On the Potential of Satellite Radar Interferometry for Monitoring Dikes of the Netherlands

Home , Flevopolder, Houtribdijk, Lauwersoog, Oosterscheldekering

“POSEIDON”

On the potential of satellite radar interferometry for monitoring dikes of the Netherlands

- a technical feasibility study -

17 November 2006

Frank Dentz Lidia van Halderen Boudewijn Possel Sami Samiei Esfahany Cornelis Slobbe Tom Wortel ii

POSEIDON, ﬁnal report 17 November 2006 Version

DISTRIBUTION LIST

Person Aﬃliation Dr.ir. R.F. Hanssen TU Delft/Tutor Dr.ir. M.J.P.M. Lemmens, Ir. F.J. van Leijen TU Delft/Project coaches TU Delft/Project Management

CHANGE RECORD

Issue Date Change Record Notes Main Author Reviewed by 1 September 27, 2006 Draft of the report Team Dr.ir. R.F. Hanssen Dr.ir. M.J.P.M. Lemmens Ir. F.J. van Leijen 2 November 3, 2006 Final report Team Dr.ir. R.F. Hanssen Dr.ir. M.J.P.M. Lemmens Ir. F.J. van Leijen 3 November 17, 2006 Final report Team -

Version 3.0

Final Report, GSP 2006 group 1

ISSUED BY

Delft University of Technology, Geomatics Faculty of Aerospace Engineering c/o Mrs. M.P.M. Scholtes Kluyverweg 1 2629 HS Delft phone: 015-2783546 email: [email protected]

iii iv CHAPTER 0. VERSION

POSEIDON, ﬁnal report 17 November 2006 Preface

This report is the product of nine weeks of research on the feasibility of the PS-InSAR technique for deformations monitoring of dikes. This research was part of the Geomatics Synthesis Project (GSP), which is a part of the 2nd year of the Geomatics master program of Delft University of Technology (DUT). The goal of this project is that students, in groups of 5-6 students, go through the whole chain of the geo-information process to get experience in geomatic project handling. The authors of this report all started their master study in September 2005, the same year as the start of the Geomatics program. In the ﬁrst half of 2006, the contours of this project became more clear. Especially, the eﬀorts of Mr. Tiberius and Mr. Hanssen have to be mentioned here. Due to their initiative the preparations accelerated, and the research topic was chosen.

Our thanks go out to everybody who has cooperated in establishing this report. In particular we would like to thank Mr. Hanssen, Mr. van Leijen and Mr. Lemmens for assisting and coaching us. A significant part of this research was the study to what can happen with a dike in terms of deformation. This research was only possible due to the close collaboration with several dike experts. We want to thank Mr. van Baars en Mr. Vrijling from the faculty of Civil Engineering from DUT, Mr. Van and Mr. van Duinen from GeoDelft and Mr. Van der Meer from Fugro. Also we would like to thank Mr. Perski for his technical support with the use of the GRASS software, Mrs. Ketelaar for her help in the interpretation of the data and Mr. van Zwieten for his support in working with LaTeX. The conducted case studies were performed with the use of different datasets we received from different organizations. Special acknowledgements go to the people who spent a lot of time in the retrieving or preparation of these datasets. Here we want to mention Mr. Ritter (Map Room of DUT), Mr. Vroonland (Adviesdienst Geo-informatie en ICT (AGI)), Mr. Landa (AGI), Mr. Boezeman (waterboard Zuiderzeeland), Mr. van Duinen (GeoDelft), Mrs. Man in ’t veld (Rijkswaterstaat Noord-Holland) and Mr. Nieuwenhuis (Rijkswaterstaat Noord-Holland).

During our ﬁeld trips, we received a lot of information about the local situation that gave us a lot of inspiration. Especially we would like to thank Mr. Oldenhof for his explanations during the trip to Kornwerderzand and Mr. Bos for his support at Marken.

Delft, 17 November 2006

v vi CHAPTER 0. PREFACE

POSEIDON, ﬁnal report 17 November 2006 Contents

Version iii

Preface v

Used abbreviations xi

Used symbols xiii

Glossary xv

Abstract xxiii

1 Introduction 1 1.1 Purpose statement ...... 2 1.2 Research methodology ...... 3 1.3 Boundary conditions ...... 3 1.4 Structure of the report ...... 4

2 Dikes, deformation and monitoring 5 2.1 Water barriers ...... 5 2.1.1 Categories of water barriers ...... 5 2.1.2 Types of water barriers ...... 7 2.1.3 Structure of a dike ...... 8 2.2 Description of deformation mechanisms ...... 9 2.3 Legal context of dike monitoring ...... 14 2.3.1 Responsibility of dike monitoring ...... 15 2.3.2 Legal issues using InSAR for dike monitoring ...... 15 2.4 Conventional guidelines for dike monitoring ...... 15 2.4.1 Height inspection ...... 15 2.4.2 Stability inspection ...... 17 2.5 Dike monitoring in practice ...... 18 2.5.1 Used measurement techniques for dike monitoring ...... 19

vii viii CONTENTS

3 Deformation monitoring with radar interferometry 21 3.1 Introduction to InSAR ...... 21 3.2 Conventional InSAR ...... 22 3.2.1 Basic idea ...... 22 3.2.2 Main interferometric parameters ...... 23 3.2.3 Main limitations of conventional InSAR ...... 25 3.3 Persistent Scatterer InSAR ...... 26 3.3.1 Concept of PS-InSAR ...... 26 3.3.2 Main issues in interpretation of PS-InSAR results ...... 27

4 Estimation of dike deformation parameters 31 4.1 Detection of deformation mechanisms with PS-InSAR ...... 31 4.1.1 Discussion of detectability of deformation mechanisms ...... 31 4.1.2 Superposition of deformation mechanisms ...... 33 4.2 Forward modeling ...... 34 4.2.1 General considerations about forward modeling ...... 34 4.2.2 General input parameters ...... 34 4.2.3 Modeling of deformation mechanisms ...... 35 4.3 Inverse modeling ...... 39

5 Case study methodology 45 5.1 The choice of the case study locations ...... 45 5.2 Data gathering ...... 46 5.3 Preparation of the data ...... 46 5.3.1 Georeferencing ...... 47 5.3.2 Selection of the reference point ...... 47 5.4 Time series analysis ...... 47 5.5 Detection of deformation ...... 48 5.6 Classiﬁcation of deformation ...... 49 5.7 Quality assessment ...... 51 5.7.1 Internal precision ...... 52 5.7.2 External precision ...... 52 5.7.3 Global Overall Model test ...... 53 5.8 Feasibility ...... 53

6 Case studies 55 6.1 Introduction ...... 55 6.2 Case study Harlingen ...... 55 6.2.1 Detection of deformation ...... 55

POSEIDON, ﬁnal report 17 November 2006 CONTENTS ix

6.2.2 Quality assessment ...... 57 6.2.3 The number of Persistent Scatterers ...... 58 6.2.4 Summary of results ...... 59 6.3 Case study Kornwerderzand ...... 59 6.3.1 Detection of deformation ...... 60 6.3.2 Quality assessment ...... 61 6.3.3 Summary of results ...... 62 6.4 Case study Marken ...... 62 6.4.1 Detection of deformation ...... 63 6.4.2 Time series analysis ...... 63 6.4.3 Estimation of deformation parameters ...... 63 6.4.4 Classiﬁcation ...... 64 6.4.5 Quality assessment ...... 65 6.4.6 Summary of results ...... 66 6.5 Case study Noordoostpolder ...... 67 6.5.1 Detection of deformation ...... 67 6.5.2 Time series analysis ...... 68 6.5.3 Estimation of deformation parameters ...... 69 6.5.4 Classiﬁcation ...... 70 6.5.5 Quality assessment ...... 71 6.5.6 The number of Persistent Scatterers ...... 72 6.5.7 Summary of results ...... 74

