Of these codes, “Rear

Area” was found only in the 1967 manual. Ten codes—“Base,” “Country,” “Hinterland,”

“Nation,” “Rural Area,” “State,” “Territory,” “Theater of Operation,” “Transportation Hub,” and

“Wilderness Area”—changed usages between the two manuals. The remaining codes have generally consistent usages.

Of the codes that changed during this period, it should be noted that there are two noteworthy subgroups. The first group of settings is “Country,” “State,” “Nation,” and

“Territory”. These codes represent terms that are often linked with an understanding of sovereign power in the state (Dean 2010; Elden 2007). The change between these field manuals also represents a change in the usage of these terms. For example, in the 1967 manual, the code

“State” is often used not in the context of representing a nation-state, instead the term is used specifically for denoting sub-units or provinces of a single nation-state. Additionally, the term

“State” decreases between the two manuals occurring 17 times in the 1940 manual and 5 times in the 1967 manual. Additionally, the code “Territory” occurring 29 times in the 1940 manual occurs only four times in the 1967 manual. The code “Country” also represents an interesting change in how the code is used. In the 1940 manual, great emphasis is placed on understanding the complexity of the country in which foreign counterinsurgent forces are operating. In the

1967 manual, country is used to represent the setting of the insurgency, but is not understood as a larger multi-dimensional entity as in the earlier manual.

The second set of codes—“Hinterland,” “Rural Area,” and “Wilderness Area”—are codes that represent the area that is often characterized as the base area of guerilla formations

(Trinquier 1964). This change suggests a difference in how the base areas are understood in counterinsurgency operation field manuals. This is consistent with Trinquier’s (1964) argument that insurgencies after 1945 were of a different nature than those that had come before.

5.5 Statistical Analysis of Code Pairs in Paragraphs and Results

The final part of the textual analysis focused on the contexts in which codes appeared in the field manuals. This analysis was designed to uncover significant associations among activities and settings or actors and settings. Were particular activities or actors more likely to be discussed in the same paragraph as particular settings than expected given the overall frequencies of occurrence of the actor or activity and setting codes in the field manual as a whole? The following sections describe how code pairs were identified and the use of the odds ratio and relative risk measures to assess their significance.

5.5.1 Definition and Numbers of Code Pairs

This research defines a code pair as the co-occurrence of an actor or an activity code with a setting code in the same paragraph. In order to explore the co-occurrence of codes within paragraphs, Access queries were designed to create six new tables, three from each manual’s database table of codes: and actor table, an activity table, and a setting table. These tables had the same design with three fields: the RECID, the OBSID, and the CODE. Four additional Access queries were created to link actors to settings and activities to settings the frequencies for both years based on the OBSID or paragraph identifier. The link was designed as a one-to-one link so that every time an actor code was paired with a setting code within a paragraph, the code pair would be returned in the query result. If a paragraph contained a single activity code and three setting codes, the query result would return three records, one for each pairing of the activity

92 code with one of the three setting codes. Similarly, if the paragraph contained two activity codes and one setting code, the query result would return two records, one for each pairing of the activity codes with the one setting code with which actor codes appeared in the same paragraph as setting codes.

Table 5.6 shows the number of code pairs for activities and actors with settings for both m manuals. For the 1940 manual, there were more activity-setting pairs than actor-setting pairs.

For the 1967 manual, there were more actor-setting pairs than activity-setting pairs. The number of actor-setting pairs coded in the 1967 manual, 308, is far larger than any of the other pairs.

This provides additional evidence that the 1967 field manual emphasized actors and settings in describing counterinsurgency operations.

Table 5.6 Raw Activity-Setting and Actor-Setting Code Pairs in 1940 and 1967 Field Manuals

Pairs 1940 1967

Activity Code Paired with Setting Code 187 189

Actor Code Paired with Setting Code 173 309

5.5.2 Code Pairs for Statistical Analysis

For the statistical analysis of code pairs, codes were grouped into general categories based on counterinsurgency theory. Counterinsurgency actors and insurgent actors are grouped into categories (Trinquier 1964). Actors at the most general level may be enemy forces or government forces including the foreign government forces such as U.S. troops during the Viet

Nam war who support the government. Trinquier’s theory also identifies activities, which he considers “ineffective”, and others, which he believes, are “effective” as counterinsurgency measures. Finally, the theory discusses a range of geographical settings in relation to insurgency: urban areas, non-urban areas, and lines of communication, theaters of operation, and the nation-

93 state. Table 5.7 presents how the individual actor, activity, and setting codes used in this study map to Trinquier’s more general categories.

Table 5.7 Codes Mapped to Trinquier’s General Categories of Actors, Activities, and Settings

General Category 1940 Codes 1967 Codes

Actors Enemy Guerilla Unit Guerilla Unit Main Force Unit Main Force Unit

Government Forces Foreign Government Forces Foreign Government Forces Regular Military Regular Military

Activities Effective Grid Action Grid Action Gridding Gridding Interval Action Interval Action Intervention Action Intervention Action

Ineffective Ambush Ambush Outpost Outpost Patrol Patrol

Settings Urban Population center Population center Urban area Urban area

Non-urban Hinterland Hinterland Rural Area Rural Area Wilderness Area Wilderness Area

Line of communication Line of Communication Line of Communication River River Road Road Transportation Hub Transportation Hub

Theater of operation Rear Area Rear Area Theater of Operation Theater of Operation Zone Zone

Nation-state Country Country Nation Nation State State

5.5.3 Statistical Analysis of Associations of Code Pairs in Paragraphs

The odds ratio and relative risk are two statistical measures used to quantify how strongly the presence or absence of one condition is associated with the presence or absence of another condition in a given population (Fleiss 1981). In this research, the population is the set of all generalized actor-setting or activity-setting code pairs within a paragraph for all paragraphs in the training manual for a particular year. Odds ratios have been used in qualitative analysis of text, primarily to compare how well coding by different analysts match (Bernard and Ryan

2010). Lowe (2003) suggests that the odds ratio may be a useful measure of association in textual analysis because it takes into account differences in the marginal probabilities.

To simplify the illustration of the application of odds ratios and relative risk measures to analysis of the co-occurrence of code pairs, the odds ratio and relative risk will be computed for the single activity code “Patrol” and the single setting code “River” among activity-setting code pairs in the 1940 manual rather than the generalized groupings of codes after Trinquier. The first step in calculating both the odds ratio and the relative risk is creating a cross-tabulation of the activity code with the setting code for the activity-setting code pairs (Table 5.8). The two rows represent the activity with the top row including all the activity-setting code pairs where “Patrol” is the activity and the bottom row including all the activity-setting code pairs where the activity is some other activity not including “Patrol.” The two columns represent the setting with the left column including all the activity-setting code pairs where “River” is the setting and the right column including all the activity-setting code pairs where the setting is some other setting not including “River.” Row and column subtotals are included in the table along with the grand total equaling 187 activity-setting code pairs for 1940.

Table 5.8 Example odds ratio and risk analysis for the Patrol-River code pair Activity by Setting Crosstabulation

Setting Activity River Not River Total

Patrol a=18 b=65 83 % within action 21.7% 78.3% 100.0%

Not Patrol c=7 d=97 104 % within action 6.7% 93.3% 100.0%

Total 25 162 187 % within action 13.4% 86.6% 100.0%

Risk Estimate

Statistical Measure Value 95% Confidence Interval Lower Upper

Odds Ratio for Activity Patrol and Setting River 3.837 1.517 9.705 Relative Risk for Patrol and River 3.222 1.413 7.345 Relative Risk for Patrol and Not River 0.840 0.741 0.951

Within each cell, the count of activity-setting code pairs is given. For example, 18 of the

187 activity-setting code pair records paired “Patrol” as the activity and “River” as the setting.

The row percentages are also given. This link between “lines of communication” and insurgent forces is found in the spatial distribution of defoliation missions. While some base areas were heavily defoliated, many defoliation missions were aimed at transportation infrastructure in

South Vietnam or generally in areas between hamlets and known base areas. This was done to decrease the ability of the insurgent forces to conceal their movments.

The odds for “Patrol” is calculated as the number of times the “Patrol” code occurs with a

“River” setting code relative to the total number of times it does not occur with a “River” setting code (a/b=18/65=0.277). The odds for “Not Patrol” is calculated as the number of times the

“Not Patrol” code occurs relative to the total number of times it does not occur with a “River”

96 setting code (c/d=7/97=0.072). The numerator of the odds ratio is the “Patrol” odds for a “River” setting. The denominator of the odds ratio is the “Not Patrol” odds for a “River” setting. The odds ratio is (a/b)/(c/d)=0.277/0.072=3.837. If the odds ratio is greater than 1, “Patrol” as an activity is associated with “River” as a setting in the sense that having the river setting raises the odds of a “Patrol” activity relative to other, non-river settings.

A specific discussion of patrolling and its purpose is perhaps justified to understand these results. Trinquier’s framing of ‘patrolling’ as an ineffective military activity in modern warfare

(1964) is based on the nature of the insurgency. While patrolling is an important activity that is an important tactic against a direct military force to find, fix and destroy it: against a political organization imbedded within the population, patrolling cannot directly address the insurgency’s control over a population and address breaking that control. As Jackson (2005) argues however, infantry is the fundamental component of a counterinsurgent force and the patrol is the most basic action for infantry forces. However, as political organizations are not easily found through patrols, constant patrolling can weaken the morale and combat effectiveness of the counterinsurgent forces (Fall 1966). Additionally, patrols are transitory in nature. Instead of occupying a specific position or place, patrols only pass through areas that can then be easily reoccupied by enemy forces. In spite of this, patrols were still valid as they provided a continuous obstacle that forced enemy forces to have to react to their presence.

Confidence intervals were calculated to test the significance of the odds ratio. If the value

1.0 lies within the upper and lower limits of the confidence interval, the code pair is just as likely to occur as not occur and the research cannot conclude that there is a significant association between the activity and the setting. If the odds ratio is greater than 1.0 and the upper and lower limits of the confidence interval are also greater than 1.0, then the activity is more likely to be

97 associated with the setting. If the odds ratio and confidence interval values are both less than 1.0, then the activity is less likely to be associated with the setting of interest than with other settings.

Relative risk is a related measure. However, instead of comparing the occurrences versus the non-occurrences of the pairings, as in the odds ratio, the denominator in the relative risk formula takes into account both occurrences and non-occurrences. To assess the relative risk for the “Patrol” code occurring in the same paragraph as the “River” code, the ratio of the probability of “Patrol” occurring with “River” and the probability of “Not Patrol” occurring with

“River” is calculated and the ratio of the two is computed ((a/(a+b))/(c/(c+d)) = (18/83)/(7/104)

= 0.217/0.067 = 3.222 (Table 5.8). It is also possible to calculate the relative risk for “Patrol” and the “Not River” setting. Many statistical software packages provide both results.

Odds ratios and relative risks were computed for the generalized actor codes with generalized setting codes and for the generalized activity codes with the generalized settings codes shown in Table 5.7. The Analyze→Descriptive Statistics→Crosstabs function in SPSS software Version 24 was used requesting row percentages and risk measures in the output.

Tables 5.9, 5.10, 5.11, 5.12, and 5.13 present the results of the analysis for the various generalized activity and actor codes against each of the five generalized settings based on the analysis performed using SPSS. The odds ratio and both relative risk measures are presented with 95 % confident intervals and statistically significant associations are highlighted.

Table 5.9 matches generalized activity and actor codes with “Urban” setting code. In Table 5.9 the only set of odds ratios that are significant are for activities considered effective by Trinquier and found in the 1940 field manual. In the 1940 manual, these activities, i.e. “Gridding,” “Grid

Actions,” “Interval Actions,” and “Intervention Actions,” are more likely to be associated with codes that represent urban or populated areas than other settings. Additionally, Government

Forces in 1967 is significantly less like to appear in the same paragraphs as the urban area code group.

Table 5.9 Statistical associations among activities, actors, and urban setting codes in 1940 and 1967 Urban Area Setting (Urban Area, Population Center) 95 % Confidence Interval Activities Measure Value Lower Upper

Effective Activities 1940 Odds Ratio 4.437 1.673 11.766 Relative Risk Effective Activities = Yes 3.553 1.596 7.913 Relative Risk Effective Activities = No 0.801 0.656 0.978

Effective Activities 1967 Odds Ratio 0.894 0.283 2.827 Relative Risk Effective Activities = Yes 0.905 0.323 2.537 Relative Risk Effective Activities = No 1.012 0.897 1.142

Ineffective Activities 1940 Odds Ratio 0.548 0.215 1.395 Relative Risk Ineffective Activities = 0.585 0.255 1.345 Yes Relative Risk Ineffective Activities = 1.068 0.961 1.188 No

Ineffective Activities 1967 Odds Ratio 1.074 0.433 2.664 Relative Risk Ineffective Activities = 1.066 0.475 2.389 Yes Relative Risk Ineffective Activities = 0.992 0.897 1.097 No

Actors

Enemy 1940 Odds Ratio 1.064 0.326 3.469 Relative Risk Enemy = Yes 1.057 0.365 3.059 Relative Risk Enemy = No 0.994 0.882 1.120

Enemy 1967 Odds Ratio 1.798 0.713 4.530 Relative Risk Enemy = Yes 1.731 0.728 4.115 Relative Risk Enemy = No 0.963 0.906 1.023

Government 1940 Odds Ratio 0.653 0.230 1.854 Relative Risk Government = Yes 0.680 0.263 1.756 Relative Risk Government = No 1.041 0.945 1.147

Government 1967 Odds Ratio 0.333 0.075 1.472 Relative Risk Government = Yes 0.351 0.083 1.479 Relative Risk Government = No 1.054 1.000 1.111

Note: Significant measures are highlighted in bold.

While there is not good agreement between field manuals, in terms of defining significant relationships between code groups, what significant results that do occur do not contradict

Trinquier’s (1964) discussion of counterinsurgency operations. Urban Areas are thought to be the most secure areas in counterinsurgency operations as they are districts that are most easily

99 controlled by the government through a variety of means. Particularly for the 1967 field manual, where U.S. forces are actively participating in counterinsurgency operations, it would make sense that these forces are not significantly co-occurring in paragraphs that also contain an Urban

Area code because if Trinquier is to be followed, these would not be areas where insurgents are strongly present, and the police should be able to deal with insurgents in these settings.

For the effective activities code group being found to co-occur significantly with Urban

Area codes across all measures in the 1940 field manual, again makes sense as Urban locations are most well set up to support these types of activities. If Urban Areas as a collective setting do not contain many significant results, one would think that maybe Non-Urban settings might also not contain as many significant results as might have been previously postulated. This is counterintuitive to what analysis the two groups suggested as much of the usage of these two groups of setting codes was relating these areas to being where Guerilla forces would be located.

Table 5.10 in fact does show that only in the 1940 manual are Enemy Forces more likely to occur in paragraphs with Non-Urban Settings than other codes. Additionally the relative risk as another measure supports the odds ratio as showing a significance of Enemy Forces occurring in paragraphs that also contain a Non-Urban Area group code.

It is interesting that in these two different geographic settings, there are very few significant results from analyzing actor/setting code pairs for either urban setting codes or non- urban setting codes. This suggests that while areal aspects of counterinsurgency operations would still be important, that the urban/rural divide as discussed by Trinquier (1964) might not be as important within American counterinsurgency doctrine. Perhaps moving to a more general measure of the area of an insurgency might show more significant results when being paired with

100 various activities and actors. Table 5.11 pairs these two code groups with an Operations Area setting.

