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Quantifying Deforestation Rates in a Cocaine Source Region in Bolivia: a Study to Verify Rates of Land-Use Change Under Pro-Coca Policies

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Quantifying Deforestation Rates in a Cocaine Source Region in Bolivia: a Study to Verify Rates of Land-Use Change Under Pro-Coca Policies Quantifying deforestation rates in a cocaine source region in Bolivia: A study to verify rates of land-use change under pro-coca policies Thesis submitted by Edmond NAGOMBI (BSc, PNG UNITECH, BEng, PNG UNITECH) June 2017 For the degree of Masters of Science in GIS In the School of Environment, Faculty of Science and Engineering Flinders University, Adelaide, South Australia i Abstract This thesis focuses on humid tropical deforestation in one of the most important coca growing regions in central Bolivia, Chapare. On the one hand, the cultivation of coca leaves which is the source of cocaine paste, their processing and narcotrafficking are global, social and legal issues that lead to violence, corruption, and instability in foreign policy frameworks. On the other hand, their cultivation has local environmental and economic repercussions that are not always negative. The project is grounded in geospatial science and the methodology comprises of three main sections: image pre-processing, land-use and land-cover classification aimed at forest/non-forest mapping, and the generation of forest and non-forest statistics for individual farms in four communities in Chapare. Landsat 4 & 5 (TM) (2011) and Landsat 8 (OLI) satellite (2015 and 2016) image data were used. Pre- processing steps covered verification of geometric and radiometric parameters, image mosaicking and, for the 2015 data, pan sharpening. Thus, the images were classified using unsupervised classification to map major land-use and land-cover types from 2015 imagery. These were verified with reference to field data collected in 2015 that was made available to this research project. Forest and non-forest classification was carried out for the 2011, 2015 and 2016 image data. All geospatial analyses were done in ERDAS Imagine 2015 and ArcGIS version 10.4. The results of the three classified images for 2011, 2015 and 2016 shows overall accuracies of 84.51%, 87.84% and 98.42% respectively. Comparing the four different communities investigated in detail in the study area, the areas in the Community I and Community II shows regrowth of forest areas while areas in Community IV shows increased rate of deforestation. Community I with an average iii of 20 ha of land parcels and a standard deviation of 3 hectares has a current average regrowth rate of 204.73 ha/year which is 2 ha/year per farm at the end of the study period in 2016. Community II with mix grazing and farming land parcels indicated by its size of 50 ha (50 hectare land parcels are meant for pastures) have a regrowth of 786 ha/year which is 8.46 ha/year per farm in 2016. Community III and IV has a clearance rate of 25.18 ha/year which is 0.42 ha/year per farm and 79.56 ha/year which 1.99 ha/year per farm. However, there is 50% decrease in deforestation rate for the communities mapped in detail compared to statistics generated for the 1980s and 1990s. This is indicative of the Bolivian government’s pro-coca policies and legislation since they were first elected in 2006, and their increasing influence since c. 2000. The quantitative data reaffirms the hypothesis that weak anti-coca polices lead to less deforestation in Chapare. A key recommendation arising from the use of pan-sharpening technique used in this study shows improvement of the quality of the image and its spatial resolution in the 2015 classification discriminating individual forest degradation needs to explored. That is recommended as an advantage that must be employed on newly available sources of high spatial resolution imagery, to more accurately map and monitor fluctuations in the rates of deforestation in different communities and different farmers in each community under policies that either promote or discourage coca cultivation in future researches. iv Dedication I wish to dedicate this work to the memory of my late brother – Marceline Nagombi. 1 Thessalonians 4:17- “After that, we who are still alive and are left will be caught up together with them in the clouds to meet the Lord in the air. And so we will be with the Lord forever.” v Acknowledgment I sincerely would like to extend my acknowledgement to all the people who contributed in many ways directly or indirectly to make this thesis project a success. Firstly, I would like to take this time to thank the heavenly God for this gift of life. My acknowledgement to my wife, Michelle and the five children for their undivided support during my time of studies in Flinders University in these two years. My sincere gratitude to the Government of Australia for the prestigious scholarship (Australian Awards Scholarship) that funded my study