7 Conclusions and recommendations 75 7.1 Answer on main research question ...... 75 7.2 Conclusions ...... 75 7.2.1 Characteristics of dikes ...... 75 7.2.2 Detection and identiﬁcation ...... 76 7.2.3 Quality assessment ...... 76 7.2.4 PS-InSAR with respect to the needs ...... 77 7.3 Recommendations for further research ...... 78

A List of used datasets 79

B Background information Harlingen 83

C Background information Kornwerderzand 89

D Background information Marken 95

E Background information Noordoostpolder 101

POSEIDON, ﬁnal report 17 November 2006 x CONTENTS

F Color images 111

Bibliography 119

POSEIDON, ﬁnal report 17 November 2006 Used abbreviations

AGI Adviesdienst Geoinformatie en ITC (RWS department of geoinformation and ICT) AHN Actueel Hoogtebestand Nederland, current elevation model of the Netherlands DTB Digitaal Topografisch Bestand, digital topographical files DUT Delft University of Technology ERS European Remote-Sensing Satellite FliMap Fast Laser Imaging – Mapping and Profiling GIS Geographic Information System GOM Global Overall Model test GPS Global Positioning System GPR Ground Penetrating Radar GRASS Geographic Recourses Analysis Support System, Gis-program GSP Geomatics Synthesis Project InSAR Interferometric SAR LiDAR Light Detection And Ranging LOS Line of sight MRM Multi Reflectivity Map NAP Normaal Amsterdams Peil, Dutch reference surface POSEIDON Potential of satellite radar interferometry for monitoring dikes of the Netherlands PS Persistent Scatterer PS-InSAR Persistent Scatterer InSAR RADAR RAdio Detection And Ranging RD RijksDriehoeksmeting, Dutch national grid RTK Real Time Kinematic RWS RijksWaterStaat (directorate general of public works and water management) SAR Synthetic Aperture RADAR Top10vector The topographic vector map on scale 1:10000

xi xii CHAPTER 0. USED ABBREVIATIONS

POSEIDON, ﬁnal report 17 November 2006 Used symbols

α The distance to the dike’s length axis αh Heading of the satellite (azimuth) αha Heading of ascending orbit αhd Heading of descending orbit γ The slope of the dike γa Azimuth of lenght axis of dike θ Incidence angle λ Radar wavelength λnc Non-centrality parameter 2 σvˆ The variances of the estimated deformation rates φatmo Phase shift due to atmosphere φdefo Phase shift due to deformation φnoise Phase shift due to noise φscat Phase shift due to a change in the scatter characteristics of the resolution cell φtopo Topographic phase φ∆H The diﬀerential phase dasc Observed deformation in ascending track ddesc Observed deformation in descending track de The projection of the 3D deformation vector in east direction dinner slope The deformation magnitude of the inner slope dn The projection of the 3D deformation vector in north direction douter slope The deformation magnitude of the outer slope dr Deformation vector in LOS component dtop The deformation magnitude of the top of the dike du The projection of the 3D deformation vector in up direction dx deformation perpendicular to the lenght direction of dikes dy deformation in the lenght direction of dikes dz The vertical deformation dz base The deformation of the foot of the dike in vertical direction dz foreland The uplift of the foreland dz sub The deformation of the top of the dike in z-direction dx top The deformation of the crest of the dike in horizontal direction dz top The deformation of the crest of the dike in the vertical direction dSlope The deformation vector parallel to the slope eˆ Estimated residual vector h The crest height of the dike k The unknown integer number of full phase cycles l The base width of the dike x Vector of unknown parameters xˆ BLUE of the unknown parameters ti Time epoch i vˆ The estimated deformation rates y Vector of observations A Model of observation equations

xiii xiv CHAPTER 0. USED SYMBOLS

B⊥ Perpendicular baseline (distance between the satellites) D Deformation in the radar LOS ∆H the topographic phase residual H Height above the reference frame Ha Alternative hypothesis H0 Null hypothesis Im Identity matrix of size m Qxˆxˆ Variance-covariance matrix of the BLUE Qyˆyˆ The variance-covariance matrix of the estimated observations Qyy Variance-covariance matrix of observations R Slant range from the master platform to the earth surface T q GOM test statistic Y North direction X East direction Z Up direction

POSEIDON, ﬁnal report 17 November 2006 Glossary

Ascending (orbit) The satellite moves in upwards direction (south-north). Autonomous movement A PS-InSAR measurement that is not related to the expected deformation mechanism. Boulder clay Kind of clay, more stiff and tough than normal clay. Collar mattress Geotextile with on top mats of willow branches, used for protection against erosion of a bank (’kraagstuk’ in Dutch). Corner reflector A retroreflector consisting of three mutually perpendicular, intersect- ing flat surfaces, which reflects electromagnetic waves back towards the source Crest height The highest point of a dike (’kruinhoogte’ in Dutch). Descending (orbit) The satellite moves in downwards direction (north-south). Dike-ring area An area fully enclosed by water barriers Embankment Wall that protect and hold the bank (’kade’ in Dutch). High grounds Areas which are sufficiently high and broad to stop outside water. Isolated points PS points with no sidelobes and no other PSs in its surrounding. Non-primary water barriers Secondary barriers, protect against flooding by small water systems. Outlier PSs that contain only noise. Persistent Scatterer (PS) Point with constant backscatter characteristics in time. Pilings Foundation piles of a building, to protect the building against subsidence (’heipalen’ in Dutch). Primary water barriers Barriers that protect against flooding by the see, large rivers or large lakes. Protective cover Layer of stones or asphalt that protect the outer slope of a dike against erosion. Reference point A point within the study area to which all deformation measurements are relative. Resolution cell Radar pixel on the ground. Sidelobe Neighbouring pixel of a PS, which is also detected as PS due to the sinc pattern of the reflected radar wave. Storage basin Water basin in which polder water is drained (’boezem’ in Dutch). tolerable water discharge Maximum amount over water that may come over the dike, which a pumping station can handle (’overslagdebiet’ in Dutch). Water barrier Constructions that prevent the land behind it from flooding.

xv xvi CHAPTER 0. GLOSSARY

POSEIDON, ﬁnal report 17 November 2006 List of Figures

1.1 Potential coastline of the Netherlands without dikes ...... 2

2.1 Primary water barriers in the Netherlands ...... 6 2.2 The main types of water barriers ...... 8 2.3 Schematical drawing of a dike ...... 9 2.4 Overview of deformation mechanisms ...... 10 2.5 Schematical overview of height testing procedure...... 16 2.6 Crumbling of basaltic stones ...... 18 2.7 The FliMap system ...... 19

3.1 Phase measurement ...... 22 3.2 Interferogram of Bam ...... 23 3.3 Diﬀerent scattering resolution cell ...... 27 3.4 Example of time series ...... 28 3.5 Possible deformation for buildings ...... 29 3.6 Autonomous movement due to settlement ...... 30

4.1 A dike body’s cross-section of the used model...... 34 4.2 Geometry of incidence angle ...... 35 4.3 Model of a deformation due to sliding...... 36 4.4 The decomposition of the deformation vector...... 36 4.5 Model of a deformation due to sliding of the inner slope...... 36 4.6 Model of a deformation due to sliding of the outer slope of the dike...... 37 4.7 Model of a deformation due to seepage...... 37 4.8 Model of a deformation due to sliding of the protective cover...... 37 4.9 Model of a deformation due to horizontal deformation...... 38 4.10 Model of a deformation due to settlement...... 38 4.11 Model of a deformation due to subsidence...... 38 4.12 Model of a deformation due to swelling...... 39 4.13 The observation geometry ...... 40 4.14 Dike coordinate system ...... 40

xvii xviii LIST OF FIGURES

4.15 Deformation components ...... 41 4.16 Sensitivity (standard deviation in mm) of estimated deformation parameters to the dike orientation ...... 44