Table 5.10 Statistical associations among activities, actors, and non-urban setting codes in 1940 and 1967 Non-Urban Area Setting (Rural Area, Wilderness Area, Hinterland) 95 % Confidence Interval Activities Measure Value Lower Upper

Effective Activities 1940 Odds Ratio 1.291 0.478 3.482 Relative Risk Effective Activities = Yes 1.241 0.541 2.844 Relative Risk Effective Activities = No 0.961 0.816 1.132

Effective Activities 1967 Odds Ratio 0.750 0.206 2.733 Relative Risk Effective Activities = Yes 0.769 0.234 2.525 Relative Risk Effective Activities = No 1.026 0.923 1.139

Ineffective Activities 1940 Odds Ratio 1.516 0.642 3.581 Relative Risk Ineffective Activities = 1.431 0.679 3.016 Yes Relative Risk Ineffective Activities = No 0.944 0.841 1.060

Ineffective Activities 1967 Odds Ratio 1.235 0.465 3.281 Relative Risk Ineffective Activities = 1.211 0.500 2.934 Yes Relative Risk Ineffective Activities = No 0.980 0.894 1.075

Actors

Enemy 1940 Odds Ratio 3.969 1.299 12.128 Relative Risk Enemy = Yes 3.436 1.283 9.201 Relative Risk Enemy = No 0.866 0.744 1.008

Enemy 1967 Odds Ratio 0.756 0.300 1.904 Relative Risk Enemy = Yes 0.769 0.324 1.829 Relative Risk Enemy = No 1.018 0.960 1.079

Government 1940 Odds Ratio 0.471 0.142 1.566 Relative Risk Government = Yes 0.499 0.163 1.529 Relative Risk Government = No 1.058 0.971 1.153

Government 1967 Odds Ratio 0.539 0.154 1.894 Relative Risk Government = Yes 0.558 0.168 1.851 Relative Risk Government = No 1.035 0.975 1.097

Note: Significant measures are highlighted in bold.

Unlike the previous two tables, Table 5.11 shows no significant occurrence between code group pairs meaning that these codes are just as likely to occur with each other as not occur with each other and no real themes can be inferred. The next table, Table 5.12 compares activities

101 and actors with setting codes that represent Lines of Communications.

Table 5.11 Statistical associations among actions, actors, and operations area codes in 1940 and 1967 Operations Area Setting (Theater of Operations, Zone, Rear Area) 95 % Confidence Interval Activities Measure Value Lower Upper

Effective Activities 1940 Odds Ratio 1.100 0.382 3.166 Relative Risk Effective Activities = Yes 1.086 0.438 2.693 Relative Risk Effective Actions = No 0.987 0.857 1.145

Effective Activities 1967 Odds Ratio 1.375 0.644 2.934 Relative Risk Effective Activities = Yes 1.250 0.745 2.097 Relative Risk Effective Activities = No 0.909 0.714 1.158

Ineffective Activities 1940 Odds Ratio 1.319 0.550 3.161 Relative Risk Ineffective Activities = Yes 1.272 0.593 2.729 Relative Risk Ineffective Activities = No 0.964 0.863 1.079

Ineffective Activities 1967 Odds Ratio 1.008 0.534 1.903 Relative Risk Ineffective Activities = Yes 1.006 0.637 1.589 Relative Risk Ineffective Activities = No 0.998 0.835 1.192

Actors

Enemy 1940 Odds Ratio 1.735 0.652 4.616 Relative Risk Enemy = Yes 1.603 0.704 3.652 Relative Risk Enemy = No 0.924 0.788 1.083

Enemy 1967 Odds Ratio 1.310 0.810 2.119 Relative Risk Enemy = Yes 1.202 0.867 1.666 Relative Risk Enemy = No 0.917 0.786 1.071

Government 1940 Odds Ratio 1.588 0.646 3.901 Relative Risk Government = Yes 1.496 0.683 3.276 Relative Risk Government = No 0.942 0.838 1.060

Government 1967 Odds Ratio 0.741 0.414 1.324 Relative Risk Government = Yes 0.811 0.535 1.229 Relative Risk Government = No 1.095 0.928 1.292

Note: Significant measures are highlighted in bold.

Table 5.12 contains the largest number of significant results of any of the settings tables.

In this table, ineffective activities in both years are significant across all measures for being more likely to co-occur with Line of Communication Settings. Effective activities in the 1940 manual are more likely to co-occur with settings that are not Line of Communication settings. In the

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1967 field manual, Enemy actors are more likely to co-occur with Line of Communication settings than other settings.

Table 5.12 Statistical associations among activities, actors, and lines of communication codes in 1940 and 1967 Lines of Communication (Lines of Communication, River, Road, Transportation Codes) 95 % Confidence Interval Activities Measure Value Lower Upper

Effective Activities 1940 Odds Ratio 0.340 0.124 0.929 Relative Risk Effective Activities = Yes 0.434 0.187 1.009 Relative Risk Effective Activities = No 1.277 1.072 1.522

Effective Activities 1967 Odds Ratio 0.576 0.223 .1.484 Relative Risk Effective Activities = Yes 0.641 0.291 1.411 Relative Risk Effective Activities = No 1.113 0.948 1.308

Ineffective Activities 1940 Odds Ratio 5.598 2.536 12.357 Relative Risk Ineffective Activities = Yes 3.657 1.904 7.024 Relative Risk Ineffective Activities = No 0.653 0.546 0.782

Ineffective Activities 1967 Odds Ratio 2.664 1.283 5.529 Relative Risk Ineffective Activities = Yes 2.161 1.199 3.894 Relative Risk Ineffective Activities = No 0.811 0.695 0.947

Actors

Enemy 1940 Odds Ratio 1.506 0.575 3.944 Relative Risk Enemy = Yes 1.415 0.633 3.164 Relative Risk Enemy = No 0.940 0.801 1.103

Enemy 1967 Odds Ratio 2.215 1.160 4.228 Relative Risk Enemy = Yes 1.968 1.130 3.430 Relative Risk Enemy = No 0.889 0.806 0.980

Government 1940 Odds Ratio 0.465 0.182 1.186 Relative Risk Government = Yes 0.513 0.224 1.174 Relative Risk Government = No 1.105 0.983 1.241

Government 1967 Odds Ratio 0.859 0.404 1.829 Relative Risk Government = Yes 0.878 0.459 1.683 Relative Risk Government = No 1.022 0.920 1.136

Note: Significant measures are highlighted in bold.

Particularly in the 1940 field manual, the code “Patrol” is often talked about in conjunction with lines of communication. “In fairly open country, with roads available which permit the use of normal distances within the column, a reinforced rifle company or large organization can operate with reasonable control and battle efficiency” (Department of Navy

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1990, Chapter 6 Page 9). Likewise the code “Patrol” in the 1967 manual is also linked to lines of communication, “…small, highly mobile units moving by foot, track or wheel vehicle, air, or water. They will operate day and night in visiting populated areas, establishing surprise checkpoints on routes of communication, and preserving order outside the boundaries of populated areas” (Department of Army 1967, 50). In both cases, patrolling is strongly linked to lines of communication, yet the subtle changes in the usages of the codes can also be seen. Note how in the 1940 manual, the patrol is on foot along a road. Yet in the 1967 manual, the patrol has developed more mobility options either using vehicles or air transportation.

The last table, 5.13 looks at the activity/actor pairs with the State, Nation, Country

(Nation-State) setting code group. For these code pairs, in both cases, Enemy Forces in the 1940 manual and the 1967 manual are not as likely to occur with the Nation-State setting code group as they are with other codes. Also, in both years, ineffective activities are less likely to occur with this setting group compared to other settings. This suggests that just like the enemy forces code group, the ineffective activities code group is not associated with the setting that is at a larger geographic scale while they are, after table 5.12 associated with a geographic setting that is at a less extensive geographic scale.

5.5.4 Summarizing Themes from Qualitative Analysis

The qualitative analysis component of this dissertation has been used to analyze the interrelation between activities, actors and setting. This was done in three ways. First, the counts of codes between field manuals were compared to understand the changing emphasis of between these two field manuals. Second, the usage between codes was compared between field manuals. This was done to understand the changing nature of the code usage. The last method

104 of analysis was to use odds ratios and relative risk to characterize the occurrence of large groups of codes representing specific activities, actors, and geographic settings. Overall, the qualitative analysis showed that on average the frequency of codes per unit of analysis, in this case the paragraph, was very low necessitating the utilization of text analysis measures such as odds ratios and relative risk.

Table 5.13 Statistical associations among activities, actors, and Nation-State codes in 1940 and 1967 State (Country, Nation, State Codes) 95 % Confidence Interval Activities Measure Value Lower Upper

Effective Activities 1940 Odds Ratio 0.902 0.362 2.248 Relative Risk Effective Activities = Yes 0.921 0.445 1.908 Relative Risk Effective Activities = No 1.022 0.849 1.230

Effective Activities 1967 Odds Ratio 0.545 0.178 1.666 Relative Risk Effective Activities = Yes 0.592 0.219 1.596 Relative Risk Effective Activities = No 1.086 0.954 1.235

Ineffective Activities 1940 Odds Ratio 0.114 0.049 0.266 Relative Risk Ineffective Activities = Yes 0.179 0.087 0.367 Relative Risk Ineffective Activities = No 1.571 1.296 1.905

Ineffective Activities 1967 Odds Ratio 0.192 0.074 0.495 Relative Risk Ineffective Activities = Yes 0.242 0.104 0.565 Relative Risk Ineffective Activities = No 1.264 1.109 1.440

Actors

Enemy 1940 Odds Ratio 0.325 0.147 0.719 Relative Risk Enemy = Yes 0.498 0.285 0.871 Relative Risk Enemy = No 1.533 1.189 1.976

Enemy 1967 Odds Ratio 0.288 0.168 0.492 Relative Risk Enemy = Yes 0.407 0.271 0.612 Relative Risk Enemy = No 1.416 1.221 1.640

Government 1940 Odds Ratio 1.738 0.948 3.188 Relative Risk Government = Yes 1.345 0.973 1.860 Relative Risk Government = No 0.744 0.580 1.032

Government 1967 Odds Ratio 2.210 1.280 3.813 Relative Risk Government = Yes 1.686 1.200 2.370 Relative Risk Government = No 0.763 0.617 0.944

Note: Significant measures are highlighted in bold.

Several important themes can be drawn from the qualitative analyses done in these field manuals. First, as indicated in the second analysis, there is a change in the usage of codes

105 relating to changes in the technologies available to counterinsurgent forces. This is also supported in the first analysis as well. In the 1940 field manual, waterways either interior or coastal provided an important component of mobility in counterinsurgency operations. Air mobility played a secondary role in the 1940 manual. The 1967 manual reflects the evolution of military technology and implications in counterinsurgency operations. The code count for river has dropped from 74 occurrences in the 1940 manual to 12 occurrences in the 1967 manual. The usage of “Transportation Hub” follows this theme. Whereas in 1940 the majority use of this code was with respect to port facilities with airfields being a secondary concern, in the 1967 manual, “Transportation Hub” applies exclusively to airfields.

Recent scholarship in geography has stressed two specific issues in the study of politico- military forms of geographic scholarship, “mobility” (Cresswell et al 2016) and the vertical nature of power (Elden 2013). Particularly, as Shaw (2013) argues for his interpretation of the

Vietnam War, the dominant forms of technological advancement in the battlefield pushed military force vertically instead of increasing ‘horizontal’ capabilities. As counterinsurgency is an associated but not analogous form of warfare to conventional, the changes in these terms is meaningful as this provides additional insight into counterinsurgency warfare following similar trends. Despite Jackson (2005) arguing that infantry forms the backbone of the counterinsurgent force, the importance of airpower in these field manuals is highlighted. In relating this discussion to other datasets in this study, the defoliation program which was partly meant to increase the effectiveness of patrolling by increasing the visibility of an area by engaging in defoliation missions were based at airfields. Airfields act as a means from which to separate the counterinsurgent’s logistic infrastructure from the landscape and provide a means of protection from enemy forces.

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A second important theme developed from these analyses is the continuing use of what

Trinquier (1964) characterizes as ineffective activities. These activities continued to be present in the lines of communications setting in the 1967 field manual. In many ways technology again plays a role. Particularly with respect to patrols, the 1967 field manual shows a reconceptualization of the practice from being road bound to also including the use of aircraft.

While the technology might appear to offer new techniques for fighting counterinsurgencies, these technologies are only reimagining earlier counterinsurgency concepts.

The third theme that can be extracted from this analysis relates to the conceptualization of the insurgent forces as the object of counterinsurgency operations. In the 1940 manual, insurgent forces are strongly associated with non-urban settings. The 1967 manual does not associate insurgent forces with non-urban areas, rather insurgent forces are strongly associated with the lines of communication. In both manuals, insurgent forces are neither more or less likely to occur in urban settings.

These three general themes suggest that during the intervening years between 1940 and

1967 two important characteristics occurred with respect to counterinsurgency warfare. First, airpower added a new dimension to the prosecution of counterinsurgency operations and second, lines of communication evolved into ever increasingly important targets of insurgents.

5.6 Conclusions

These analyses represent a means to understand counterinsurgency doctrine. The next two chapters will analyze data representing the actual counterinsurgency environment during the

Vietnam War. The themes developed in this analysis will provide context for understanding the results of the series of spatial analyses in the next two chapters. While the themes will not be

107 explicitly incorporated into the analyses, they are implicit within the data selected for the spatial analyses. The defoliation data aligns with the increasing importance of airpower in counterinsurgency operations. The primacy of lines of communication can understood as the intervening space in between settings. In this way, the point pattern analyses will look at the outcomes between proximity to known enemy bases and hamlet control.

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CHAPTER 6 - A SPATIAL ANALYSIS OF HAMLET SECURITY PATTERNS

6.1 The Importance of Hamlet Control

In a revolutionary war, an important focus of both insurgency and counterinsurgency efforts is control of the population. Separating insurgents from their human environment is of the utmost importance by counterinsurgency policies (Trinquier 1966; Galula 1965). In the

Vietnam War, that meant control of hamlets. The hamlet (Xa) in South Vietnam was long seen as the fundamental unit of social interaction in rural areas (Fall 1954). Since the beginning of the state of South Vietnam, government policies have focused on securing the hamlet population beginning with the resettlement of almost one million people who left the North Vietnam in accordance with the Geneva Agreement of 1954 (Logevall 2013). The Agroville Program of

1959 was the first attempt at resettling the rural population of South Vietnam into new villages that were more easily accessible to the mechanisms of government (Zasloff 1963). This required a fundamental restructuring of the economic infrastructure of rural South Vietnam. The failure of the program (it was abandoned in less than a year after its start) was tied to the failure of the

South Vietnamese government to respect the local traditions and the rural population’s ties with their ancestral lands. Later, the Strategic Hamlets Program (1961-1963) employed during the early stages of the Vietnam War was designed to protect and insulate the rural population of

South Vietnam from the guerilla infrastructure of the Viet Cong and North Vietnam.

These programs failed in part because they separated the rural population from their ancestral lands and weakened local knowledge of the natural environment. During the main

109 combat period of the Vietnam War, securing hamlets remained a priority but not through extensive resettlement programs as in the earlier period. This chapter investigates the spatial pattern and changes in hamlet security from January, 1967 to December, 1968. This time frame was the most intense period of American troop involvement in the conflict and the most important insurgent operation, the Tet offensive, occurred midway through the time frame.

6.2 The Spatial Distribution of Hamlets Within the Environment

As discussed in Chapter 4, the U.S. military collected data on South Vietnamese hamlets from January, 1967 to January, 1974. The data used in this analysis is from the HAMLA version of the recording program. From January, 1967 to December, 1968, hamlet security was coded as being either contested, code of ‘CO’, under government security, a code of ‘HT”, or being under

Viet Cong control, a code of ‘VC”. A few other codes exist but referred less to security than to the stage of physical development.

As noted in Chapter 4, the number of hamlets surveyed changed from month to month and not every month covered the entire country. In those months with full spatial coverage, more than 10,000 hamlets were reported. Also as noted in Chapter 4, hamlets were not evenly distributed spatially but were clustered in the south and in the coastal regions of the north and north central. As would be expected, this clustering coincides with the natural environment of

South Vietnam. The hamlets mainly lie in the coastal plains and the lowlands of the Mekong

River deltas. Another important aspect of their distribution is their general absence from the forested regions that dominate South Vietnam’s landscape. Figure 6.1 displays the location of hamlets in January 1967 overlaid on top of the forested environment and visual inspection shows the hamlets are mostly away from the forested areas except in the central highlands.