program here in South Australia. It also cover the cost of managing our stay through our case manager Clare Muller. The help and support of the International Student Service is appreciated and acknowledged here in Flinders University. I sincerely acknowledge and appreciate the support and supervision of Professor Andrew Millington. He has been very instrumental in guiding me to put this paper together. With his vast experience, he has challenged and encouraged me to put up with this constructive analysis in this paper. I would like to thank Robert Keane, Andrew Millington and Steve Fildes for the GIS and Remote Sensing skills that is seen very helpful in carrying out my thesis project. My extended thank you to Dr Beverly Clarke for her time in coordinating the Master student’s research. Lastly my thank you and appreciation to the School of the Environment and Physical Science here in Flinders for the facility and software used. The Administrative staff in the school working behind the walls to make everything count and all the academic and technical support staff. vi Acronyms and abbreviations AOI Area Of Interest CDRP Cochabamba Regional Development Program; CONCADE Counter Narcotics Consolidation of Alternative Development Program CORDEP Chapare Regional Development Program EKC Environmental Kuznets Curve EU European Union FAO Food and Agricultural Organisation FCC False Colour Composite GCV Generalized Cross Validation GDP Gross Domestic Product GIS Geographical Information Systems GMO Genetically Modified Organism GNP Gross National Product GPS Global Positioning Systems IBTA Bolivian Institute of Agricultural Technology IPPC International Plant Protection Convention ISODATA Iterative Self-Organising Data Analysis Technique LAI Leaf Area Index Landsat TM Landsat Thematic Mapper Landsat ETM+ Landsat Enhanced Thematic Mapper Landsat OLI Landsat Operational Land Imager LEDAPS Landsat Ecosystem Disturbance Adaptive Processing System LULC Land Use & Land Cover LULCC Land Use Land Cover Change MAS Morales Movement to Socialism NDVI Normalised Difference Vegetation Index NEP New Economic Policy NIC Institute Nacional de Colonización NIR Near infrared PS Polar Stereographic RGB Red Green Blue vii ROC Receiver Operator Characteristics SW1 Short Wave 1 TIPNIS Isiboro Sécure Indigenous Territory and National Park USGS United States Geological Survey UN United Nations UNCED United Nations Conference on Environment and Development UNHCR United Nations High Commission for Refugees UNODC United Nations Office of Drug and Crime USA United States of America UTM Universal Transverse Mercator UK United Kingdom WGS World Geodetic System WRS Worldwide Reference System viii CONTENTS Title Page…………………………………………………………………………………….i Declaration…………………………………………………………………………………..ii Abstract……………………………………………………………………………………...iii Dedication……………………………………………………………………………………v Acknowledgment……………………………………………………………………………vi Acronyms and abbreviations………………………………………………………………vii Table of contents………………………………………………………………………..…..ix List of figures (in chapter sequence)……………………………………………………...xi List of tables (in chapter sequence)……………………………………………………...xiii Appendices…………………………………………………………………………………xiii TABLE OF CONTENTS 1 INTRODUCTION ................................................................................................. 1 1.1 Deforestation and Land-use .......................................................................... 1 1.2 Focus of this study ........................................................................................ 4 1.2.1 Agriculture and natural resources policies ................................................. 6 1.3 Aims and objectives ...................................................................................... 8 1.4 The research in a wider context .................................................................... 8 1.4.1 Environmental impacts ............................................................................... 9 1.4.2 Economic impacts .................................................................................... 10 1.4.3 Political and social impacts ...................................................................... 11 1.5 Thesis Structure .......................................................................................... 12 2 : DEFORESTATION AND ITS DRIVERS INCLUDING COCA IN CHAPARE ... 14 2.1 Coca and cocaine ....................................................................................... 14 2.2 Chapare ...................................................................................................... 16 2.2.1 Location and administrative divisions ....................................................... 16 2.2.2 Geology ................................................................................................... 18 2.2.3 Climate ....................................................................................................
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