5.1 Linear model vs. alternative models...... 48 5.2 Other possibilities for phase unwrapping...... 49 5.3 Decision tree for deformation detection...... 50 5.4 Characteristics of deformation mechanisms...... 50 5.5 Decision tree deformation classiﬁcation: two observations ...... 51 5.6 Decision tree deformation classiﬁcation: one observation ...... 51

6.1 Deformation rate in ascending track ...... 56 6.2 Deformation rate in descending track ...... 56 6.3 Shifted deformation rate in ascending track ...... 56 6.4 Shifted deformation rate in descending track ...... 56 6.5 Estimated absolute subsidence due to salt mining ...... 57 6.6 Example of time series in subsidence bowl ...... 58 6.7 Division of dikes in straight segments ...... 59 6.8 Relation points and dike orientation w.r.t. the satellite’s orbit ...... 60 6.9 Time series Marken ...... 64 6.10 PS-INSAR and leveling comparison ...... 66 6.11 Some time series for Case A...... 68 6.12 Alternative time series for Case A...... 69 6.13 Some time series for Case B...... 70 6.14 Some time series for Case C...... 71 6.15 Division of dikes in straight segments...... 73 6.16 Relation points and dike orientation w.r.t. the satellite’s orbit ...... 74

A.1 Example radar data ...... 80 A.2 Example top10vector ...... 80 A.3 Example DTB-wet ...... 80 A.4 Example lenght proﬁle ...... 80 A.5 Example AHN ...... 81 A.6 Example geotechnical proﬁle ...... 81 A.7 Example soil map 1:50000 ...... 81 A.8 Example aerial photograph ...... 81

C.1 Location of Kornwerderzand ...... 89 C.2 Aerial overview of Kornwerderzand ...... 89 C.3 Construction of the Afsluitdijk ...... 90

POSEIDON, ﬁnal report 17 November 2006 LIST OF FIGURES xix

C.4 Histogram of deformation rates of the whole dataset, ascending track ...... 92 C.5 Histogram of deformation rates of the whole dataset, descending track ...... 92 C.6 Histogram of deformation rates of Kornwerderzand, ascending track ...... 92 C.7 Histogram of deformation rates of Kornwerderzand, descending track ...... 92

D.1 Location of Marken ...... 96 D.2 Old map of Marken ...... 96 D.3 Schematical cross-section of the ring dike of Marken ...... 97 D.4 northern part of ring dike Marken ...... 97 D.5 Deformation protective cover ...... 97

E.1 The Zuiderzee Works ...... 102 E.2 The locations where ground improvements are carried out ...... 102 E.3 Cross-section of the dike from 1956 ...... 103 E.4 Locations with new sheet piling in 1992 ...... 104 E.5 The windmills near the IJsselmeer dikes in the Noordoostpolder ...... 108 F.1 Example of overﬂowing ...... 111 F.2 Example of wave overtopping ...... 111 F.3 Example of nipping ice ...... 111 F.4 Example of piping ...... 111 F.5 Example of plastic horizontal sliding ...... 111 F.6 Example of sliding of the inner slop ...... 111 F.7 Persistent Scatterers in the area of Harlingen ...... 112 F.8 Radar data Harlingen ...... 112 F.9 Overall Model Test results in ascending track ...... 112 F.10 Overall Model Test results in descending track ...... 112 F.11 Standard deviation of residuals from linear model, ascending track ...... 112 F.12 Standard deviation of residuals from linear model, descending track ...... 112 F.13 Interesting areas at Kornwerderzand ...... 113 F.14 Zoom in on area of the bridge ...... 113 F.15 Side of the bridge ...... 113 F.16 Visible deformation cracks ...... 113 F.17 Zoom in on sluice area ...... 113 F.18 Overview of the North dike ...... 113 F.19 Overall Model Test results for ascending track ...... 114 F.20 Overall Model Test results for descending track ...... 114 F.21 Standard deviation of residuals from linear model ascending track ...... 114 F.22 Standard deviation of residuals from linear model descending track ...... 114 F.23 Rejected points in OMT are represented in black ...... 114

POSEIDON, ﬁnal report 17 November 2006 xx LIST OF FIGURES

F.24 Accepted measurements ...... 114 F.25 Locations PS-InSAR points Marken ...... 115 F.26 Persistent scatter locations case study Marken ...... 115 F.27 GOM for ascending data Marken ...... 115 F.28 GOM for descending data Marken ...... 115 F.29 Standard deviation of residuals for ascending data Marken ...... 115 F.30 Standard deviation of residuals for descending data Marken ...... 115 F.31 Locations measurements Marken RWS ...... 116 F.32 Leveling results measurements Marken RWS ...... 116 F.33 GPS results measurements Marken RWS ...... 116 F.34 The results of the detection step...... 116 F.35 The two groups of PSs for Case B...... 116 F.36 The results of the Overall Model Test...... 116 F.37 Overview of datasets ...... 117 F.38 Overview of radar data ...... 117 F.39 Overview of normalized dataset ...... 117 F.40 Normalized dataset in Matlab ...... 117 F.41 Overview of the dikes and their deformation rates from PS-InSAR...... 117

POSEIDON, ﬁnal report 17 November 2006 List of Tables

2.1 Deformation mechanisms ...... 11

4.1 Deformation mechanisms potentially detectable with PS-InSAR...... 32

6.1 The number of PSs for ascending orbit ...... 58 6.2 The number of PSs for descending orbit ...... 59 6.3 Overview vertical deformation Marken ...... 64 6.4 Overview radar and leveling measurements ...... 66 6.5 The external precision of the estimated deformation parameters ...... 71 6.6 The number of PSs for ascending orbit ...... 73 6.7 The number of PSs for descending orbit ...... 74

B.1 Ascending data track 258 ...... 84 B.2 Descending data track 151 ...... 85 B.2 Descending data track 151 ...... 86 B.2 Descending data track 151 ...... 87 B.3 Shift diﬀerences in meters ...... 88 B.4 Standard deviation in meters ...... 88

C.1 Shift diﬀerences ...... 91 C.2 Mean deformation...... 92

D.1 Characteristics PS-InSAR datasets Marken...... 99 D.2 Correction values georeferencing Marken ...... 99

E.1 Overview of the used datasets ...... 105 E.2 Ascending data track 029 ...... 106 E.3 Descending data track 151 ...... 107 E.4 Results of the georeferencing ...... 109

xxi xxii LIST OF TABLES

POSEIDON, ﬁnal report 17 November 2006 Abstract

Dike monitoring is an indispensable issue in countries like the Netherlands. The largest part of the Dutch population lives on land reclaimed from the sea and most of the gross national product is earned in these vulnerable areas. This implies that the continuous monitoring of dike deformation and strength with reliable technology is vital for the Netherlands. Satellite radar interferometry is currently recognized as an eﬃcient method for the detection and monitoring of surface deformation such as subsidence.

The purpose of the POSEIDON project is to explore the potential of deformation monitoring of water barriers in the Netherlands with the satellite Interferometric Synthetic Aperture Radar (InSAR) technique.

In this report, diﬀerent kinds of water barriers in the Netherlands are presented and various deformation and failure mechanisms of dikes and their eﬀects are studied. Also the necessity of dike monitoring is discussed, and the procedure of dike monitoring that is used in practice is described.

This report also reviews the basic concepts of the Persistent Scatter InSAR technique, the more advanced interferometric technique that is used in this project. The main issues in the interpretation of the PS-InSAR measurements are explained. Furthermore, it describes which kinds of deformation can be detected with the PS-InSAR technique. Inverse and forward modeling are studied to derive the deformation parameters.