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This relationship is more visible and can be quantified by creating a two kilometer buffer around individual hamlets and dissolving these buffers into an area of hamlet presence. This area is then overlaid with the forested area to find the intersection region where hamlets and forests coincide as well as the forested area without hamlets and the hamlet areas without forests.

Figure 6.2 displays these regions for the hamlet distribution of January, 1967. The areas in red denote the intersection region between hamlets and forests. The level of spatial coincidence can be measured using the coefficient of areal correspondence, which is the ratio of the area of intersection of two regions divided by the union of the same regions. This measure ranges from

0 (no overlap) to 1 (complete overlap). For the hamlet/forest relationship in Figure 6.2, this measure is 0.09 representing a very low coincidence. Similar values were found for other months during the period of investigation. The next sections investigate the spatial structure of hamlet security and the extent to which these structures changed over time.

6.3 Point Pattern Analysis of Hamlet Security Distributions

Security exists along both a political and a spatial continuum. From a political perspective, the continuum ranges from GVN controlled or secured hamlets to contested hamlets to those controlled by the Viet Cong. The spatial perspective is that the GVN secured hamlets should be in clusters and the VC controlled hamlets should also be in clusters although the GVN clusters should be spatially separated from the VC clusters. The contested hamlets should be located somewhere in between the GVN clusters and the VC clusters and in general not as strongly clustered as either of the other types of control. The actual relationship between the political continuum and spatial continuum of hamlet security is examined next using point pattern analysis.

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Figure 6.1 The location of hamlets for January 1967 with respect to the jungle region.

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Figure 6.2 The intersection of the hamlet region with the jungle region.

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6.3.1 Point Pattern Analysis

Point pattern analysis is used across a wide variety of disciplines to investigate the spatial relationship between different phenomena over distance (Baddeley et al 2016). Besides patterns in a Euclidean plane, point pattern analysis has been developed to look at points that are distributed on a network (such as a street system) or in three-dimensional space. The versatility of different methods in point pattern analysis make it suitable for the datasets used in this study.

The hamlet survey data as well as the enemy base area centroids are both represented as geographic points within a Euclidean grid. While these points do not represent the true size and shape of the objects in the landscape, they represent their distribution on the landscape at a given scale.

The core concept behind point pattern analysis is to determine the underlying effects of density and dispersion (Baddeley et al 2016). Patterns are understood as being indicative of underlying spatial processes. Yet, one must distinguish between point data versus point pattern, where data might be collected at specific points but are indicative of entities that are not points in nature such as hamlets. Point patterns can also include more than one type of point such as different species of trees. They can also include attribute data such as marks which are either qualitative (representing individual plants that are alive or dead) or quantitative representing an attribute such as tree size.

Additionally, underlying environmental factors called covariates are often modelled as explanatory data features that represent the specifics of the given point pattern. Descriptions of the spatial point pattern relate to three fundamental concepts: intensity, correlation and spacing.

However, for analyzing marked points, such as this study does, one does not have to worry about controlling for as many parameters as in a standard point pattern analysis.

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Wiegand and Maloney (2004; 2014) have noted that there are numerous types of data related to point pattern analysis. One must know the properties of several aspects of a given point pattern to select the correct method of point pattern analysis. First, one must have a clearly defined research question about the data. For this study the question is: what is the spatial structure between hamlets of varying security grades?

Second, one must identify how to relate the research question to the specific elements within the point pattern. One element is whether each point has an attribute, and if it does what is the data scale of the attribute. For the research question in this case, each hamlet point has the attribute related to its security status. This type of attribute is considered ‘qualitative in nature’

(Wiegand and Maloney 2014) because the attribute is a categorical variable. For this analysis, the security code of a given hamlet is the categorical variable (although these categories are ordinal in nature) used in the analysis to answer the research question. This means that examining hamlet security will use what Wiegand and Maloney (2014) call ‘data type four’, which has one attribute variable attached to each location.

For type four data, the basic question is understanding the processes responsible for producing the pattern of qualitative marks by using a test statistic. The null model for this marked point process is ‘random labeling’ which assumes that the point locations are fixed and that the attribute marks of the points are randomly distributed across the pattern of points

(Wiegand and Maloney 2014). In this study, the hamlet locations are fixed and it is the security codes what vary over space. Alternative realizations of the point pattern using the specified test statistic are simulated with random distributions of marks across points 199 times. The test statistic of the observed pattern is then measured against these simulations which are representative of the random labelling null model to search for deviations.

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Point pattern analysis is used then to detect the underlying spatial structure within a set of points which represent discrete objects within a given area. It provides a useful numerical complement to visual means of detecting the spatial structure of patterns that might otherwise go undetected by visual inspection only. This situation is illustrated by the point pattern presented in Figure 6.3. This example contains a subset of 236 points from the HAMLA dataset for March

1968. In this figure, VC controlled hamlets given in red are designated as mark 1, and contested hamlets given in green are designated as mark 2. Based on a visual inspection of the points in the observation window, one might assume that there is a fair amount of segregation between these two types of points as it appears that the green dots are clustered within the observation window to varying degrees, but there is little overall interspersion of marks 1 and 2. One might say that the two types of points tend to cluster together and exhibit spatial segregation.

Figure 6.3 A distribution of 236 Viet Cong controlled and contested hamlets that form the example dataset.

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To determine if the visual inspection is correct, a point pattern analysis is performed.

Because our analysis is analyzing a ‘qualitative’ attribute of the points, whether a hamlet is controlled by the Viet Cong versus contested by the government of South Vietnam, the specific test statistic used to measure relationships in this example is a mark connection function. Mark connection functions are based on the probability that a given point at distance r from an observation point, the focal point, is of a specific qualitative mark. With two marks, the mark connection function p11 uses mark 1 points as the set of focal points and finds the probability that another mark 1 point will be found at distance r from any focal point. The mark connection function p22 uses mark 2 points as the set of focal points and find the probability that another mark 2 point will be found at distance r from any focal point in this set. For mark connection function p12, the focal points are mark 1 and we find the probability of a mark 2 points at r distance from a focal point; mark connection function p21 reverses the marks in this relationship.

Formally, the mark connection function, plm, is calculated (Wiegand and Maloney 2014) as:

n n,, ≠ i plm = ∑ i=1 ∑j=1 Clm (xi , xj) k(dij – r) / ∑ i=1 ∑j=1 k(|dij – r|) . (6.1)

Clm (xi , xj) is an indicator function that equals 1 if focal point i has mark l and the other endpoint has mark m; k( ) is a kernel density function, dij is the distance between point i and j, and r is the distance scale being measured by the mark connection function. Kernel density functions take a value between 0 and 1. As the mark connection function is a probability function:

p11 + p22 + p12 + p21 = 1. (6.2)

Given that a is the proportion of mark 1 points and b is the proportion of mark 2 points in the

2 2 dataset, the expected value of p11 is a , of p22 is b and both p12 and p21 should equal ab if the points were randomly distributed (Jacquemyn et al 2010; Wiegand and Maloney 2014).

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Determining the probability of each of these four outcomes at varying distances reveals the spatial structure of the overall point pattern. The null model for this type of point pattern analysis is that the marks are randomly distributed and not the product of some underlying spatial structure. A total of 199 simulations was performed to ascertain how likely the function derived from the empirical dataset was from what would be expected if the mark values of the points were randomly chosen. The mean mark connection values for the 199 simulations will approximate the expected values over all distances. In the example, the expected value for p11 is

0.155, for p22 is 0.367 and for both p12 and p21 is 0.239. For the purposes of this example, a grid cell size of 1,000 meters in length is used; the grid cell size is used to aggregate individual distance pairs into larger groupings. In Figure 6.4 the horizontal value shows that the expected

th p11 values is approximately 0.155 over all distances. For the 199 simulations the 5 highest and

5th lowest function values at each distance is used to construct an envelope within which values are not that different than what would be expected at random. Any time the observed function enters the simulation envelope the pattern observations at that distance are interpreted as being random. Those distances for which the observed function exits the simulation envelope can be interpreted as representing evidence of some form of underlying spatial structure.

Figure 6.4 The marked connection function p11 associating mark 1 points with other mark 1 points in the example over all distances.

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The graph of p11 denoted by the line with red diamonds in Figure 6.4 shows that over distances less than 4,000 meters the value is near or above the envelop indicating a clustering of

VC controlled hamlets or a higher density of them than expected at random. The observed value goes above the envelope again at 8,000 meters and then again between 32,000 and 33,000 meters. Between 12,000 and 24,000 meters the observed values are below the lower envelope values indicating lower density of VC controlled hamlets than would be expected at random for these distances with respect to other VC controlled hamlets. Overall, the clustering occurred over short distances. The higher than expected density at 32,000 meters indicates the distance between the different short distance clusters. When the values go below the simulation envelope over shorter distances, this can be interpreted as a dispersion of these marks; however, when this occurs at higher distances as the situation between 12, 000 and 24,000 meters, this shows a void of similar marks at these distances. In the plot of the hamlets in Figure 6.3. The Viet Cong controlled hamlets are mainly located around the perimeter of the point pattern; as one moves towards the center there is a relative void of these marks corresponding at distances 12,000 to

24,000 from the outer rim of the pattern.

In contrast, the values of p22 were above the envelope out to a distance of 18-19,000 meters (Figure 6.5). The clustering of this type of hamlet control extends out a larger distance as these hamlets are more centrally located and bunched together. The p22 function dips below the envelope at distances beyond 31,000 meters as there are not as many as expected points of this type on the perimeter.

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Figure 6.5 The marked connection function p22 associating mark 2 points with other mark 2 points in the example over all distances.

Finally, how do these two marks vary with respect to one another? The functions p12

(Figure 6.6) and p21 (Figure 6.7) both show somewhat similar results. Similar results are somewhat expected as the relationships are for the most part mirror images of one another. Both observed functions are well below the simulation envelope up to distances between 11,000 to

12,000 meters. This shows dispersion or spatial segregation of the two marks in the pattern meaning that VC hamlets are not likely to be near hamlets that are contested. Then p12 stays within the envelope out to 24,000 meters and stays somewhat above the envelope over greater distances, whereas p21 stays almost along the lower boundary of the envelop for distances greater than 13,000 meters. By comparing this to the visualization of the pattern we can see that at smaller distances from VC hamlets there are not very many contested hamlets and that the clustering of the two only occurs when one considers the entire observation window and all of the points within the pattern. This example help relate the information in the results graphs to a visual distribution of the point pattern in Figure 6.3.

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Figure 6.6 The marked connection function p12 associating mark 1 points with mark 2 points where the mark 1 points are the focal points in the example.

Figure 6.7 The marked connection function p21 associating mark 2 points with mark 1 points where the mark 2 points are the focal points in the example.

These results are interpreted from only two of a number of spatial perspectives. Besides examining the level of departures from random labeling to determine if the process generating the pattern is promoting clustering or dispersion of the mark under consideration within the univariate pattern (the unmarked pattern) and the level of segregation between two marks at different spatial scales, two other tests are possible. A third test examines whether the process distributing the marks is affecting only one type of marked point but not the other, and a fourth test determines whether the density of points around one type of mark is greater or less than the density of points around the other type of marked point. All of these perspectives taken together

121 present an overall view of the spatial structures within any point pattern, and are used next to ascertain the type spatial structure associated with hamlet security across all of South Vietnam.

6.3.2 The Spatial Structure of Hamlet Security

The twenty-four month period of HAMLA data was divided into quarters and the pattern of security was examined for January, March, June, September, and December of 1967 and

March, June, September and December of 1968. It is important to characterize the spatial structure of the marks representing the three stages of security to better understand the spatial structure of these levels of security throughout South Vietnam. Table 6.1 presents the total number of hamlets associated with each security type. Overall, more than 10,000 hamlets belonged to one of the three security types in each time period. The number of hamlets in each category also did not change much from quarter to quarter. In relative terms, the percentage of hamlets in each category also did not change very much over the time period. The VC controlled group changed the most from a high of 30.2% in January 1967 to a low of 28.1% in December

1968, a loss of only about two percent in two years. The government secured group stayed at about 39.7% for most of the time, and the contested group increased slightly by about 1.7% between the start and the end of the two years.

The next step is to determine the spatial structure of the security continuum and to what degree it changed over that time frame. Simple mapping of the security types is not sufficient to determine the nuances of the spatial structure. Figure 6.8 displays the distribution of hamlets by security types for January, 1967. One can see that VC controlled hamlets (in red) tend to cluster and government secure hamlets (in blue also cluster and the contested hamlets (in green) are somewhat in between but this is not definitive. For a finer investigation, three separate random labeling analyses were conducted in which two security types were paired together done for each

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Figure 6.8 The spatial pattern of hamlet security codes in January 1967.

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TABLE 6.1 The Number of Hamlets Associated with each Security Type

Date GVN Secure Contested VC Controlled Total

January 1967 3988 (39.7%) 3016 (30.1%) 3037 (30.2%) 10041

March 1967 4046 (39.3%) 3169 (30.7%) 3086 (30.0%) 10301

June 1967 4159 (39.7%) 3225 (30.8%) 3090 (29.5%) 10474

September 1967 4334 (39.4%) 3475 (31.7%) 3181 (28.9%) 10990

December 1967 4340 (39.6%) 3468 (31.6%) 3165 (28.8%) 10973

March 1968 4386 (39.5%) 3509 (31.7%) 3195 (28.8%) 11090

June 1968 4373 (39.7%) 3488 (31.6%) 3168 (28.7%) 11029

September 1968 4340 (39.7%) 3440 (31.5%) 3143 (28.8%) 10923

December 1968 4278 (40.2%) 3377 (31.7%) 2994 (28.1%) 10649

pair of hamlet security types. These analyses were used performed in the Programita software system (Jackuemyn et al 2010; Weigand and Moloney, 2004; 2014).

The first random labeling matched the GVN hamlets against the contested hamlets; this examines the pattern associated with one end of the security continuum. As noted in the previous section, there are several questions that can be asked regarding the spatial relationships in a random labeling analysis. The first is whether there is more or less clusteringn in each marked pattern than in the overall unmarked pattern. This question is answered using marked connection functions p11 and p22. Figures 6.9 and 6.10 show the mark connection functions p11 and p22 for the month of January, 1967; in this figure the mark ‘1’ refers to government secured hamlets and mark ‘2’ refers to contested hamlets. Figure 6.9 shows that within 20 kilometers,

GVN secured hamlets are aggregated within all pairs of non-VC controlled hamlets at these distances. Figure 6.10 shows that all contested hamlets are also clustered within all non-VC hamlets but to a range of 70,000 meters. Overall then the clustering of government secured

124 hamlets is tighter than that for contested hamlets. Secondly, the maximum difference between the test statistic and the expected value is greater over the shortest distances for the government secured hamlets.

Figure 6.9 The marked connection function for GVN secured hamlets with respect to other GVN secured hamlets with contested hamlets as mark 2 for January 1967

Figure 6.10 The marked connection function for contested hamlets with respect to other contested hamlets with GVN secured hamlets as mark 1 for January 1967.

The next question is to what degree are government secure hamlets and contested ones attracted to or are segregated from one another. Figure 6.11 shows the summary statistic p12 in which this observed marked connection function lies well below the envelope over all distances.

This denotes that the neighborhood density of contested hamlets is much lower around secured hamlets than the expected amount. Thus, there is spatial separation between secured and contested hamlets over all distances.

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Figure 6.11 The mark connection function p12 for GVN secured and contested hamlets where the GVN secured hamlets are the focal points for January 1967.