To be able to decide about the technical feasibility of PS-InSAR for dike monitoring, a methodology is developed. It includes detection of deformation, time-series analysis, estimation of deformation parameters, classification of detected deformation, and finally quality assessment of the results. This methodology is applied in four different case studies in the Netherlands, namely Harlingen, Kornwerderzand, Marken and the Noordoostpolder.

The results of the case studies conﬁrm that this technique is technically feasible for dike deformation monitoring, especially as indicator method. In particular, it shows good performance for deformation detection on dikes which have rock ﬁll on their slopes.

xxiii xxiv CHAPTER 0. ABSTRACT

POSEIDON, ﬁnal report 17 November 2006 Chapter 1

Introduction

The Netherlands is a country which largely consists of reclaimed land. Only because of a large amount of infrastructural water defense objects (dikes, dams, storm-surge barriers, etc.) it is possible to keep the areas situated below sea level dry. This can be seen in Figure 1.1 where the situation is sketched of the Netherlands without water barriers.

“Most of the Netherlands’ 16 million people live on land reclaimed from the sea, and 70 percent of the gross national product is earned in these vulnerable areas. Therefore, the safety of the water barriers is of paramount importance to maintain the balance in the Dutch society. Failure can have catastrophic humanitarian and socio-economic consequences, as we have seen from the ﬂooding in Zeeland (31/1/1953) when dikes breached at 400 locations and 1800 people died. In the 1990s, climate change and increased rainfall in central Europe led to ﬂooding of the Rhine and Meuse rivers in the Netherlands. More recently, dike failures as in Wilnis (26/8/2003), Terbregge (1/9/2003), and Stein (27/1/2004) have shown that knowledge of failure mechanisms should be improved, and that the regular inspections of primary and secondary water barriers failed to detect hazardous areas. After August 2005, when the hurricane Katrina hit the southwestern coast of the USA and caused breaching of the levees along New Orleans’ 17th Street and London Street canals and the city was inundated, it created a new sense of urgency for the Netherlands to review its safety levels. ”Could this happen here?” was a question frequently posed. Many governmental and research organizations are currently addressing this question” [39].

Proper dike monitoring and maintenance can be a big step in the prevention of ﬂooding in the Netherlands. A technique which might be appropriate for this intensive monitoring is the PS-InSAR technique. This is the technique whose potential will be explored in this research.

There are a number of interesting characteristics of the PS-InSAR technique which lead to the choice of researching the potential of this technique for monitoring of the dikes of the Netherlands. The most important factor is the accuracy potential, which is at sub-millimeter level due to the small wavelength of the radar. This accuracy alone is not enough to make it better than existing measurement techniques; leveling has the same or maybe even a better accuracy potential. The revisit period and the involved costs are, in combination with the accuracy potential, unique for the PS-InSAR technique. The satellite passes over every area about once in 35 days, so each 35 days a difference measurement can take place. The costs can probably be relatively low since there are no field campaigns necessary to gather the data. Another striking factor which makes the use of PS-InSAR favourable especially for the monitoring of dikes is that dikes contain a lot of Persistent Scatterers. This is mostly due to the protective cover of the toe of most dikes which mainly consists of large basaltic rocks. In between these rocks are open spaces which lead to very good reflections.

1 2 CHAPTER 1. INTRODUCTION

Figure 1.1: Potential coastline of the Netherlands without dikes [5]

1.1 Purpose statement

The purpose statement can be divided into three separate parts. The ﬁrst part is the statement of work. This part describes the assignment of the project, with some boundary conditions. The project objective follows, this is the direct assignment from the project guide. The third part is the main research question, divided into 4 sub-questions.

Statement of work: Explore the potential of detecting and monitoring deformation of water barriers in the Netherlands with satellite SAR Interferometric data carried out by 6 students during an 8 week period, leading to a report of the ﬁndings. Project objective: “Perform an analysis, based on satellite synthetic aperture radar interferometric data, to detect and monitor deformation of water barriers in the Netherlands and give an interpretation of the results. A combination of various sources of geo-information, as well as expert knowledge should lead to a well-balanced evaluation of the potential of the technique.” [39] Main research question: Is the PS-InSAR technique feasible for dike (deformation) monitoring in the Nether- lands from a technical point of view? This considers the feasibility of PS-InSAR for dike deformation monitoring based on the answers of subquestion 1, 2, and 3, considering the current needs for dike monitoring in the Netherlands, the dike types in the Netherlands, and the needs of Dutch stakeholders in dike monitoring.

Sub questions: 1. What are the important characteristics of dikes with respect to PS-InSAR? What are the main physical and geometrical characteristics of dikes which allow us to use PS-InSAR for dike monitoring. For example, the influence of the orientation of dikes, coverage layers of dikes. 2. Which types of deformation can be detected and which deformation mechanisms can be identified? Which deformation parameters can be derived from these observations considering different orbital configurations and which deformation mechanisms can be identified? 3. What is the quality of the results of the PS-InSAR technique in dike monitoring? What is the precision and reliability of the observations and the estimated deformation parameters. What is the quality of the diagnosis of the identified deformation mechanism?

POSEIDON, ﬁnal report 17 November 2006 1.2. RESEARCH METHODOLOGY 3

4. To what extent does PS-InSAR fulﬁll the needs for dike deformation monitoring in the Netherlands? This considers the feasibility of PS-InSAR for dike deformation monitoring based on the answers of subquestions 1, 2, and 3, considering the current needs for dike monitoring in the Netherlands, the dike types in the Netherlands, and the needs of Dutch stakeholders in dike monitoring.

1.2 Research methodology

In this paragraph, the research methodology that is developed for the POSEIDON project is described. The project is divided into three diﬀerent phases, because after each phase there are some documents that have to be handed in. This is described in the Deliverable Items Description, see [38]. For each of those three phases, the research methodology is described individually.

Phase 1: Requirement analysis and project planning. In this phase the requirements are speciﬁed, the stakeholders are identiﬁed and the project plan is made. Also the organization of the team is worked out. After this phase the baseline review has taken place. (See [34] for the product of this phase: the baseline report.)

Phase 2: Conceptual analysis, information gathering and combination and initial definition of case studies. The conceptual analysis part of phase 2 describes our route towards a good level of knowledge on the subject, which leads from literature study, through interviewing experts to performing forward models and studying inverse models. The information gathering and combination can be divided into defining additional data sources, combine them in one GIS package and getting experienced with the GIS package which will be needed in the 3rd phase. The initial definition of case studies deals with the number of case studies, and it will also give a rough determination of interesting locations.

Phase 3: Detailed analysis of the defined case studies. In the third phase a detailed analysis of the case studies will take place, using all information gathered in the second phase. To combine all this information and data sets, the GIS environment is needed. In this phase the locations of the case studies as they are defined in phase 2 will be visited. Another necessity is to increase the number of interviews with various experts, preferably during fieldtrips, so the case studies can be discussed one by one.

1.3 Boundary conditions

There are a few boundary conditions that can be deﬁned. They limit the scope of the POSEIDON project and are listed below.

1. The feasibility of satellite SAR interferometry is researched, so no comparison with other methods is conducted.

2. This project focuses on the application of the Persistent Scatterer method for dike monitoring.

3. The POSEIDON project focuses on the monitoring of primary dikes in the Netherlands.

POSEIDON, ﬁnal report 17 November 2006 4 CHAPTER 1. INTRODUCTION

1.4 Structure of the report

After this introduction the report continues with chapter 2, which describes the existing water barriers, the diﬀerent dike deformation mechanisms and the current monitoring methods. After this, chapter 3 will explain the Persistent Scatterer InSAR technique. After that, estimations of the dike deformation parameters are given in chapter 4. Detectable deformation mechanisms are presented, and the methods and results of our forward and inverse modeling are explained. The report concludes with the methodology and overview of our case studies, which will be treated in chapter 5 and 6 and the conclusions and recommendations for further research in chapter 7.

POSEIDON, ﬁnal report 17 November 2006 Chapter 2

Dikes, deformation and monitoring

This chapter starts with a brief explanation of the basics of water barriers. A division of categories is made and the structure of a typical dike is described. Hereafter we will explain the diﬀerent deformation mechanisms and the legal context of dike monitoring will be discussed. The chapter concludes with an explanation of diﬀerent dike inspection techniques.

2.1 Water barriers

In this section an overview of the different water barrier types in the Netherlands is presented. There will be a distinction between categories and types of water barriers. The POSEIDON project will focus on non- natural water barriers, the reason for this is that artificial water barriers are expected to have better reflection characteristics, see chapter 3.

2.1.1 Categories of water barriers

There are 17,000 kilometers of water barriers in the Netherlands. These can be separated into two categories, [20] , [22].

• Primary water barriers; • Non-primary water barriers (e.g. secondary barriers, storage basin embankments).

In this chapter the further discussion is based on this classiﬁcation.

Primary water barriers: The Netherlands has an extensive network of 3,700 kilometers of primary water barriers. These barriers offer protection against flooding by the North Sea, the Waddenzee, the large rivers (Rijn, Maas, IJssel), the Westerschelde, the Oosterschelde and the IJsselmeer. The primary water barriers mainly consist of dikes, only the North Sea coast is predominantly protected by dunes. The network of primary water barriers includes a large number of big dams and special constructions, like the storm surge barriers in the Oosterschelde and the Nieuwe Waterweg. For a limited number of places high grounds fulfill the function of primary water barrier. High grounds are areas that are sufficiently high and broad to prevent water from flowing further, no management is necessary to maintain this situation.

5 6 CHAPTER 2. DIKES, DEFORMATION AND MONITORING

Figure 2.1: Primary water barriers (in red) and dike-ring areas in the Netherlands [54]

The total length of the different kinds of primary water barriers in the Netherlands are [41]: • 264 km dunes; • 431 km sea dike; • 1,433 km river dike; • 535 km lake dike; • 1,000 km of dike that is in front of other primary water barriers (e.g. the Afsluitdijk). The Netherlands can be divided into separate areas which are each fully enclosed by water barriers. Such an area is called a dike-ring area (”dijkring gebied”). In total there are 57 dike-ring areas in the Netherlands (figure 2.1). The primary water barriers have stringent safety standards. In the law on water barriers in the Netherlands (”Wet op de waterkering” [4]) the importance of these standards is assessed based on the nature of the flooding and the possible amount of damage in that area. For each dike-ring area there is a dedicated norm, this is the average amount of times a year that the water level reaches the maximum that the dike must be able to withstand. For instance the norm 1/1,250 means that there is a chance of 1 to 1,250 a year that the water level will reach the maximum of the dike. The most important areas in the Netherlands have a norm of 1/10,000.

POSEIDON, ﬁnal report 17 November 2006 2.1. WATER BARRIERS 7

The primary water barriers can be subdivided into ﬁve categories:

1. The water barrier belongs to a dike-ring area and blocks a body of water; 2. The water barrier belongs to a dike-ring area but does not directly block a body of water; 3. The water barrier lies in front of a dike-ring area and blocks a body of water; 4. The water barrier lies in front of a dike-ring area but is not intended for direct blocking of a body of water; 5. Primary water barriers outside of the Netherlands.

Water barriers belonging to category 1 are the last line of defense against inundation of salt water. Category 2 water barriers separate two dike-ring areas and they are the last line of defense against freshwater flooding. Behind the water barriers of category 3 and 4 there is no land, only water. Examples of category 3 are the Afsluitdijk and the storm surge barrier in the Oosterschelde. An example of category 4 is the northern part of the Grevelingendam, where there is water on both sides, this dam can be seen in figure 2.1 above the dike-ring area number 27. The function of water barriers of category 3 and 4 is to avoid or reduce the occurrence of high water levels behind them. This means they limit the load on the category 1 and 2 water barriers. Category 5 water barriers exist where a dike-ring area passes the border of the Netherlands, these are the dikes along the Rijn, Schelde and Eems. A dike failure in these areas will possibly result in a flood in the Netherlands.

Non-primary water barriers: Non-primary water barriers consist of secondary water barriers, storage basin embankments and other types of embankment. Secondary water barriers protect the Netherlands against floods from other water systems. They lie within a dike-ring area and have the function of splitting up that area. In this way they limit the area that would be inundated in case of a flooding, they can also be used as an escape route for people or transport of rescue-material. Storage basin embankments (”boezemkaden”) lie within a dike-ring area and are there to protect a polder area from the water in the storage basin around the polder. Another function is to maintain the storage basin, which has a buffer function in case of high waters. In contrast to secondary water barriers, storage basin embankments do have a direct water blocking function. Other types of embankments were constructed to protect the dike-ring areas against water for the (smaller) rivers that run through the Netherlands. They have the function of blocking water coming from the rivers.

2.1.2 Types of water barriers

A major separation in types of water barriers can be made by distinguishing natural and artiﬁcial water barriers. Natural water barriers can be found along the largest part of the Dutch coast. The most important natural water barriers are the dunes, but also high grounds function as a natural water barrier. Dunes are a part of the natural landscape: they are formed by the wind and consist of sand in combination with vegetation. The water blocking function of dunes is solely due to the mass of the sand. This mass needs to be enough to protect the land behind it even though there might be a lot of erosion.

There are 3 types of artiﬁcial water barriers for the protection of a dike-ring area against high waters. These are (ﬁgure 2.2):

Ground constructions: Dikes and dams are artiﬁcial earth bodies. In comparison to dunes dikes need to be more erosion proof due to their smaller size. This is achieved by reinforcing the top layer with clay and grass, a stone-like material or asphalt. Typical for this construction is the form, which is the same as a trapezoid. The water blocking ability of this construction is determined by the height and the strength.

Water blocking constructions: These constructions are made for another purpose that crosses the function of water barrier. Such a function can be: shipping (sluices), a storm surge barrier, a water pumping station, a ﬂoodgate or a road passage.

POSEIDON, ﬁnal report 17 November 2006 8 CHAPTER 2. DIKES, DEFORMATION AND MONITORING

Figure 2.2: The main types of water barriers [57]

Special water blocking constructions: Special water blocking constructions have the same function as the ground constructions, but the form and materials used can be very diﬀerent. Examples of special water blocking constructions are embankments and walls. In this way a larger design freedom is achieved and more functionality is possible. On the other hand more management and maintenance is needed. The strength of the construction results from the used construction materials like steel and concrete which can handle much higher stresses than clay. The global stability is achieved by friction with the ground, for instance with pilings.

The artificial water barriers of types 1 and 3 are made of a combination of clay, sand and basaltic rock. This material is available in large quantities, easily processed, flexible, very durable and simple to maintain. In situations where water barriers cross (water) ways, artificial water barriers of type 2, like sluices and crossings are made. These water blocking objects were formerly made of wood and brickwork, later also of concrete and steel. The amount of these constructions was generally limited because of the risk of not being able to close them quickly enough.

Often there are other objects in the surroundings of water barriers, for instance buildings, roads, cables and trees. These objects are there for other reasons than blocking water, but can inﬂuence the functioning of the water barriers. Objects inside the water barrier ask for extra attention and extra maintenance. Pipelines form potential leaks, buildings and trees can become a weak spot.

The diﬀerence between the types of water barriers and the related objects is not that evident. Special constructions can reinforce, complete or entirely replace ground constructions. Special constructions can be ﬁxed or be movable, while water blocking constructions are in fact nearly always movable special structures.