To determine whether the process distributing the marks over the locations is affected only one type of point but not the other, the results of the two summary statistics g12(r) – g22(r) and g21(r) – g11(r) can be compared (Weigand and Moloney 2004). These g statistics are paired correlation functions that are similar to the marked connection function but use an area density value in the denominator rather than a count of points at any spatial scale. If the value of g12(r) – g22(r) is approximately zero, then the density of the second mark around the first mark at distance r is almost the same as the density of the second mark around other second marks. The converse applies for the value of g21(r) – g11(r). The graphs in Figure 6.12 and 6.13 show a strong, negative departure from the null model out to 26 kilometers for contested hamlets within secure hamlets and out to 48 kilometers for secure hamlets within contested ones. This again supports the hypothesis of a spatial separation between the two types of hamlets.

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Figure 6.12 The difference in the marked correlation functions, g21-g11, where GVN secured hamlets are mark 1 and contested hamlets are mark 2 for January 1967.

Figure 6.13 The difference in the marked correlation functions, g12-g22, where GVN secured hamlets are mark 1 and contested hamlets are mark 2 for January 1967

The final test is to determine if one type of hamlet is surrounded, on average, by more hamlets with the same mark or a different mark – in other words, is the density of hamlets around one type greater than the density around the other type. For this analysis, this test determines if secured hamlets are surrounded by more hamlets in their neighborhood or if contested hamlets are surrounded by more hamlets in their neighborhood. The summary statistic for a test of density-dependent effects is given by g1,1+2(r) − g2,1+2(r). This statistic compares the density of a neighborhood with both marks surrounding the first mark against the neighborhood with both marks surrounding the second mark. The expected value of g1,1+2(r) − g2,1+2(r) is zero under random labeling (Weigand and Moloney 2014). In Figure 6.14, it is clear that there are more hamlets in the neighborhoods surrounding contested hamlets than there are in the neighborhoods around secure hamlets between distances of four kilometers to 48 kilometers.

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This could be a sign that the North Vietnamese are contesting more in areas of higher hamlet density.

Figure 6.14 The difference in density functions where GVN hamlets are mark 1 and contested hamlets are mark 2 for January 1967.

The other end of the security spectrum is investigated by comparing the VC hamlets to the contested hamlets; now VC control is denoted as mark ‘1’ and contested is denoted as mark

‘2’. Figures 6.15 to 6.20 present the results for the same tests as those given in Figures 6.9 to

6.14 respectively. In these graphs, there are similar patterns to those between government secured and contested hamlets but there are differences in the details. VC controlled hamlets are only clustered out to a distance of 12 kilometers (Figure 6.15) whereas secured hamlets in the previous analysis were clustered to a distance of 20 kilometers, and contested hamlets are clustered out to 90 kilometers (Figure 6.16). From 36 kilometers to 90 kilometers there is a substantially lower proportion of VC controlled hamlets marking a wide separation between VC controlled hamlet clusters. If the hypothesis is correct, that contested hamlets are spatially in between GVN secured and VC controlled hamlets, then one would expect that contested hamlets to be bunched at longer distances as in Figure 6.16.

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Figure 6.15 The marked connection function for VC controlled hamlets with respect to other VC controlled hamlets with contested hamlets as mark 2 for January 1967.

Figure 6.16 The marked connection function for contested hamlets with respect to other contested hamlets with VC controlled hamlets as mark 1 for January 1967.

Figure 6.17 shows that neighborhood density of contested hamlets is much lower around

VC controlled hamlets than expected. Thus, there is some spatial separation between VC controlled and contested hamlets out to 48 kilometers.

Figure 6.17 The mark connection function p12 for VC controlled and contested hamlets where the VC controlled hamlets are the focal points for January 1967.

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The graphs in Figure 6.18 and 6.19 again show a strong, negative departure from the null model out to 32 kilometers for contested hamlets within VC controlled hamlets and only out to

24 kilometers for VC controlled hamlets within contested ones. This again supports the hypothesis of a spatial separation between the two types of hamlets at the other end of the security spectrum.

Figure 6.18 The difference in the marked correlation functions, g21-g11, where VC controlled hamlets are mark 1 and contested hamlets are mark 2 for January 1967.

Figure 6.19 The difference in the marked correlation functions, g12-g22, where VC controlled hamlets are mark 1 and contested hamlets are mark 2 for January 1967.

Finally, In Figure 6.20, it is clear that there are more hamlets in the neighborhoods surrounding contested hamlets than there are in the neighborhoods around VC controlled hamlets between distances of two kilometers to 18 kilometers and from 30 to 85 kilometers. This result in conjunction with the one for the secured/contested pairing suggests that both sides are both contesting more in areas of higher hamlet density.

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Figure 6.20 The difference in density functions where VC controlled are mark1 and contested hamlets are mark 2 for January 1967.

The last series of analyses compares the two ends of the spectrum, the marked pattern of

Viet Cong controlled versus secured hamlets; now a GVN secured hamlet is denoted as mark ‘1’ and VC controlled ‘2’. Figure 6.21 shows that there is a strong clustering above expected among secured hamlets over all distances.

Figure 6.21. The marked connection function for GVN secure hamlets with respect to other GVN hamlets with VC controlled hamlets as mark 2 for January 1967.

Among VC hamlets, the strong departure above expectation only extends out to 48 km and after 52 km the trend is below expectation (Figure 6.22). At the latter distances, there is an absence of VC controlled hamlets at these distances away from other VC controlled hamlets.

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Figure 6.22. The mark connection functions of VC controlled hamlets with respect to other VC Controlled hamlets with GVN secured hamlets as mark 1 for January 1967.

Next, the marked connection function between secured and VC controlled shows that there is less than expected connection across all distances (Figure 6.23). Secured hamlets are spatially separated from VC controlled hamlets for all distances which is much different than the relationship between GVN secured hamlets and contested hamlets. This again supports the notion that GVN secured hamlets and VC controlled hamlets are spatial opposites of one another, more so than with the contested hamlets.

Figure 6.23 The Mark Connection Function p12 for GVN secured and VC controlled hamlets where the GVN secured hamlets are the focal points for January 1967.

The graphs in Figure 6.24 and Figure 6.25 again show a strong, negative departure from the null model out to 82 kilometers for secured hamlets within secured hamlet neighborhoods and only out to 48 kilometers for VC controlled hamlets within secure hamlet neighborhoods.

This spatial separation is stronger than the earlier ones between secure and contested hamlets and

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VC controlled and contested hamlets supporting the hypothesis of greater spatial separation for hamlets at different ends of the political security spectrum.

Figure 6.24 The difference in the marked correlation functions, g21-g11, where GVN secured hamlets are mark 1 and VC controlled hamlets are mark 2 for January 1967.

Figure 6.25 The difference in the marked correlation functions, g12-g21, where GVN secured hamlets are mark 1 and VC controlled hamlets are mark 2 for January 1967.

Finally, Figure 6.26 shows that the density of hamlets in the neighborhoods surrounding

GVN secured hamlets are greater than that for VC controlled hamlets out to a distance of 12 kilometers; from 20 to 32 kilometers the density associated with VC controlled hamlets is higher than for GVN secured hamlets. The trend shifts again as the density for secured is higher from

46 to 92 kilometers The much higher density in the short distance range suggests that the North

Vietnamese and Viet Cong’s immediate neighborhoods were not operating in areas of higher hamlet density when compared against the GVN secured neighborhoods.

The results for January 1967 form the benchmark for the following eight time periods.

Overall, the patterns were the same with differences only in the details. This is to be expected

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Figure 6.26 The difference in density functions where GVN secured hamlets are mark1 and VC Controlled hamlets are mark 2 for January 1967.

given the level of temporal autocorrelation from time period to time period that results from the stable nature of hamlet locations and their associated security designation over a three month to

24 month duration. Figure 6.27 shows the spatial pattern of hamlet security for December 1968 the last month of the study period; overall it is relatively similar in its pattern to that of January,

1967 (Figure 6.8) although more hamlets are included. However, there were some important changes in the relationship of VC controlled hamlets to the other security types at that time.

In a comparison of the spatial relationships between VC controlled and GVN secured hamlets between January 1967 and December 1968, certain trends are apparent. First, whereas

VC clusters in January 1967 extended out to 48 km (Figure 6.22), VC clusters in December 1968 extended out farther to 52 km (Figure 6.28). Secondly, the distance over which the density of hamlets was higher for GVN hamlets decreased from 12 km in January 1967 to 10 km in 1968

(Figure 6.29). With respect to contested hamlets, VC controlled hamlet clusters grew from a distance of 12 kilometers (Figure 6.15) to almost 50 km (Figure 6.30). The distance over which the density of hamlets was higher for contest hamlets decreased from 12 km in January 1967

(Figure 6.20) to 10 km in 1968 (Figure 6.31). This change at different distances while the

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Figure 6.27 The spatial pattern of hamlet security codes in December 1968.

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Figure 6.28. The mark connection functions of VC controlled hamlets with respect to other VC Controlled hamlets with GVN secured hamlets as mark 1 for December 1968.

Figure 6.29 The difference in density functions where VC controlled are mark1 and GVN secured hamlets are mark 2 for December 1968.

Figure 6.30. The mark connection functions of VC controlled hamlets with respect to other VC controlled hamlets with contested hamlets as mark 2 for December 1968. overall proportions of each security type remained about the same means that there were real shifts in the spatial structure that are independent of the overall changes in the amount of hamlet control. Although some of these changes were not dramatic, it seems that the insurgents were able to encroach into the territory that was once contested and the separation with GVN secured hamlets decreased. The spatial structures for the intermediate quarters are given in Appendix B.

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Figure 6.31 The difference in density functions where VC controlled are mark1 and contested hamlets are mark 2 for December 1968.

6.4 Summary

This analysis has focused on the spatial arrangement of hamlets in South Vietnam with respect to the spectrum of security levels. Overall, the spatial patterns of security corresponded with the political spectrum of security; both the GVN secured hamlets and the VC controlled hamlets were clustered with other hamlets of the same security code, and the two types were spatially separate from one another. The contested hamlets were less clusterd and were located between the other two security types. It was also noted that the relationships did not change much from time period to time period. This is most likely due to the problem of temporal autocorrelation. The lack of changes in overall proportions while changes occurred at different distances implies that there are real shifts in spatial structure occurring independent of overall shifts in amount of controlled hamlet areas.

The areal extent of the clustering between January of 1967 and December of 1968 increased while the strength of that clustering declined. While the insurgents may have increased the geographic extent of their hamlet domination by the increasing distances of clustered VC controlled hamlets, the number of hamlets that they controlled did not increase indicating that there was a decline in the strength of that control. While this analysis establishes

137 the spatial connection to this spectrum, no links have been made yet to insurgency and counterinsurgency tactics designed to influence the level of security in favor of one side or the other.

The next chapter examines the spatial aspects of some of these tactics during the period of investigation, and their relationship to the changes in security type among hamlets from one quarter to another. .

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CHAPTER 7 – AN ANALYSIS OF THE IMPACT OF INSURGENCY/COUNTERINSURGENCYTACTICS ON HAMLET SECURITY

7.1 Introduction

Fall (1963) has noted a distinction between guerilla warfare or insurgencies and revolutionary warfare. In revolutionary warfare, military action is an appendage to a larger political mobilization of the population. The insurgent tactics of a revolutionary war are therefore tied to political attempts to convince the people to support their cause. Thus insurgents not only are directing their policies towards the military defeat of their enemies’ armed forces but also their defeat in support by the population. As noted earlier, separating insurgents from their human environment is a major focus of counterinsurgency policies (Trinquier 1964; Galula

1965), although political success may not succeed if this is limited to mainly military actions.

This chapter will examine a pair of strategies – one insurgent and one counterinsurgent – tied to the control of the hamlet population in South Vietnam. The analyses will link the spatial pattern of hamlet security examined in the last chapter with these two counter strategies. These strategies are linked together also by their spatial contest being focused within the jungle environment of South Vietnam. The success of each strategy will be evaluated both from a military and a political perspective.

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7.2 Enemy Base Locations and the Environment

In the context of U.S. counterinsurgency doctrine, enemy base camps represent secure areas designed to support and supply insurgent forces engaged in politico-military operations within South Vietnam. These were locations that allowed forces to train, accumulate supplies and provide medical facilities for the insurgent forces. These locations represent key centers for supplies coming into the political military organization from sources such as the Ho Chi Minh

Trail or Sihanouk trail or from locations within South Vietnam which would then be redistributed to the insurgent agents operating throughout South Vietnam. Prior to the Tet offensive, base areas outside of Hue acted as key forward planning centers and intelligence nodes that were in constant contact orchestrating the buildup and prepositioning of supplies to aid in the upcoming offensive (Bowden 2017). Ultimately these areas operated in much the same manner as air bases for U.S. and allied forces in South Vietnam. They theoretically supplied a ‘rear area’ delineating a safe zone from the area of perceived ‘contamination’.

As noted in Chapter 4 there were 139 enemy base camps active at some point in time in the South Vietnam theater of operations. Of these 139 base camps, 101 were located in South

Vietnam itself and 38 base camps (blue dots in Figure 7.1) were located in the neighboring countries of North Vietnam, Laos, and Cambodia. The base camps outside of South Vietnam provided what Fall (1963) calls an active sanctuary. He believed that active sanctuaries were very important to the sustained existence of a revolutionary war because they provided the insurgents with shelter, training facilities, and equipment. During the French Indochina War, the

Viet Minh had active sanctuaries in China, especially after the fall of that country to communists in 1949. The North Vietnamese used the same strategy again during the Vietnam War against the United States.

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Figure 7.1. The location of North Vietnamese base camps in South Vietnam (red dots) and active sanctuaries in neighboring countries (blue dots).

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A second aspect of the overall pattern of base camp locations is their reliance on the jungle land cover in South Vietnam. Again, building on the experience of the Viet Minh during the French Indochina War, the North Vietnamese sought locations in the forested highlands.

There were a total of 84 camps (red dots in Figure 7.2) out of the 101 camps that were within 2 kilometers of a forested area and 67 that were completely within the jungle land cover (see

Figure 7.2). The insurgent base camps located in the non-jungle region were in the southern region near Saigon and the Mekong Delta.

Although most of the base camps were placed then in the jungle, they were still proximate to the hamlet populations – at the interface of the natural environment for shelter and the human environment for political access and control (see Figure 7.3). This is especially true near the coast all the way from the Hue area in the north to the Saigon area in the south. The human/natural landscape interface then would be the focus of insurgent and counterinsurgent operations as both sides vied for this critical territory.

Of particular interest to this study is the dynamics of North Vietnamese base camp locations between January 1967 and December 1968. January 1967 marked the apex of base camps locations with 93 base camps. Between that month and December 1968 the number declined to 56 camps (the lowest was in September, 1968) (see Table 7.1). Another interesting aspect of the dynamic was that as the total number of camps declined, the number in active sanctuaries increased to a peak of 24 in June 1968 and then returned to the same number in

September and December 1968 as there was in January 1967 – 18 camps (Table 7.1) although the 18 active sanctuaries in December 1968 was a much higher percentage of the overall number of base camps than what the 18 active sanctuaries in January 1967 was. Over time there was

142 more dependence on active sanctuaries due to the counterinsurgency actions taken within South

Vietnam by the U.S. military.

Figure 7.2 Location of North Vietnamese base camps in the jungle environment (red dots) and the Mekong Region (blue dots). Active sanctuaries are in purple.

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Figure 7.3 Location of North Vietnamese base camps (red dots) with respect to the hamlet areas (in blue) in January 1967. Active sanctuaries are in purple.