2.1.3 Structure of a dike

This section gives an overview of the general structure of dikes, the construction materials and how they are built. Furthermore the general shape of a dike is described with some remarks on the dimensions.

Construction materials: Primary water barriers (as described in subsection 2.1.1) are usually made of clay, sand and boulder clay. Secondary dikes are usually made of a different material, like for instance peat. A dike is built on a surface that has different subsoil layers each with their own characteristics. In some cases the subsoil is not strong/stable enough to build a dike on, in those cases ground improvement has to be performed. This can be done by removing the top layer of the soil and replacing it with a more suitable material. The rest of the dike is built on top of this. The core component of primary dikes usually consists of sand, it is covered by one or two layers of (boulder) clay with a minimal thickness of 1 meter. This is because clay (in combination with grass) is best suited against erosion and does not let water through easily [32]. On the surface some extra protection is added, on the inner slope and on top this is usually grass, and on the outer slope this is a hard material like asphalt, basaltic rocks and rubble. These hard materials have good reflectivity properties for radar; it does not absorb a lot of energy and signals can bounce back with more ease. A schematic drawing of a dike can be seen in figure 2.3.

POSEIDON, ﬁnal report 17 November 2006 2.2. DESCRIPTION OF DEFORMATION MECHANISMS 9

Figure 2.3: Schematical drawing of a dike [50]

Shape of a dike: Dikes in the Netherlands can have different shapes, this is due to different demands on the dikes and a different historical background. Primary dikes have much shallower slopes than non-primary dikes. Dikes with a wider base are preferred because these are more stable and have more strength; on the other hand they are also more expensive and take up more land. The top of a dike is about 2-4 m wide, but sometimes wider due to, for example, a road. The maximal slope is determined by the soil type, each soil type has a natural slope at which the soil just does not start sliding. For sand the proportion is 1 : 1 (that is at an angle of 45◦). Most dikes have less steep slopes, for instance with a proportion of 1 : 4 (that is 14◦). These slopes can not be too steep, because then the slope will become unstable, but it is also preferred that the slope must also not be too shallow. This is an unnecessary use of material and space. The height of a dike is determined using regulations like the Delta-norm, these say that most primary dikes should have a height of at least 10 meters above NAP. Every dike has a so called inspection report (”keur” in Dutch) in which the construction height of a specific dike is mentioned. To prevent water flowing underneath the dike it is sometimes reinforced with an additional (smaller) body of material on the inner slope, this is because there is an increase of the dike length and water has more resistance flowing underneath the dike. Due to this extra material the dike now has the shape of a long trapezoid with a smaller trapezoid on top. Something else that determines the shape of a dike is the infrastructural need. Many dikes have roads or paths on top, these determine the minimal width of the top of the dike.

2.2 Description of deformation mechanisms

Several types of deformation of a dike can be distinguished. These types of deformation largely coincide with the failure mechanisms of a dike. Failure mechanisms are commonly used in the ﬁeld of dike monitoring to test the dike for safety. They are mechanisms that may lead to breaching of the dike. In total there are 12 diﬀerent kinds of failure mechanisms that endanger the primary function of a dike, which is of course protecting the land

POSEIDON, ﬁnal report 17 November 2006 10 CHAPTER 2. DIKES, DEFORMATION AND MONITORING

Figure 2.4: Overview of deformation mechanisms from the water ([41],[17], [30] and [31]). These failure mechanisms are causes of deformation mechanisms, which are schematically explained in ﬁgure 2.4.

In this section the types of deformation are explained. Some of them are the same as the failure mechanisms, but when discussing deformation mechanisms we focus on the fact that there should be a visible deformation on the dike body. Most deformation types do cause the dike to fail. Table 2.1 gives an overview of all deformation mechanisms, along with the failure mechanisms which cause the deformation, the magnitude and direction of the eﬀect, the duration of the process and the duration of the eﬀect.

Erosion foreland: The foreland is the part of the outer slope below the water level. This part can collapse due to sediment ﬂowing over it. The sediment ﬂow, which consists of matter like sand or clay mixed with water, can take soil particles of the foreland with it, causing the foreland to loose its stability and therefore can collapse. Collapsing of the foreland can lead to collapsing of the whole outer slope and after that the entire dike. Erosion of the foreland is a deformation mechanism as well as a failure mechanism.

POSEIDON, ﬁnal report 17 November 2006 2.2. DESCRIPTION OF DEFORMATION MECHANISMS 11

Deformation Failure Magnitude Direction Duration Plastic / mechanism mechanism(s) deformation process elastic deformation Erosion foreland Erosion foreland Different Horizontal + Endless Plastic vertical Erosion inner Wave Different Horizontal + Up to 2 weeks Plastic slope overtopping, vertical (duration high overflowing water) Erosion outer Erosion outer Different Horizontal + Up to 2 weeks Plastic slope slope vertical (duration high water) Horizontal Deformation ≤15 cm Horizontal Up to 2 weeks Elastic / Plastic deformation due to high (duration high water, nipping water), collision ice, collision is seconds Piping Piping small craters Forms craters Endless, up to a Plastic couple of days per crater Seepage Seepage <5 cm uplift vertical Mainly during Elastic high water Settlement Settlement Up to 50 cm, Vertical Exponential Plastic stretching up to decreasing 10 m form toe Sliding Sliding Announces itself Horizontal Up to a minute Plastic, with ≤15 cm announcement elastic is elastic movement Sliding inner Sliding inner Announces itself Horizontal + Seconds, Plastic, slope slope, micro with mm Vertical announcement announcement instability replacement, years is elastic later meters Sliding outer Sliding outer Announces itself Horizontal + Seconds, Plastic, slope slope with mm vertical announcement announcement replacement, years is elastic later meters Sliding (erosion decimeters Horizontal + Seconds, Plastic, protective cover foreland) vertical announcement announcement days elastic Subsidence Subsidence Depending on Vertical As long as the Plastic source of cause of subsidence, up subsidence to meter continues (to grow) Swelling Micro instability Few mm Horizontal + Up to a few Elastic vertical months

Table 2.1: Deformation mechanisms

POSEIDON, ﬁnal report 17 November 2006 12 CHAPTER 2. DIKES, DEFORMATION AND MONITORING

The magnitude of this deformation depends on the rate of flow of the sediment flows in the water body next to the dike. The deformation is plastic and remains until this flow vanishes. The direction of the deformation is in both the horizontal plus the vertical plane.

Erosion of the inner slope: Erosion of the inner slope can be caused by 2 different failure mechanisms, the first is wave overtopping, the second is overflowing. If the process of erosion continues long enough, it could cause a breach in the dike. The deformation mechanism is therefore very dangerous for the dike. Overflowing takes place if the water level in front of the dike exceeds the height of the dike. An example of overflowing can be seen in figure F.1. This can occur when the water level is higher than the dike is designed to handle. It can also be that the dike has become lower during the years so that it is not able to handle the water level that it was designed for anymore. There are a lot of deformation mechanisms that cause a dike to loose height, like settlement, erosion or sliding of the slopes. Possible causes for the higher water level can be a rise in the sea level, heavy precipitation, wrong calculations or just not enough data at the design phase to predict the water level correctly. Wave overtopping occurs when there is a combination of a high water level and large wave amplitude. These waves can be caused by passing ships or a storm. To make a distinction between wave overtopping and overflowing, the dike should be higher than the actual water level, but should not be high enough for stopping the waves. Wave overtopping leads to erosion of the top and inner slope of the dike, which can cause the dike to breach because of sliding of the inner slope. An example of wave overtopping can be seen in figure F.2. The magnitude of this deformation depends on the rate of flow of the water over the dike. The deformation is plastic and keeps on going until this flow vanishes. The flow vanishes if the water level decreases, which is usually after about 2 weeks. The direction of the deformation is in both the horizontal and the vertical plane.