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Table 7.1 Number of Enemy Base Camp Locations by Month

Camps Camps Camps Internal Number Remaining from Removed Added in to South Active Date of Camps Previous Date in Period Period Vietnam Sanctuaries January, 1967 93 ------75 18

March, 1967 90 86 7 4 73 17

June, 1967 77 77 13 0 60 17

September, 1967 79 67 10 12 58 21

December, 1967 66 63 16 3 44 22

March, 1968 64 52 14 12 42 22

June, 1968 60 58 6 2 36 24

September, 1068 55 48 12 7 37 18

December, 1968 56 52 3 4 38 18

The overall pattern of base camps shown in Figure 7.3 is also reflected in the pattern for those base camps active in January 1967 with some deviations. Most of the active sanctuaries are located in the far north (see Figure 7.4) in Laos and North Vietnam. The camps inside South

Vietnam follow the overall pattern of being located in that interface between the human and forested environments down the coast to the Saigon region (Figure 7.4). By December 1968 these patterns had changed somewhat as the active sanctuaries shifted to being all along the Laos and Cambodian borders Figure 7.5). The number in the coastal interface zone had substantially declined and a couple of new bases were added to the South Vietnamese side of the Cambodian border (Figure 7.5). The decline in total number over time and the spatial shifts in location are investigated next in conjunction with the counterinsurgency efforts of the U.S. defoliation program.

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Figure 7.4 Location of active North Vietnamese base camps (red dots) in South Vietnam and active sanctuaries in neighboring countries with respect to the jungle and hamlet areas for January 1967.

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Figure 7.5 Location of active North Vietnamese base camps in South Vietnam and active sanctuaries in neighboring countries with respect to the jungle and hamlets areas for December 1968.

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7.3 The Spatial Relationships of Operation Ranch Hand

As discussed in Chapter 3, the Operation Ranch Hand herbicide program was the U.S. military’s attempt to improve the security capabilities of the GVN and allied forces by removing the dense jungle vegetation that was providing a key source of cover and concealment for the insurgent enemy. There was technically no way to delineate front lines within the country, and enemy forces were able to use the jungle to hide their movements and base areas. Beginning in

1961, defoliation in South Vietnam was viewed as a means of assisting the GVN in two key aspects of the United States defense support policy: as an aid in improving the interdiction of supplies moving across South Vietnam’s borders and as a direct means for implementing technological solutions to the counterinsurgency problem.

Slowly, the herbicide program developed into two basic types of missions, spraying defoliation runs to improve visibility in areas of known insurgent activity, thereby improving surveillance capabilities, and in theory decreasing the troop requirements to conduct area control operations against the insurgency. The second major objective of the herbicide campaign was to target agricultural areas, namely rice fields, to deny sources of food to the insurgents and to force the Viet Cong to devote more time to supplying its members with food. The infrastructure utilized and expanded during the conflict had already existed in the U.S. military for quite some time. Beginning in the 1920s and 1930s the U.S. military had developed aerial spray capabilities by spraying pesticides for agriculture purposes. During the Second World War, this spray capability was utilized in the Pacific Theater to combat the vectors for various diseases endemic to those regions (Buckingham 1982). Prior to implementation in South Vietnam, limited spraying had been executed during the Malayan Emergency by British Forces (Buckingham

1982).

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Implementation of these capabilities in South Vietnam was viewed from the standpoint of economy of force. President Diem was particularly supportive of defoliation for crop destruction missions. While the missions started in 1962, their implementation was limited primarily to spraying lines of communication and limited targets in the area around Saigon. Major expansion of the spray missions began in 1965 with the full implementation of both types of missions.

Spraying continued to expand in size and distribution from 1965-1968. For maximum effect, it was suggested that 3 gallons per hectare be used which necessitated aircraft to spray an area twice to reach the minimum requirement for the desired effect (Buckingham 1982).

During this period, spraying also expanded into southern Laos to target the supply networks emanating from North Vietnam. Defoliation of mangrove swamps was deemed to be especially effective due to the characteristics of those habitats. Defoliation was also used as a preliminary step in trying to induce massive forest fires by first killing the vegetation by defoliation and then using incendiary bombs and napalm to start massive forest fires

(Buckingham 1982). When these attempts were conducted, they almost universally were ineffectual. As the program expanded, the initial air fleet of 6 aircraft was slowly expanded to over 40 aircraft by 1969.

Over the course of the program, this method was extremely controversial from two perspectives. From a political-military perspective, it was argued that when the mission was to destroy crops, defoliation was not precise enough and ground intelligence was ambiguous enough such that the ownership of rice fields could never be reliably determined (Buckingham

1982). Often areas were sprayed belonging to farmers who were not insurgents or supporting them. It could never be reliably determined whether or not the loss of crops outweighed the

149 negative impact the spraying missions had on civilian populations, especially as Viet Cong propaganda stated that defoliants were poisonous to people.

The second controversy was centered on the ecological and moral impact of the spraying program (Buckingham 1982). Beginning in the early years of the program and growing into a large advocacy group by the end of the 1960s, many scientists and activists argued against the use of herbicides based upon their negative effect on the environment and the structure of the ecosystems in South Vietnam. Under the weight of public opinion and the specific use of Agent

Orange which had known negative effects on human exposure and with a lack of suitable alternatives, the herbicide program was shut down by 1970. Although health and environmental issues were major factors in the stopping Operation Ranch Hand, another important factor would be the effectiveness of its role in counterinsurgency measures. Was the program effective in neutralizing enemy base camps and/or forcing their relocation to more remote areas away from the rural hamlet population?

The defoliation program during the conflict framed the position of the ‘jungle’ within the context of efficiency and security during the Vietnam War. First, for the insurgent, the jungle provided a secure location to station their infrastructure and base areas. The jungle provided an efficient location to conceal their operations from the materially superior counterinsurgent forces. Second, from the standpoint of the counterinsurgent, the jungle represented a zone of insecurity with respect to protecting rear areas, vital locations and population centers, the jungle was a region that required more material and personnel to secure compared to other terrain. The purpose of the defoliation program, therefore, was to decrease the security of the insurgent infrastructure while in theory it would increase the efficiency with which the counterinsurgency could use forces to secure given areas. This would suggest that areas which had been heavily

150 defoliated would be areas where enemy base camps were more apt to be destroyed. The analyses in the following subsections assess the nature of spatial relationships with natural and human ecosystems and the effectiveness of the defoliation program with respect to enemy base camp locations in these ecosystems.

7.3.1 Spatial Relationships with the Natural and Human Environments

The first aspect of the spatial relationship between the herbicide program and the environments of South Vietnam is that the flight paths in general avoided the hamlet population.

Figure 7.6 displays an overlay of a one kilometer buffer region around the 7,067 flight paths against the hamlet region of January, 1967. In Figure 7.6, the areas in red denote the intersection region between hamlets and flight paths. The coefficient of areal correspondence for the hamlet/flight path relationship in Figure 7.6 is 10% of the area of the intersection of the hamlet and flight path regions divided by the area union of these same regions); this is a low value indicating the avoidance of the hamlet region. However, when the flight path region is compared against the forested areas (the intersection region is again in red in Figure 7.7) the coefficient of areal correspondence rises to 30.1% of the intersection area between flight path and forested regions divided by the area union of these same regions; this represents a much higher coincidence than the previous one between flight paths and hamlets. Overall 77.9% of the flight path region in South Vietnam occurred within the forested areas of that state. The defoliation was not a war on the population directly but it was a war on the environment.

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Figure 7.6. The location of the flight path region with respect to the location of the hamlet region for January 1967. The hamlet region only is in blue, the flight path region only is in grey and the intersection of these regions is in red.

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Figure 7.7. The location of the flight path region with respect to the location of the jungle region. The jungle region only is in green, the flight path region only is in purple and the intersection of these regions is in red.

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7.3.2 Spatial Relationships with the Base Camps Locations

Because of its mission objectives, one would expect that the flight paths would relate to the position of North Vietnamese base camps. Figure 7.8 shows the flight paths that occurred between June 1, 1965 and December 31, 1966 (a total of 1209 flights) in relation to the base camp location as of January 1967. The defoliation portion of the program focused in three main regions, the north around the DMZ, near the Cambodian border in the Tay Ninh province and northeast of Saigon in the Long Khanh province (see Figure 7.8). The crop destruction component mainly targeted the north along the Laos border. Overall, not that many camps were directly under the herbicide flight paths.

Between January 1967 and December 1968, the herbicide campaign intensified as 3495 missions occurred in this time period, slightly more than half of all missions (see Figure 7.9).

The locations around the three main defoliation regions at the beginning of the period expanded during the period especially the region around Long Khanh. Now there was also a higher density of flights near the borders with Laos and Cambodia as the North Vietnamese had established base camps all along that stretch during the two year interval. Defoliation missions also grew in the region to the northeast of Saigon. The missions aimed at agricultural production (the green lines in Figure 7.9) were mostly in the edge of the forested interface region near the coast.

7.4 Point Pattern Analyses of Insurgency and Counterinsurgency Operations

These preliminary cartographic analyses of the spatial relationships suggest that as each side changed the locations of their battlescape elements, the other side acted in response. This section conducts several point pattern analyses to investigate further the back and forth nature of

154 the different operations. First, an analysis is conducted to determine if the locations of inoperative base camps is correlated with the flight paths. Second, a bivariate point pattern

Figure 7.8. Herbicide flight paths from July 1965 to January 1967 with respect to the location of North Vietnamese base camps in January 1967. Defoliation flight paths are in purple and agricultural destruction flight paths are in green.

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Figure 7.9. Herbicide flight paths from January 1967 to December 1968 with respect to the location of active North Vietnamese base camps in December 1968. Defoliation flight paths are in purple and agricultural destruction flight paths are in green.

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analysis is used to determine how correlated the locations of new base camps were to those that had been removed. Finally, a trivariate point pattern analysis is performed to examine how hamlet security was affected by these changes.

7.4.1 Impact of Flight Paths on Base Camp Deactivation

Because the herbicide program was designed as a counterinsurgency operation, with respect to the location of base camps, one measure of its success would be whether there was an association between the sprayed areas and the deactivation of these camps. To investigate this association, different statistical analyses were performed in which the camps that were deactivated are compared against the camps that were not during the period from January 1, 1967 to December 31, 1968. Base camps that were active sanctuaries in other countries were excluded because there were almost no flight paths outside of South Vietnam during this time period (see

Figure 7.9). There were 113 locations that had an active base camp during the timeframe of which 62 locations had a camp neutralized and 51 remained active.

In this analysis, the pattern of these base camps, both active and neutralized, is examined against a covariate which is represented as a surface representing distance to the nearest herbicide flight path.. The null model for this analysis treats the pattern of base camps as representing a sample of a cumulative distribution function of the covariate. If the covariate values found at the locations of points in the pattern are indeed random, then the cumulative distribution of the values at pattern locations would match that of the entire covariate surface

(Baddeley 2016). The SpatStat package in R (Baddeley et al. 2016) is used to conduct a spatial

Kolmogorov−Smirnov test of CSR, hereafter referred to as ‘KS’, based on the distribution of the covariate. The KS test measures the absolute distance between the sampled CDF and the

157 observed CDF using a value ‘D’. Based on the size of the sample the probability that the deviation is significant can be calculated. Given a surface of distances to a flight path, a cumulative density function (CDF) of expected distances for a random pattern is generated in a graph form. Figure 7.10 presents the CDF for a random pattern with respect to the distribution of distance values. Because flight paths are present in most parts of South Vietnam (see Figure

7.9) over the time period being investigated, the expected CDF is skewed towards shorter distances. The probability of any point being 60,000 to 80,000 meters from a flight path is far less than being between 0 and 20,000 meters at random.

Figure 7.10. Observed and expected cumulative density functions for all base camps given the covariate, distance to the nearest flight path. The observed CDF is more skewed than the expected CDF.

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The Kolmogorov-Smirnov test statistic is based on the maximum vertical separation between the graphs of 퐹̂(푧) (the observed CDF) and 퐹0(z) (the expected CDF) where (Baddeley et al. 2016):

퐷 = max|퐹̂(푧) − 퐹0(z)| (7.1) 푧

This discrepancy can be visualized in a plot of the expected CDF against the empirical

CDF. In Figure 7.10 the observed CDF for all base camps was more skewed than the expected

CDF implying that all base camps were closer to a flight path than what would be expected at random. The D value is significant to 0.0000535 meaning that there is less than six chances in

100,000 that the observed distribution was spatially random. Flight paths were targeting base camp locations.

Next, a spatial Kolmogorov-Smirnov test was done for the subset of base camps that continued operating and the subset of neutralized base camps, respectively. The distribution of base camps that continued operating had an observed CDF that was more skewed than expected

(Figure 7.11a) also but not as much as the CDF for all camps. Its D value had a probability of

0.0138 meaning that there was about a 1 in 100 chance that the pattern for active camps was spatially random. Similarly, the distribution of neutralized base camps had an observed CDF that was more skewed than expected (Figure 7.11b) but it was more skewed than the CDFs for all camps and active camps. Its D value had a probability of 0.0000231 meaning that there were about 2 chances in 100,000 that the pattern for neutralized camps was spatially random. This result suggests that overall there was a higher likelihood of deactivated base camps being closer to areas of herbicide operations than that of active camps, and that defoliation had some effectiveness in the overall strategy towards the neutralization of the enemy base areas during the conflict.

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Figure 7.11a. Observed and expected cumulative density functions for active base camps given the covariate, distance to the nearest flight path. The observed CDF is more skewed than the expected CDF.

Figure 7.11b. Observed and expected cumulative density functions for neutralized base camps given the covariate, distance to the nearest flight path. The observed CDF is more skewed than the expected CDF.

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7.4.2 The Pattern of the Insurgent Response to Base Camp Deactivation

As base camps were deactivated by the various counterinsurgency operations of the U.S. military and its allies, the North Vietnamese responded by reactivating previously neutralized sites or locating camps at new sites. As is the common practice in a war with no fronts, areas cleared of enemy forces were often reoccupied by those same enemy forces sometime after the location was vacated by the U.S. military. The expectation in this case is that if the original sites were preferred by the North Vietnamese, then attempts would be made to reassert their presence at or near these locations.

To test this hypothesis, a point pattern analysis is performed in which the locations that were deactivated are compared against the locations the North Vietnamese chose for reasserting control in local areas. Overall, 62 base camp locations that were once active became inactive during the study time period. During the same time period, the North Vietnamese added 33 camps. As mentioned, 18 times they chose the same locations as what previously existed, and 15 times they chose a completely new location. This resulted in a total of 95 total observations.

A bivariate point pattern analysis was run in Programita; this time the null model in the analysis holds the pattern of sites in which a camp was deactivated as fixed, while the pattern of sites where a camp was added is allowed to exhibit complete spatial randomness (CSR). The null model holds deactivated camp locations fixed because they represent an antecedent pattern whereas added camps are randomized because they could potentially have occurred anywhere in the study region. Because the study region is all of South Vietnam, the polygon boundary of

South Vietnam was used to ensure that random location of a base camp in a simulation would only occur with the South Vietnam polygon. An O-ring statistic was used measure the density of added camps at different distances from deactivated camps. The specific O-ring statistic used

161 was: n n O12(r) = 1/n ∑ i=1 Ni(r) / 1/n ∑i-1 vi (r) (7.2) where n is the number of points in antecedent pattern 1, Ni(r) is the number of points in pattern 2 that lie within the ring at distance r from the ith point in pattern 1, and vi is the area of a potentially incomplete ring at distance r for the ith point in pattern i. In this case it measured the density level between fixed pattern and the CSR pattern of added camps was calculated using a cell size of 2 kilometers for 199 simulations to determine the mean O-ring value, and the simulation envelopes corresponded to the fifth highest and lowest simulation values.

The O-ring statistic for the observed pattern was then compared against the simulated mean and envelopes (see Figure 7.12). If the North Vietnamese were choosing site locations patterns were similar to those that existed before, then one would expect the observed value to be either higher than the upper envelope. At longer distances, the observed statistic falls within the simulation envelope suggesting that the two patterns are not statistically different from one another. However, at shorter distances the observed value often lies above the upper envelope; the observed value is highest at zero distance (extends outside the graph), 0.371, far outside of the upper envelope value of 0.016. This is due to the high number of bases that were added at the same locations where a camp previously existed. The next section examines the likely reason for this strategy with respect to the control of the population.

Figure 7.12 The bivariate O-ring Statistic for the density of added camp locations (mark 2) pattern of sites at different distance rings with respect to deactivated camp locations (mark 1). Values above the upper envelope are greater than expected.

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7.4.3 The Relationship Between Hamlet Security and Base Camp Locations

Because one role of North Vietnamese base camps was to facilitate conversion of local populations to their cause, it is hypothesized that North Vietnamese base camps would have a greater density of VC controlled hamlets in their vicinity and a lower than expected density of

GVN secured hamlets in the same vicinity. To examine the relationship between hamlet security and base camp locations, an approach was used for what Weigand and Maloney (2014) call "data type five" information, which is a pattern for two point sets (base camps and hamlets) with a qualitative mark in the second point set (the secure category for hamlets). For data type five, one is investigating the impact of a focal pattern (the pattern of base camps), on the processes responsible for the distribution of marks in another pattern (the pattern of hamlet security categories).

The null model uses a trivariate random labelling process in which both the focal locations (base camps) and the location in the other point set (hamlets) are fixed, and the two marks for the second point set are randomly allocated in a simulation. The marked connection is the statistic used to measure the density of the mark in question at different distances from the focal points which are now the points in the fixed pattern. For this research question, one examines how the pattern of marks denoting the level of hamlet control was influenced by the presence of enemy base camps. In each case (VC controlled hamlets versus non-VC controlled hamlets, GVN secured hamlets versus non-GVN secured hamlets, and contested versus non- contested hamlets), the base camps serve as the set of focal points.

For each test, a total of 199 simulations are run, with the fifth highest and lowest simulations used to form an envelope of test statistic values corresponding to the null hypothesis.

The first run is for January 1967; in this run the 93 base camp locations are used as the

163 antecedent pattern, with hamlet locations as the second pattern. The hamlet marks under investigation indicate whether each hamlet is VC controlled versus non-VC controlled. Figure

7.13 shows that VC controlled hamlets are clustered up to a distance of 20 kilometers. Beyond that distance, more random behavior is found in the marked pattern. Next, the same analysis was conducted for a marked pattern of GVN secured versus non-secured hamlets. In this instance, the observed patterns of marked correlation shows a pattern of much less density than at random out to a distance of 16 kilometers from a base camp (Figure 7.14) suggesting that government secured hamlets are not likely to be clustered near enemy base area locations. The observed pattern beyond 16 kilometers is not different from random for government secured hamlets.

Finally, the pattern of contested versus non-contested hamlets are compared against base camp locations. It is expected the contested hamlets would not be different from a random pattern with respect to base camp locations because they are intermediate on the security scale. This is the pattern which is present in Figure 7.15. Overall, the location of enemy base camps appears to have had an impact on the level of hamlet security. This is one of the factors behind the spatial pattern of the spectrum of hamlet security observed in Chapter 6.

Figure 7.13 The marked connection function where enemy base camps in January 1967 are the antecedent pattern and VC controlled hamlets are mark 1 and non-VC controlled hamlets are mark 2.

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Figure 7.14 The marked connection function where enemy base camps in January 1967 are the antecedent pattern and GVN secured hamlets are mark 1 and non-GVN secured hamlets are mark 2.

Figure 7.15 The marked connection function where enemy base camps in January 1967 are the antecedent pattern and Contested hamlets are mark 1 and non-Contested hamlets are mark 2.

Over time, the Viet Cong and North Vietnamese were able to increase their yield in hamlets becoming VC controlled within the vicinity of their base camps (see Table 7.2). This partially offsets the herbicide flights and other counterinsurgency efforts by the U.S. military and its allies. Of particular interest are the two dates before and after the Tet offensive launched at the end of January 1968 and lasting through February of that year. At the end of Tet, the March

1968 values were the overall highest values across distances less than 18 kilometers. In the later months of 1968 but they were still higher than in early 1967 although they were only significant

165 to a distance of 14 kilometers. The Tet offensive was disruptive of insurgent forces, particularly for the Viet Cong, as much men and material was put into the offensive.

From the perspective of the counterinsurgency operations, the clustering of GVN secured hamlets declined over the two year period (see Table 7.3) as the enemy was able to increase its influence in local areas. In later 1968 the values were about one third of what they were in early

1967. However, the overall percentage of secure hamlets increased during this period as was documented in Chapter 6 and the number of hamlets within 20 kilometers of a base camp decreased from 5102 hamlets in January 1967 (red dots in Figure 7.16) to 3945 hamlets in

December 1968 (red dots in Figure 7.17). Efforts to eliminate base camps might have been a factor in this increase, mitigating the lower intensity in the vicinity of base camps.

These analyses illustrate that spatial organization of the insurgency is related to the distribution of the enemy base camps. The Viet Cong are more likely to control hamlets in the vicinity of a base camp while the government controlled hamlets are less likely to be found close to these areas and each side sought to limit or increase the access of the base camps to the hamlets. These analyses, however, only look at the structure of stock totals at different points in time. The issue of where and why hamlet security changed over time is examined in the next section.

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TABLE 7.2 Marked Connection Function Values for VC Controlled Hamlets With Respect to Base Camp Locationsa Distance (km) 01/1967 03/1967 06/1967 09/1967 12/1967 03/1968 06/1968 09/1968 12/1968

0 0.74419 0.79592 0.79546 0.80000 0.97059 0.97143 0.96667 0.88889 0.90323

2 0.69014 0.68056 0.70922 0.73077 0.81651 0.80734 0.81818 0.75926 0.75248

4 0.53759 0.57241 0.54118 0.56198 0.67429 0.71892 0.70808 0.66102 0.6527

8 0.44138 0.45434 0.43609 0.47478 0.48077 0.5704 0.54732 0.47692 0.50189

10 0.44463 0.48710 0.4518 0.44141 0.46782 0.55658 0.50677 0.44882 0.44385

12 0.45161 0.47240 0.41311 0.43243 0.43948 0.47754 0.44088 0.41245 0.38086

14 0.41310 0.40610 0.34127 0.34389 0.35174 0.42818 0.39970 0.35957 0.33501

16 0.36874 0.38217 0.33225 0.33964 0.31797 0.37401 0.35714 0.33333 0.31612

18 0.34087 0.34895 0.32282 0.33241 0.30489 0.34079 0.31109 0.29712 0.29493

20 0.35007 0.36292 0.33918 0.34469 0.30769 0.32203 0.29224 0.26564 0.26321

22 0.35113 0.34364 0.32982 0.32763 0.31658 0.33207 0.30164 0.29301 0.28493

a Values outside the simulation envelope are given in bold italics.

7.5 Temporal Changes in Hamlet Security

Time represents a key aspect in counterinsurgency warfare. As insurgent warfare is not a struggle for territory in the traditional meaning, conflict should not be thought of as revolving around a front but around control of population. In this effort, time plays a key role in deciding the outcomes in counterinsurgency operations. Sometimes, all that is required is for the insurgents to outlast the counterinsurgents in a strength of will instead of marshal prowess

(Trinquier 1964). The spatial/temporal change in hamlet security over time has only been

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TABLE 7.3 Marked Connection Function Values for GVN Secured Hamlets With Respect to Base Camp Locationsa Distance (km) 01/1967 03/1967 06/1967 09/1967 12/1967 03/1968 06/1968 09/1968 12/1968

0 0.18605 0.14286 0.15909 0.15000 0.02941 0.02857 0.03333 0.07407 0.05882

2 0.09155 0.09722 0.08511 0.08462 0.06422 0.05505 0.06061 0.09259 0.09346

4 0.18421 0.19655 0.19608 0.18182 0.13143 0.13514 0.14907 0.16384 0.14359

8 0.23218 0.24429 0.23058 0.21068 0.26923 0.23105 0.23868 0.21923 0.17628

10 0.26116 0.22903 0.22117 0.24023 0.23762 0.16859 0.1897 0.22572 0.17167

12 0.25677 0.2362 0.2622 0.21622 0.24395 0.22795 0.24449 0.27237 0.23974

14 0.26934 0.26087 0.29025 0.26638 0.29506 0.27236 0.28614 0.28858 0.25344

16 0.32309 0.30185 0.33333 0.30279 0.33215 0.31525 0.32957 0.31846 0.29524

18 0.35143 0.31772 0.34416 0.32318 0.36519 0.33546 0.36114 0.34812 0.30046

20 0.36611 0.35362 0.35923 0.34631 0.37063 0.35593 0.38257 0.38114 0.31652

22 0.36961 0.36683 0.38655 0.34882 0.35578 0.33587 0.35956 0.37240 0.31407

a Values outside the simulation envelope are in bold italics. examined indirectly thus far by examining hamlet security codes in a series of cross-sectional evaluations. The stock total of hamlets in each time period was not the same as some hamlets were added and some hamlets were removed from the totals over time. For this portion of the analysis, a longitudinal study will be restricted to only those hamlets that were reported as existing in January 1967 and were still reported there in December 1968. Hamlets could have been added through new construction or removed by destruction, or their absence could have been the result of improper reporting. In either case, to ascertain the effects of insurgent and counterinsurgent actions during the time period, only those hamlets that were in the databases over the entire time period are included in the next analysis. Of the 10,041 hamlets included in

January 1967 and the 10,649 hamlets in December 1968, 9,051 hamlets were in both datasets.

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Figure 7.16 Hamlets within 20 kilometers of an enemy base camp in January 1967. Hamlets in red are within 20 kilometers and hamlets in blue are more than 20 kilometers away.

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Figure 7.17 Hamlets within 20 kilometers of an enemy base camp in December 1968. Hamlets in red are within 20 kilometers and hamlets in blue are more than 20 kilometers away.

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Overall there was a high level of stability in the type of hamlet control. Of the 9,051 hamlets only 140 hamlet that were not under total VC control in 1967 became under VC control in December 1968. Similarly, only 304 hamlets under total VC control in January 1967 were not in this situation by December 1968. The remaining 8,607 remained the same over the time period. Another aspect of the change was the clustering of these hamlets. Many of the hamlets that switched from VC control to one of the two other categories (blue dots in Figure 7.18) were located in the southeastern part of Binh Dinh province with another grouping in the central highlands around Pleiku province. In contrast the largest cluster of hamlets that switched to VC control were in the Mekong Delta region to the southwest of Saigon.

7.5.1 Global Regression Analysis of Hamlet Security Change

Next, the longitudinal study brings together the factors of the forest, base camp locations and spraying missions in a regression analysis to explore their impact on changes in the structure of VC control of hamlets. For this analysis, South Vietnam was divided into a series of 450 squares that are 20 km x 20 km. The 20 km interval was chosen based on the results of the point pattern analyses because most of those results generally showed that beyond 20 km the patterns in spatial clustering (indicating lack of independence) were not significant. Each hamlet was then assigned to the square within which it was located (Figure 7.19). The percent of hamlets under VC control in January 1967 and the percent under VC control in December 1968 were then calculated for each square grid cell.

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Figure 7.18. Hamlets that switched with respect to VC control between January 1967 and December 1968. Hamlets in red switched to VC control and hamlets in blue switched away from VC control.

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Figure 7.19. A twenty kilometer square grid partition of South Vietnam. Hamlet locations are purple dots.

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The forest factor (PForest) was calculated as the percent of forested area within the total area of the entire square. The spray data factor (AFlyDen) was calculated as the average of all kernel density cell values within a given square; these kernel density cell values represent the density of all spray flights that occurred between January 1967 and December 1968. Finally, the distance from each hamlet within a given square to its nearest base camp was averaged for both

January 1967 and December 1968. The base camp factor (ABDDiff) was calculated as the average distance in December 1968 minus the average distance in January 1967.

Ordinary Least Squares Regression (OLS) was applied to these data as a first step in investigating the longitudinal analyses. To ensure that the change in security of only one or two hamlets would not create a wide shift in the percent of VC controlled hamlets in any square unit, only those units that had at least 30 hamlets were used as observations in the regression; this resulted in 112 observations generally concentrated in the Mekong River delta and along the central coast between Quang Tri and Cam Ranh Bay. The regression was run only using these

112 squares. The regression was run using ArcMap 10.4 using the OLS tool in the ArcMap toolbox. The change in VC controlled hamlets within a given square (PVCDiff) was the dependent variable, and AFlyDen, PForest, and ABDDiff were the independent variables.

It is hypothesized that the percent of hamlets that switched to being VC controlled would be inversely related to spray densities given the mission of Operation Ranch Hand and also inversely related to the change in the average distance to the nearest base camp because the purpose of these camps was to aid in control of the population. It is also hypothesized that percent forest would be directly related to the change in percent VC controlled as the forests were the domain of the insurgent forces.

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Overall, the OLS regression model did not have much explanatory power with a multiple

R-square of 0.11 and an adjusted R-square of 0.08. The results also suggest that the hypotheses were in fact incorrect as signs of the regression coefficients also were not as predicted. The signs of the regression coefficients for all three independent variables were opposite than what was hypothesized (Table 7.4). In addition, only the variable PForest had a significant relationship with the dependent variable. This was probably the result of the fact that a large portion of those hamlets that switched were located in the Mekong Delta region and this region was not heavily forested.

TABLE 7.4 Summary of OLS Results Variable Coefficient Std, Error t-statistic Probability Intercept -0.92596 1.80434 -0.513184 0.608876 AFlyDen 6.11232 6.42606 0.34363 0.34363 PForest -0.18896 0.05179 -3.64819 0.00042* ABDDiff 0.20180 0.13139 1.53586 0.12751 *Significant at the 0.05 level.

Figure 7.20 presents the spatial pattern of the standardized residuals. The clustering of low residuals values indicates that spatial autocorrelation may be present in the data. This visual interpretation was verified by calculating the Moran I measure of spatial autocorrelation. The

Moran I value was 0.268076 with a highly significant z-score of 6.8594. The parameter estimates for the OLS regression are thus inefficient because the random error terms are correlated. To correct for the presence of spatial autocorrelation in the error terms, a spatial errors regression was run using GeoDa 1.12. Spatial errors regression is used to obtain a more accurate statistical inference by including a spatial autoregressive factor, λ, in the error term. In this model, the signs of the parameters remained the same but none of the parameters was significant (Table 7.5). The residuals for this model had a Moran I’s value of 0.05687 which is not significant.

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Figure 7.20. Pattern of the standardized residuals for the OLS regression model. Grid cells with less than 30 hamlets are in light green.

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TABLE 7.5 Summary of Spatial Error Regression Results Variable Coefficient Std, Error z-value Probability Intercept -2.27945 2.67897 -0.850868 0.39484 AFlyDen 2.08152 7.60086 0.273854 0.78420 PForest -0.058888 0.060807 -0.671584 0.33283 ABDDiff 0.494844 0.103828 4.76601 0.50185

In addition to the presence of spatial dependency in the OLS regression, the Koenker statistic from the OLS regression that measures the model’s spatial stationarity was significant at the 0.01 level. Both OLS and spatial error regression are considered global regressions in the sense that the processes that generate the coefficient values are the same everywhere so the same coefficient value applies everywhere. The significant Koenker statistic indicates that this is not the case for the security change model. The relationships with the dependent variable expressed by the coefficients may not be consistent over space due to non-stationarity. This means that a local regression such as geographically weighted regression (GWR) can be used to examine how the coefficient values vary over space.

7.5.2 A GWR Analysis of Hamlet Security Change

A geographically weighted regression (GWR) analysis permits a local analysis in which changing relationships within the data over space can be better studied and visualized

(Fotheringham, Brunsdon and Charlton 2002). It also allows for the interpretation of each explanatory variable independently to understand how that variable changed spatially within the study region of the regression. In examining the nature of the relationships between the dependent variable and the explanatory variables, GWR is analyzing whether any of these relationships vary over space. It is important to know if changes in the values of the dependent variables from place to place are the result of corresponding changes in the explanatory variables for the same process or if the processes generating the dependent variable values are the results

177 of changes in the process from place to place. For this study, were changes in security status the result of differences in the levels of forest coverage, defoliation density, and distances to base camps, or were changes in security status from place to place the result of varying relationships with the three explanatory variables. OLS regression and spatial error regression both estimate one set of parameters to apply to all observations; whereas, GWR estimates a set of parameters focused on each observation; in that manner, the relationships between the dependent variable and the parameters of the explanatory variables can be studied for non-stationarity.