Erosion of the outer slope: At first sight, erosion of the outer slope is very similar to sliding of the outer slope. The difference is that erosion is a slow process, where soil particles which the dike consists of are swept away by currents and waves. Sliding of the outer slope will cause a much faster deformation of the dike, since the whole slope will slide down at once. Another difference with sliding of a slope is that erosion of the outer slope only occurs below the water level. Erosion can cause sliding of the slope, if enough particles are taken away. The danger of erosion is that it cannot be seen until the water retreats. The magnitude of this deformation depends on the rate of flow of the sediment flows in the water body next to the dike. The deformation is plastic and keeps on going until this flow vanishes. The direction of the deformation is in both the horizontal and the vertical plane.

Horizontal deformation: There are a number of failure mechanisms that cause horizontal deformation. The first is collision, although that mainly causes damage to the protective cover of the outer slope. The same holds for the second failure mechanisms that causes this type of deformation, which is nipping ice. A third failure mechanism is deformation due to high water. All failure mechanisms that cause horizontal deformation will be treated here. The mechanism collision is simply a ship colliding with the dike, causing damage to it. A dike should always be strong enough to resist a collision like that. The upper layer of the dike will probably be damaged. This leads to faster saturation of the dike, because the soil beneath the protective layer is now unprotected. Saturation is a danger because it leads to micro instability, a failure mechanism that will be explained later in this chapter. A collision can also cause the dike to be pushed landwards, just because of the pressing force of the ice. If the protective layer is not strong enough to withstand the incoming ship, the dike could also breach. Nipping ice is the phenomenon of small ice plates, piling up along the dikes, therefore putting pressure on the dike. Just like collision, the protective cover is endangered first. Due to the pressure of the ice, the dike might also be pushed landwards. This effect is the horizontal deformation that is discussed in this section (see [18]). At locations where ice nips, erosion can occur. The damage must be repaired as soon as the ice has melted. There is a chance that after the winter period other failure mechanisms will occur, because the protection layer is damaged. High water is a temporal effect with a maximum period of 2 weeks. The pressure of the water against the dike results in a horizontal deformation of the dike. The deformation is the biggest at the upper

POSEIDON, ﬁnal report 17 November 2006 2.2. DESCRIPTION OF DEFORMATION MECHANISMS 13

part of the dike. After the water level has decreased to its normal level, the dike will (almost) return into its original state. The horizontal deformation can be up to 15 cm. The deformation is mostly in horizontal direction, and keeps going on until the cause vanishes, which is usually after 2 weeks (in case of nipping ice and high water) or after a few seconds (in case of collision).

Piping: It is commonly known that high water levels cause water to seep underneath the dikes. This is because the high water pressure forces the water to travel to the lower lying areas. In most cases, the water will travel through weak spots in the lower ground layers, and form pipes. This seeping water will become a danger to the stability of the dike if it transports materials from the dike, such as sand. This will happen if the ratio of the height diﬀerence to the length of the pipe is greater than 7% (Mr. Vrijling, Delft University of Technology, oral communication, 28 September 2006). If enough sand is removed from under the dike, the dike will become unstable. Piping frequently results in wells, see ﬁgure F.4. The deformation process leaves small craters in the landscape just behind the dike. These craters can measure up to a few meters in diameter. The process lasts for a few days per crater, but over all a dike body is continuously threatened by this phenomenon. The deformation is plastic.

Seepage: If the water level on one side of a dike is higher than the land on the other side, some water sill seep through the dike and soil layers under the dike towards the land. This eﬀect increases if the diﬀerence between the water level and the height of the land increases. The seeping water makes contact with the ground water on the land side of the dike, which causes an upwards pressure under the land. This upwards pressure translates into an upwards motion of the land, which can be measured as deformation. The uplift depends heavily on the soil characteristics and can be up to about 5 centimeters in case of extremely high water and a thin upper layer of soil (Mr. van Baars, Delft University of Technology, oral communication, 6 October 2006). The deformation will start as an elastic deformation, and can get plastic if the water pressure is too high for the upper layer of soil next to the dike. The deformation occurs in the vertical plane.

Settlement: Settlement is a deformation mechanism that mainly causes deformation in the vertical direction i.e. the dike becomes lower. The danger of settlement is that the dike loses too much height to prevent failure mechanisms like wave overtopping and overflowing. The settlement rate is dependent on the location, way of construction and construction material which is used to build the dike. The deformation happens mainly in the vertical plane. The most important effect is the settling of the soil layers directly under the dike, which occurs due to the weight of the dike. The settlement is therefore a very local effect around the dike, and stretches up to 10 meters from the toe of the dike. The effect lasts throughout the whole lifetime of the dike. The magnitude of the effect can be up to 50 centimeters, with a speed of a few centimeters a year. The speed decreases with time. The magnitude depends on the composition and weight of the dike, and on the composition of the soil beneath the dike. The deformation is largely plastic, if the dike is removed the soil might show some uplift, but will never return to the original state.

Sliding: Sliding of the whole dike is somewhat similar to sliding of the inner slope. The process starts with a horizontal elastic landwards deformation because of the water pressure. This may become a plastic horizontal movement when the water pressure exceeds the strength of the dike, causing the entire dike to slide horizontally. The strength of the dike is dependent on the weight of the dike, the density of the used construction materials and the capability of the construction material to dissolve in water. An example of a plastic horizontal sliding of a dike is given in figure F.5. The effect itself is, as can be seen in figure F.5, plastic and quite large. The effect is very rapid as well; the sliding is completed within a few seconds. The effect that announces the sliding is smaller and happens at a smaller speed. It is a mainly elastic deformation, and can be compared with a combination of settlement due to dryness of the dike, and horizontal deformation due to high water. The dike starts to tilt a bit landwards due to the pressure of the water, while getting smaller because of the lack of water in the dike body. Sliding is only likely to occur in case of dry peat dikes.

Sliding of the inner slope: The inner slope is the land side slope of the dike. This slope can become unstable due to various reasons. When large amounts of water are passing the dike, for example because of overﬂowing or wave overtopping, the water can soak the inside of the dike. This will lead to a higher internal water pressure of the dike and less friction resistance because of the saturation of the

POSEIDON, ﬁnal report 17 November 2006 14 CHAPTER 2. DIKES, DEFORMATION AND MONITORING

soil particles. The state of the dike at that moment is referred to as micro-instability. Micro instability can cause sliding of the inner slope. Cracks in the inner slope will speed up the sliding process. Sliding of the inner slope does not necessarily have failure of the dike as a consequence. It will definitely weaken the dike, but as long as the top of the dike stays at the same height, the area behind it will not flood immediately but some reparations are really necessary (as can be seen in figure F.6). If the top lowers as well, the height of the dike decreases which can cause immediate overflowing and eventual breaching of the dike. The effect is a horizontal and vertical plastic deformation. It announces itself by a small deformation, in the same direction as the plastic deformation. The announcement is mainly elastic. It is a combination between swelling and some incipient ruptures and minor slides. The announcing effect can last several years and is on millimeter level.

Sliding of the outer slope: Sliding of the outer slope often occurs after a period of high water, followed by a fast decrease of the water level, but it can also occur during a high water period. The first scenario is caused by the following sequence of events: When the water level is high, the dike will get saturated with water. If the water level then drops, the water which is trapped in the dike cannot flow down. Due to higher pressure of the top part of the dike the outer slope will slide down. Sliding of the outer slope during a period of high water is caused by erosion of the foreland/ outer slope. This leads to a removal of the base of the dike, which leads to a slide. Just like other sliding effects, the announcing effect is of millimeter magnitude. The effect consists of erosion of the foreland or the outer slope, and is therefore plastic. A minor deformation of the dike body can as well be seen; one should think of some tilting towards the area where the erosion takes place.