First, the intercept term is investigated (Figure 7.21); the intercept term expresses the base level of security switching not associated with any of the three factors. The intercept is negative in the central region of South Vietnam while in the North and South the coefficient is positive. These results are tempered by the fact that the standard error of the intercepts is larger than the intercept itself in most areas meaning implying the intercept may not be significantly different than zero in most locations (Figure 7.22). However, it is not appropriate to conduct individual significance tests on the local values as the local results are highly dependent; there is also a problem associated with doing multiple significance tests in that we would expect at any significance level some results would be significant at random. We can say that only in the central region of South Vietnam were the intercept values greater than the standard errors.

Security switching occurred in this region independent of the explanatory variables and was not in favor of VC control.

Figure 7.23 displays the spatial pattern of GWR coefficients for the ABDiff independent variable and associated standard error for that variable. Several patterns emerge. First, the standard error is rather large relative to the coefficients again meaning that many coefficient values are not significantly different than zero (Figure 7.24). However, there is a general trend

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Figure 7.21 The spatial pattern of the intercept term in the geographically weighted regression. Grid cells with less than 30 hamlets are in light green.

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Figure 7.22 The spatial pattern of the standard errors of the intercept term in the geographically weighted regression. Grid cells with less than 30 hamlets are in light green.

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Figure 7.23 The spatial pattern of the ABDDiff coefficient in the geographically weighted regression. Grid cells with less than 30 hamlets are in light green.

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Figure 7.24 The spatial pattern of the standard errors of the ABDDiff coefficient in the geographically weighted regression. Grid cells with less than 30 hamlets are in light green.

182 where in the area of the Mekong Delta and along the north coast of South Vietnam around the

Quang Tri-Da Nang Corridor, the variable is negatively associated with the hamlet control switching. However, in the central coast closer to Cam Ranh Bay, there is a positive association between the ABDiff and hamlet switching and the magnitude of the coefficient is greater than the associated standard error. This implies that the Viet Cong were not very successful in the central coastal region in the interaction between hamlet and the base camp locations.

Next, in Figure 7.25 the Quang-Tri Da-Nang corridor shows a negative relationship between forest cover and hamlet security while the Mekong Delta area and the central region show a positive relationship. This makes sense because in the Mekong Delta region, most of the

Viet Cong hamlets are not near any type of jungle or mangrove forest cover while in the central region increasing forest cover increased switching to VC control. The coefficients in the central region were also the only ones whose magnitude was greater than the associated standard error

(Figure 7.26).

Finally, Figure 7.27 displays the pattern in the relationship between herbicide flight density and hamlets switching to VC control. Here again, there is a difference between spray missions in the north versus those in the south. In the north, there is a positive association while in the south the association is negative, which was the expected relationship. Again, only those coefficients in the central highland region had magnitudes greater than the associated standard error (Figure 7.28).

Overall, there were distinct differences in the regional values for all of the parameters as the north, the central, and especially the south behaved in different manners. However, most of these relationships were still relatively weak. Only in the central region near the coast and in the interior were the relationships relatively strong.

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Figure 7.25. The spatial pattern of the PForest coefficient in the geographically weighted regression. Grid cells with less than 30 hamlets are in light green.

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Figure 7.26. The spatial pattern of the standard errors of the PForest coefficient in the geographically weighted regression. Grid cells with less than 30 hamlets are in light green.

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Figure 7.27 The spatial pattern of the AFlyDen coefficient in the geographically weighted regression. Grid cells with less than 30 hamlets are in light green.

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Figure 7.28 The spatial pattern of the standard errors of the AFlyDen coefficient in the geographically weighted regression. Grid cells with less than 30 hamlets are in light green.

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7.5 Conclusions

Insurgent and counterinsurgent operations continued back and forth during the war in

South Vietnam. Each side, however, had a different approach to the extensive jungle regions of the country. Because the U.S. military viewed the jungle as an obstacle to overcome whereas the

North Vietnamese and Viet Cong viewed the jungle as a protector, the two sides used the jungle in a very different manner. The ultimate goal was the control of the hamlet population and the different tactics seemed to act accordingly. Operation Ranch Hand in general avoided direct flights over the populated hamlet areas and focused much of defoliation flights on the areas of the country where supplies and troops could come in from external active sanctuary bases as well as in other jungle areas where there were enemy bases. Flights aimed at the destruction of agricultural production focused on the interface zone between the human settlement area and the jungle environment. The North Vietnamese also focused on this region in locating their base camps for training and supplying troops.

The layers of analysis illustrate a strong link between enemy base areas that were deactivated and proximity to defoliation tracks. Additionally, there is evidence that over the 24 month study period there was an increase in the ‘efficiency’ of the support of communist control by the remaining base locations. Such an increase in the efficiency would place a greater emphasis in the security of the lines of communication between hamlets and the base areas. This suggests that the herbicide program’s most important contribution was not the pure denial of cover for enemy base areas, but rather to destroy cover and concealment between the enemy base areas and the population centers.

The geography of the countryside helps support this hypothesis. For example, in the regression analysis section of this chapter, the only locations where jungle cover was correlated

188 with insurgent control was in Military Region 2. This region, covering the bulk of the central highlands with most of the population being concentrated in coastal enclaves formed by river valleys. The other military regions particularly Military Region 4 which contained a strong base of insurgent support had little jungle cover and therefore the level of insurgent control of the hamlets was not linked with the extent of jungle cover. The KS test illustrated that active base areas where further from spraying compared to deactivated locations, the O – Ring statistic highlights the increasing ‘deficiency’ of remaining enemy base areas near the end of the study period.

There was no statistical evidence that the herbicide program was successful in destroying enemy base camps and this program more likely had a supporting role in the other military operations that did destroy these camps. However, many camp locations were never permanently destroyed and the North Vietnamese returned later to their favored locations. The result of this see-saw was a slight reduction in the number of hamlets under VC control over the two year period from January 1967 to December 1968. However, the number of hamlets that actually changed their security status was actually very small compared to the total number of hamlets. Regression analyses also did not produce any conclusive evidence that the hypothesized factors behind the changes were significant. These results, combined with those from previous chapters, are summarized further in the next chapter.

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CHAPTER 8 – DISCUSSION OF RESULTS AND CONCLUSIONS

8.1 Geographical Warfare

In 1973, Yves Lacoste (1973) developed a concept known as “Geographical Warfare” to describe the bombing of dykes in the Red River Delta by U.S. forces. This article was an early example of geographic investigation into the Vietnam War. Although there is a relative paucity of studies in contemporary geographic literature, the defoliation campaign in South Vietnam has been extensively studied by contemporary environmental scientists (Brauer 2009). Also, despite the wealth of geographic data from the conflict, very few studies have explicitly examined the digital data from that era (Kalyvas and Kocher 2008). This study has specifically used data from that time period to better understand the spatial and temporal patterns in South Vietnam associated with these datasets. The datasets were developed during the conflict to assess the success of particular operations, and in the case of the Hamlet Evaluation System, the overall level of pacification in South Vietnam. This chapter will discuss the results of the analyses as they relate to the original research questions and then attempt to draw some more broadly based conclusions.

8.2 Characterizing the Jungle Environment

The results of the qualitative analysis of U.S. counterinsurgency field manuals from the era were not what was expected. Overall, the codes were sparsely contained within the text with

190 no more than on average 1.6 codes per paragraph in either text. The ‘jungle’ environment was not thoroughly discussed in either text. Instead, the text treated all areas as a larger ‘wilderness’ category. The terms “Jungle,” “Forest,” “Wilderness,” “Mountainous Area,” were all used to describe areas that were not heavily settled. The focus of understanding the landcover in counterinsurgency operations was mainly focused on the concepts of cover and concealment (i.e the ability to protect oneself from direct fire or the ability of a force to hide one’s movements and presence respectively). The connectivity of social units such as villages and towns to government infrastructure was also viewed as being weaker in these areas.

In either manual, there was no direct characterization of variation between potential environments; instead the field manuals attempted to discuss counterinsurgency operations from a theoretical standpoint to develop a situation that would be similar to actual circumstances faced during the deployment of troops to a foreign country, but not actually trying to describe the environment of an actual location. While this might be expedient from the standpoint of communicating information to troops in a training environment, these manuals undoubtedly required much translation to make them relevant to operations in a specific environment. Yet, in an analysis of the Vietnam Era derived datasets, the general layout of the theater of operations in

South Vietnam is markedly different from this hypothetical situation.

A second significant aspect of the qualitative analysis is that there is a difference in the focus of the counterinsurgency operations. In the 1940 field manual, there is a great amount of emphasis placed on developing some level of ‘connection’ with the environment and the population of the host country. The field manual is interested in describing how activities must be executed in certain settings which shows that there is an importance in engaging with the theater of operations and the local variations of that area. Conversely, the 1967 field manual is

191 structured to focus more on the actors during the counterinsurgency operations and by extension to focus on centralizing the force structure and maintaining its integrity throughout the operation.

This is markedly different from the 1940 field manual which pushes for a more dispersed and decentralized force structure in active operations.

There is also perhaps a more subtle difference in the two field manuals as well. Despite the 1940 field manual’s racist overtones, there is a strong respect for local knowledge of the indigenous population and even discussions of integrating these people directly into military formations. The rigidity between counterinsurgent unit types is not very great. Conversely, the

1967 field manual is focused on maintaining the integrity of the spectrum of units engaged in counterinsurgency operations. In some ways, this difference can be seen between the two successive eras of conflict in Southeast Asia. During the French period of the conflict, the fighting was done by units that had slowly evolved to being composed of units that maintained their strength from local recruitment.

Often times these mixed force units performed much better in dealing with enemy forces outside of their base areas (Croizat 1967). Conversely, within the American forces deployed to

Southeast Asia during the American Phase of the conflict, despite the presence of U.S. advisory forces at higher echelons of the ARVN (Army of the Republic of Vietnam), there was little attempt to enforce mixed troop units. This could perhaps be related to the colonial legacy of the military forces of the French Army, but it should be noted that the closer incorporation of local personnel into U.S. military formations deprived the U.S. military of local intelligence at the most basic level.

The 1940 manual provided a more comprehensive understanding of the roles of counterinsurgency warfare also at differing hierarchical levels. For example, the 1940 manual

192 would provide a discussion of activities that needed to be executed at the tactical level, but also at the operational and strategic levels. This is very different than the 1967 field manual which characterizes counterinsurgency operations from a purely operational perspective. This would suggest that in the perspective of the 1967 manual, counterinsurgency warfare differs most from conventional warfare at the operational level.

Also, as the 1967 manual focused directly on the role that bases and rear area installations had in supporting the deployed force, the doctrine specified that government forces be based in these installations. The growth of reliance on technology is another principle that emerges from an analysis of these two field manuals. In the 1940 manual, there is a heavy emphasis placed on foot patrols and river patrols. In the 1967 manual, particularly with respect to patrolling, there is a much greater emphasis on mobility beyond that of the foot patrol. Particularly with the growing presence of airpower, the 1967 field manual assumes complete technological superiority over the insurgent forces. Yet, if ‘human’ intelligence on the battlefield is key to victory and winning the ‘hearts and minds’ of the local population is essential to the outcome of the conflict, then relying on technology cannot be a panacea as hoped for by the Kennedy and later Johnson administrations (Buckingham 1982). Relying on air mobility provided an important solution to battlefield mobility but in effect partitioned U.S. forces from everywhere but the basecamp and the battlefield.

8.3 Characterizing the Spatial Structure of Hamlet Locations

The field manuals characterize the more remote sections of a hypothetical country as the areas most likely to support the base areas of an insurgency. However, as the distribution of hamlets in the database illustrate, the primary areas of communist insurgency are not in the

193 remote jungle areas. In fact, they are along the coastal plain and in the Mekong River deltas, the two most populous areas of South Vietnam. However, the base areas are in fact located in the jungle areas of South Vietnam excluding the area of the Mekong River delta.

The spatial structure of the political control of these hamlets was found to mirror the structure of the spectrum of political control itself. VC controlled hamlets were clustered together and were are less likely to be located near GVN secured hamlets than contested hamlets.

Likewise, GVN secured hamlets were also clustered together and were less likely to be near VC controlled hamlets. The contested hamlets formed a buffer zone in between these two political opposites. That spatial structure does not change over time. Also, overall in the 24 months of the study period, there was very little change in the overall numbers of insurgent hamlets as characterized by the data. HES data has been questioned as to its accuracy from a variety of sources because there is evidence that the quality of the data collection was sometime poor.

Nevertheless, this data was a key source in providing information from which to make decisions by the U.S. government.

As noted from a variety of sources (Buckingham 1982) the Vietnam War was executed using a variety of methods beyond traditional military intelligence. The hamlet data were used to create models to attempt to predict the spread of decline of the insurgency. Whether or not these data represent a true model of the reality on the ground, the data still formed part of the intelligence that was the basis for making decisions during the conflict. Therefore while there may be many errors inherent in the data, the data still present a very material reality from the standpoint of intelligence used to conduct operations.

194

8.4 Insurgency/Counterinsurgency Tactics

The North Vietnamese and Viet Cong relied heavily on a system of base camps for stockpiling supplies coming from sources such as the Ho Chi Minh Trail or Sihanouk trail or other locations within South Vietnam from which these supplies would then be redistributed to the insurgent agents operating throughout South Vietnam. These base camps included active sanctuary camps located just outside South Vietnam as well as base camps nearer to the focus of political and military operations. Over time the actives sanctuaries were relocated from locations in North Vietnam to location in Laos and Cambodia along the South Vietnam border to be closer to the main operations. Counterinsurgency operations, including a defoliation program, were focused on eliminating these bases and over the two year time period, there was a substantial reduction in the number of bases. However, there was no statistical evidence that the defoliation program by itself was successful in destroying enemy base camps; the Operation Ranch Hand program more likely had only a supporting role in the other military operations that did destroy these camps. However, as what often occurs in a war with no fronts, favored camp locations of the North Vietnamese were never permanently destroyed and the North Vietnamese returned later to these locations. These camps were very important in the struggle for control over the hamlet population as a point pattern analysis found that VC controlled hamlets were much nmore highly concentrated in areas nearer to these base camps than GVN secured hamlets were. The overall result of the tug-of-war over the base camps was only small reduction in the number of hamlets under VC control between January 1967 and December 1968.

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8.5 Longitudinal Analysis of Counterinsurgency Doctrine

Finally, a longitudinal analyses examined different aspects of counterinsurgency doctrine during this period. The longitudinal study was restricted to only those hamlets that existed both in January 1967 and in December 1968. Almost 90% of the hamlets that were reported in

January 1967 were also reported in December 1968. Of the more than 3,000 VC controlled hamlets in January 1967, only about 300 were converted to GVN secured by the end of 1968. al

VC control in January 1967 were not in this situation by December 1968.

An OLS regression, a global model, was used to study the impact of three factors – the level of forested cover, the density of defoliant spray flights, and the average distance to enemy base camps – on the change in the level of VC control. Overall, there were no significant relationships and the residuals in the explanatory variables were strongly auto-correlated. The results also suggested that there was evidence of spatial non-stationarity in the parameter estimates. This suggested that a local measure would more accurately explore the relationships among the variables. A geographically weighted regression showed that there was indeed local variation between the explanatory variables. This would show a fundamental error in the insurgency strategy by treating the insurgency from a global perspective. In some locations of the analysis region it appears that jungle cover is correlated with increases in the insurgency while in other locations namely the Mekong delta, the insurgency is not correlated with jungle cover because it did not exist there. What emerges from this analysis again ties back to the discussion of the spatial structure of the conflict. The conflict should not be viewed within the context of a country-wide insurgency, but instead should be viewed within the context of a series of interrelated insurgencies.

196

8.6 Conclusion

An important result from this dissertation is the notion that the insurgency in South

Vietnam was localized in some of its characteristics yet different in other aspects. Different regions have different environmental characteristics. In some regions the presence of jungle cover provided the insurgency with concealment, but in other areas, jungle cover was absent although the insurgency still had a strong presence. Yet, while the drivers might have been different throughout the country, the overarching spatial structure of the insurgency did not change. The spatial structure of hamlet security was quite uniform over the whole of South

Vietnam through the time period of the study. The uniformity also appears to be found in the counterinsurgency manuals as well. There appears to be a change from decentralizing military forces to engage at the local level to rely more on the centralization of the military forces in the

1967 manual. On the other hand, the GWR analysis demonstrated that the relationships between defoliation and the switching of hamlet control varied across South Vietnam. This conflict between centralization and decentralization as also been discussed with respect to the French conflict in Southeast Asia as well (Schrader 2015). What this analysis has shown is that despite the overall similarity of the structure of security throughout South Vietnam, the drivers of that security varied with respect to sub-regions.

This research also demonstrated the potential for using recent spatial-analytical methodologies to assess the impact of insurgency and counterinsurgency doctrines employed in the conflict. GIS techniques allows one to compile and geo-reference different historical datasets which can be then used by statistical methods such as point pattern analysis and GWR to ascertain the level of success of these operations with respect to the control of the hamlet population.

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APPENDICES

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APPENDIX A

THE CODE BOOK

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Code book

Category ACTORS Sub-Category Codes Description Enemy Main Force Unit of conventionally- Organization Unit trained, well-equipped uniformed combatants. Capable of operating anywhere in the theater of conflict (mobile) at all times of day (24 hours).

Regional Unit Unit that can engage heavily armed opponents in particular areas (limited mobility) during the daytime. Well-armed but lacking heavy support weapons. Used in conventional and non- conventional operations.

Guerilla Unit Unit of lightly-armed individuals often difficult to distinguish from civilians. Often use indirect weapons (i.e., booby traps, improvised explosives) and an array of small arms. Used at night and not generally engaged in set- piece battles.

Enemy Political Cadre Individuals attached to Organization military units or working as individuals to ensure the correct political discourse within units and to support unit morale. They also work with the civilian population to increase support for military units.

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Category ACTORS Sub-Category Codes Sub-Category Enemy Foreign Enemy Individual or constituted Organization Forces units of external militaries that support Insurgent forces.

Population Peasants Rural farmers living in agrarian areas.

Workers Urban waged laborers. Individuals working in factories or performing menial jobs.

Insurgent Individuals who support the Sympathizers insurgent organization directly or indirectly.

Government Individuals who support the Sympathizers government organization directly or indirectly.

Government Police Civilian law enforcement. Organization Not equipped to handle large-scale insurgency.

Auxiliary Para-military forces that are Forces more formalized and theoretically undergo more rigorous training than Police.

Regular National military forces Military formed to maintain the territorial integrity of a sovereign nation-state.

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Category ACTORS Sub-Category Codes Description Government Foreign Forces from a friendly Organization Government country that can be either in Forces an advisory capacity or engage as constituted units against enemy forces.

Category ACTIVITIES Sub-Category Codes Sub-Category Civilian Police Actions undertaken by Operations police to restore law and order against “civilian” populations.

Propaganda Operations designed to win the “hearts and minds” of non-combatants to support either government or insurgent forces.

Social Programs aimed at Economic improving the material Programs living standards of the civilian population. Used to undercut support for insurgent forces.

Military Outpost Establishing a fixed position from which to occupy or hold territory or vital areas.

Patrol Sending small units to conduct sweeps of areas to find insurgent forces.

Ambush Concealing forces to attack the enemy by surprise.

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Category ACTIVITIES Sub-Category Codes Sub-Category Counter- Similar in concept to patrol insurgency but conducted on a much Sweep larger spatial and temporal scale.

Gridding Aligning various social, environmental, military zones into unitary spatial divisions for counterinsurgency operations.

Grid Action First response to insurgent activity by units trained in methods to police and guard populated areas

Interval Action Using troops to destroy enemy forces in the intermediate area and conduct direct action against enemy forces.

Intervention Using elite formations to seek Action out enemy forces

Category GEOGRAPHIC SETTINGS Sub-Category Code Description Land Cover Urban Area Capital cities, cities, and related infrastructure Rural Area Towns, villages, and hamlets and the surrounding agricultural areas Wilderness Area Woods, jungles, and other unpopulated areas

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Category GEOGRAPHIC SETTINGS Sub-Category Code Description Point Base Point which sustains Geographic functioning of military Entities units or bodies of organized personnel. Population Location of settlements Center Transportation Any location that is at the Hub beginning or end of line of communication

Line Line of Network facilitating Geographic Communication movement of information, Entities people, logistics. More general than River and Road River Self-evident Road Self-evident

Area Hinterland Interior of country, often Geographic underdeveloped and Entities sparsely populated. May exist on inaccessible natural border with another country. Rear Area Zone behind front of operational forces. Country A generic term that applies to all nations. Theater of Term used to describe area Operation of active use of military forces. Zone Another term for a subdivision of a nation State A political entity controlling population within a given area that regulates the functioning of that population Territory A Subdivision of a Nation Nation A specific politico- territorial entity

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APPENDIX B

PAIRWISE MARKED CONNECTION FUNCTIONS DEFINING THE SPATIAL STRUCTURE OF HAMLET SECURITY PATTERNS, MARCH 1967 TO DECEMBER 1968

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The marked connection function for GVN secured hamlets with respect to other GVN secured hamlets with GVN secured hamlets as mark 1 and contested hamlets as mark 2 for March 1967

The marked connection function for contested hamlets with respect to other contested hamlets with GVN secured hamlets as mark 1 and contested hamlets as mark 2 for March 1967.

The mark connection function p12 for GVN secured and contested hamlets with GVN secured hamlets as mark 1 and contested hamlets as mark 2 where the GVN secured hamlets are the focal points for March 1967.

The difference in density function where GVN secured hamlets are mark1 and contested hamlets are mark 2 for March 1967.

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The marked connection function for VC controlled hamlets with respect to other VC controlled hamlets with VC controlled hamlets as mark 1 and contested hamlets as mark 2 for March 1967

The marked connection function for contested hamlets with respect to other contested hamlets with VC controlled hamlets as mark 1 and contested hamlets as mark 2 for March 1967.

The mark connection function p12 for VC controlled and contested hamlets with VC controlled hamlets as mark 1 and contested hamlets as mark 2 where the VC controlled hamlets are the focal points for March 1967.

The difference in density function where VC controlled hamlets are mark1 and contested hamlets are mark 2 for March 1967.

218

The marked connection function for VC controlled hamlets with respect to other VC controlled hamlets with VC controlled as mark 1 and GVN secured hamlets as mark 2 for March 1967

The marked connection function for GVN secured hamlets with respect to other GVN secured hamlets with VC controlled hamlets as mark 1 and GVN secured hamlets as mark 2 for March 1967.

The mark connection function p12 for VC controlled and GVN secured hamlets with VC controlled hamlets as mark 1 and GVN secured hamlets as mark 2 where the VC controlled hamlets are the focal points for March 1967.

The difference in density function where VC controlled are mark1 and GVN secured hamlets are mark 2 for March 1967.

219

The marked connection function for GVN secured hamlets with respect to other GVN secured hamlets with GVN secured hamlets as mark 1 and contested hamlets as mark 2 for June 1967

The marked connection function for contested hamlets with respect to other contested hamlets with GVN secured hamlets as mark 1 and contested hamlets as mark 2 for June 1967.

The difference in density function where GVN secured hamlets are mark1 and contested hamlets are mark 2 for June 1967.

220

The marked connection function for VC controlled hamlets with respect to other VC controlled hamlets with VC controlled hamlets as mark 1 and contested hamlets as mark 2 for June 1967

The marked connection function for contested hamlets with respect to other contested hamlets with VC controlled hamlets as mark 1 and contested hamlets as mark 2 for June 1967.

The difference in density function where VC controlled hamlets are mark1 and contested hamlets are mark 2 for June 1967.

221

The marked connection function for VC controlled hamlets with respect to other VC controlled hamlets with VC controlled as mark 1 and GVN secured hamlets as mark 2 for June 1967

The marked connection function for GVN secured hamlets with respect to other GVN secured hamlets with VC controlled hamlets as mark 1 and GVN secured hamlets as mark 2 for June 1967.

The difference in density function where VC controlled are mark1 and GVN secured hamlets are mark 2 for June 1967.

222

The marked connection function for GVN secured hamlets with respect to other GVN secured hamlets with GVN secured hamlets as mark 1 and contested hamlets as mark 2 for September 1967

The marked connection function for contested hamlets with respect to other contested hamlets with GVN secured hamlets as mark 1 and contested hamlets as mark 2 for September 1967.

The difference in density function where GVN secured hamlets are mark1 and contested hamlets are mark 2 for September 1967.

223

The marked connection function for VC controlled hamlets with respect to other VC controlled hamlets with VC controlled hamlets as mark 1 and contested hamlets as mark 2 for September 1967

The marked connection function for contested hamlets with respect to other contested hamlets with VC controlled hamlets as mark 1 and contested hamlets as mark 2 for September 1967.

The difference in density function where VC controlled hamlets are mark1 and contested hamlets are mark 2 for September 1967.

224

The marked connection function for VC controlled hamlets with respect to other VC controlled hamlets with VC controlled as mark 1 and GVN secured hamlets as mark 2 for September 1967

The marked connection function for GVN secured hamlets with respect to other GVN secured hamlets with VC controlled hamlets as mark 1 and GVN secured hamlets as mark 2 for September 1967.

The difference in density function where VC controlled are mark1 and GVN secured hamlets are mark 2 for September 1967.

225

The marked connection function for GVN secured hamlets with respect to other GVN secured hamlets with GVN secured hamlets as mark 1 and contested hamlets as mark 2 for December 1967

The marked connection function for contested hamlets with respect to other contested hamlets with GVN secured hamlets as mark 1 and contested hamlets as mark 2 for December 1967.

The difference in density function where GVN secured hamlets are mark1 and contested hamlets are mark 2 for December 1967.

226

The marked connection function for VC controlled hamlets with respect to other VC controlled hamlets with VC controlled hamlets as mark 1 and contested hamlets as mark 2 for December 1967

The marked connection function for contested hamlets with respect to other contested hamlets with VC controlled hamlets as mark 1 and contested hamlets as mark 2 for December 1967.

The difference in density function where VC controlled hamlets are mark1 and contested hamlets are mark 2 for December 1967.

227

The marked connection function for VC controlled hamlets with respect to other VC controlled hamlets with VC controlled as mark 1 and GVN secured hamlets as mark 2 for December 1967

The marked connection function for GVN secured hamlets with respect to other GVN secured hamlets with VC controlled hamlets as mark 1 and GVN secured hamlets as mark 2 for December 1967.

The difference in density function where VC controlled are mark1 and GVN secured hamlets are mark 2 for December 1967.

228

The marked connection function for GVN secured hamlets with respect to other GVN secured hamlets with GVN secured hamlets as mark 1 and contested hamlets as mark 2 for March 1968

The marked connection function for contested hamlets with respect to other contested hamlets with GVN secured hamlets as mark 1 and contested hamlets as mark 2 for March 1968.

The difference in density function where GVN hamlets are mark1 and contested hamlets are mark 2 for March 1968.

229

The marked connection function for VC controlled hamlets with respect to other VC controlled hamlets with VC controlled hamlets as mark 1 and contested hamlets as mark 2 for March 1968

The marked connection function for contested hamlets with respect to other contested hamlets with VC controlled hamlets as mark 1 and contested hamlets as mark 2 for March 1968.

The difference in density function where VC controlled are mark1 and contested hamlets are mark 2 for March 1968.

230

The marked connection function for VC controlled hamlets with respect to other VC controlled hamlets with VC controlled hamlets as mark 1 and GVN secured hamlets as mark 2 for March 1968

The marked connection function for GVN secured hamlets with respect to other GVN secured hamlets with VC controlled hamlets as mark 1 and GVN secured hamlets as mark 2 for March 1968.

The difference in density function where VC controlled are mark1 and GVN secured hamlets are mark 2 for March 1968.

231

The marked connection function for GVN secured hamlets with respect to other GVN secured hamlets with GVN secured hamlets as mark 1 and contested hamlets as mark 2 for June 1968

The marked connection function for contested hamlets with respect to other contested hamlets with GVN secured hamlets as mark 1 and contested hamlets as mark 2 for June 1968.

The difference in density function where GVN hamlets are mark1 and contested hamlets are mark 2 for June 1968.

232

The marked connection function for VC controlled hamlets with respect to other VC controlled hamlets with VC controlled hamlets as mark 1 and contested hamlets as mark 2 for June 1968

The marked connection function for contested hamlets with respect to other contested hamlets with VC controlled hamlets as mark 1 and contested hamlets as mark 2 for June 1968.

The difference in density function where VC controlled are mark1 and contested hamlets are mark 2 for June 1968.

233

The marked connection function for VC controlled hamlets with respect to other VC controlled hamlets with VC controlled hamlets as mark 1 and GVN secured hamlets as mark 2 for June 1968

The marked connection function for GVN secured hamlets with respect to other GVN secured hamlets with VC controlled hamlets as mark 1 and GVN secured hamlets as mark 2 for June 1968.

The difference in density function where VC controlled are mark1 and GVN secured hamlets are mark 2 for June 1968.

234

The marked connection function for GVN secured hamlets with respect to other GVN secured hamlets with GVN secured hamlets as mark 1 and contested hamlets as mark 2 for September 1968

The marked connection function for contested hamlets with respect to other contested hamlets with GVN secured hamlets as mark 1 and contested hamlets as mark 2 for September 1968.

The difference in density function where GVN hamlets are mark1 and contested hamlets are mark 2 for September 1968.

235

The marked connection function for VC controlled hamlets with respect to other VC controlled hamlets with VC controlled hamlets as mark 1 and contested hamlets as mark 2 for September 1968

The marked connection function for contested hamlets with respect to other contested hamlets with VC controlled hamlets as mark 1 and contested hamlets as mark 2 for September 1968.

The difference in density function where VC controlled are mark1 and contested hamlets are mark 2 for September 1968.

236

The marked connection function for VC controlled hamlets with respect to other VC controlled hamlets with VC controlled hamlets as mark 1 and GVN secured hamlets as mark 2 for September 1968

The marked connection function for GVN secured hamlets with respect to other GVN secured hamlets with VC controlled hamlets as mark 1 and GVN secured hamlets as mark 2 for September 1968.

The difference in density function where VC controlled are mark1 and GVN secured hamlets are mark 2 for September 1968.

237

The marked connection function for GVN secured hamlets with respect to other GVN secured hamlets with GVN secured hamlets as mark 1 and contested hamlets as mark 2 for December 1968

The marked connection function for contested hamlets with respect to other contested hamlets with GVN secured hamlets as mark 1 and contested hamlets as mark 2 for December 1968.

The difference in density function where GVN hamlets are mark1 and contested hamlets are mark 2 for December 1968.

238

The mark connection functions of VC controlled hamlets with respect to other VC controlled hamlets with contested hamlets as mark 2 for December 1968.

The marked connection function for contested hamlets with respect to other contested hamlets with VC controlled hamlets as mark 1 and contested hamlets as mark 2 for December 1968.

The difference in density functions where VC controlled are mark1 and contested hamlets are mark 2 for December 1968.

239

The mark connection functions of VC controlled hamlets with respect to other VC Controlled hamlets with VC controlled hamlets as mark 1 and GVN secured hamlets as mark 2 for December 1968.

The marked connection function for GVN secured hamlets with respect to other GVN secured hamlets with VC controlled hamlets as mark 1 and GVN secured hamlets as mark 2 for December 1968.

The difference in density functions where VC controlled are mark1 and GVN secured hamlets are mark 2 for December 1968.

240