Sliding of the protective cover: Sliding of the protective cover is similar to sliding of the outer slope, with the diﬀerence that only the upper layer slides down. This deformation mechanism causes a change of the surface of the dike. The main cause of this is erosion, which can cause the stones which cover most dikes to become unstable and roll down. It could also be inﬂicted by the loss of roll resistance in the layers beneath the protective cover.

Subsidence: Subsidence is a vertical deformation of a large area, including the dike. This can be caused by gas extraction or salt mining for example. The consequence is that the dike and its surrounding area will deform in vertical direction. When this happens (whereas the water level will not decrease) the dike can become lower than its required height, which gives a higher risk of overﬂowing.

Swelling: Swelling is a temporal effect, where the dike will get saturated with water for example due to extraordinary rainfall or high water. This will cause a slight increase in size of the dike.The magnitude of the effect is dependent on the construction material of the dike. A sandy dike is not likely to get saturated with water, because the sand particles are not able to hold the water, whereas dikes which are made of clay or peat are likely to get saturated with water. Swelling can, along side of micro instability, be the result of saturation. A reaction of the dike to swelling can be the sliding of the inner slope caused by water pressures inside the dike. The second is the flushing away of soil particles due to the leakage of water. Swelling is a small effect which has always been hard to measure. It is an elastic deformation, and is caused by saturation of the dike body with water. The period of the deformation is a few months at most.

2.3 Legal context of dike monitoring

The ﬁrst part of this section deals with the responsibility for the dikes in the Netherlands. The second part gives some insight into what legal issues will be relevant if some weaknesses in the dike system are found.

POSEIDON, ﬁnal report 17 November 2006 2.4. CONVENTIONAL GUIDELINES FOR DIKE MONITORING 15

2.3.1 Responsibility of dike monitoring

The waterboards make a division between primary dikes and non-primary dikes. Primary dikes are major barriers that protect the land from open water, like sea, lakes and rivers. Non-primary dikes are barriers that protect land from small water ﬂows, like canals and creeks. The non-primary dikes have mainly the function of preventing (rain) water problems.

According to [8] the primary dikes are, in 90% of the cases, the responsibility of the waterboards. The other 10% is maintained by the state. Examples of primary dikes maintained by the state are the Afsluitdijk, the Oosterscheldekering and the Maeslantkering. All non-primary dikes are maintained by the waterboards.

The Provincial Parliament has the task of controlling and checking the work of the waterboards within their own province. The ﬁnal end responsibility is with the secretary of state of the Ministry of Transport, Public Works and Water Management.

2.3.2 Legal issues using InSAR for dike monitoring

The law on the water barriers of the Netherlands does not state a definite way in which the dikes should be monitored (see [26] for the whole law text). It does say that the ”Voorschrift Toetsen op Veiligheid” (see [54]) should be followed. This document literally sets down the format and the inclusions which a dike-stability report should have (see section 2.4 for a detailed description of those inclusions). This document states that the height of the dike could be monitored with leveling, but other methods are also allowed, if specified in the dike-stability report. Other examples mentioned are tachymetry and helicopter laser altimetry. The result of the ”Voorschrift Toetsen op Veiligheid” is that any measurement method will be sufficient, as long as it is scientifically proven to work, and its accuracy known and described as well.

If unsafe areas are found, therefore causing properties of people living behind the dike to devaluate, there will be consequences for the waterboards, because they are responsible for the good condition of the dike. If new unsafe areas are found, the waterboards are to blame for that.

2.4 Conventional guidelines for dike monitoring

The assessment of the safety of dikes is based on a subdivision of the main parameters of a dike. The way the dikes will be able to protect the area behind them against inundation, will depend on the height of the dike and/or its stability. Signs of deformation can be observed during the stability inspection and comparing the crest height margins of two height inspections. Therefore, these main parameters will be discussed next in separate sections.

2.4.1 Height inspection

The failure mechanisms that are dependent on the height of the dike are overflowing, wave overtopping and settlement. Whether the dike is able to fulfill its safety function for the area behind it depends on two parameters, namely the crest height margin and the amount of tolerable water discharge. The crest height margin (”kruinhoogtemarge” ) is the difference between the crest height of the dike and the water level in leading circumstances, which includes the expected water level rise until the reference date and some additions for the expected weather oscillations. The amount of tolerable water discharge (”overslagdebiet” ) is the maximum amount of water that may come over the dike, which the pumping stations still can handle. The judgment of the crest height can be defined in three steps, which have an increasingly detailed procedure. When the result of the first and most simple method is sufficient, its not necessary to perform the other methods. These steps are given in figure 2.5 schematically.

POSEIDON, ﬁnal report 17 November 2006 16 CHAPTER 2. DIKES, DEFORMATION AND MONITORING

Figure 2.5: Schematical overview of height testing procedure.

Step 1: Simple testing The simple testing method of step 1 is based on the design conditions (e.g. the water level) the dike is designed to handle. This way of testing is only possible when the used design conditions have proved to be favorable with respect to the current testing conditions. This means that:

• The expected water level rise until the reference date plus the additions, wave amplitude and wave period should be the same or less than the designed ones • The crest height including the settlement cannot be lower than the designed height of the dike • The slope of the dike may not be steeper than the designed value • The amount of tolerable water discharge cannot be smaller than the designed value

To be able to test those conditions, it is necessary that the actual crest height is known and that the settlement of the dike is estimated. When these conditions cannot be fulfilled, the testing must proceed to the next step. An advantage of the first step is that no calculations are needed. It is only necessary to compare the current parameters with the design parameters. Step 2: Detailed testing The second, detailed testing method is applying the calculations from the guidelines for dams, sea- and lake dikes [58] or the guidelines for river dikes (see [55] and [56]), dependent on the dike type. The first thing that should be calculated (see [59]) is the amount of tolerable water discharge, belonging to the crest height and the slope of the dike. • If the amount of tolerable water discharge is smaller or equal to 0.1 l/m/s it is considered negligible and then the crest height margin is calculated. When the crest height margin is more than 0.3 meter it is ”sufficient” (if it is 0.5 meter or more its excellent), but when it is less than 0.3 meter, advanced testing is necessary (step 3). • If the amount of tolerable water discharge is bigger than 0.1 l/m/s but smaller than 10 l/m/s, the influence on the inner slope should be tested. This influence is strongly dependent on the type of protective cover on the inner side of the dike. When this cover consists of stone or asphalt, it is assessed as ”excellent” as long as the crest height is bigger than the water level in leading circumstances and the amount of tolerable water discharge is coming from 2% or less of the total number of incoming waves. When this cover is grass, it has to be tested for erosion and sliding of the inner slope, for other types of protective cover the specialists have to step in. When the protective cover gets a judgment ”insufficient” this is also the final assessment, when it is

POSEIDON, ﬁnal report 17 November 2006 2.4. CONVENTIONAL GUIDELINES FOR DIKE MONITORING 17

”sufficient” or ”excellent” the crest height margin has to be checked. Then the same holds as in the previous situation, that when the crest height margin is more than 0.3 meter the assessment is ”sufficient” (if its 0.5 meter or more its ”excellent”, but this is only possible if the protective cover was excellent as well), but when its less than 0.3 meter, advanced testing is necessary (step 3). • If the amount of tolerable water discharge is 10 l/m/s or more, the crest height margin plays a crucial role in the further testing method. When this margin is less than 0.5 meter, the assessment ”sufficient” can only be given after advanced testing (step 3). When the margin is 0.5 meter or more, this is large enough to exclude overflowing and only consider wave overtopping. With a tolerable water discharge of 10 l/m/s or more, the crest of the dike is not passable for inspection or reparation work and it has to be proved that this does not endanger safety. If it does, the final assessment is ”insufficient”. When it is not necessary that the crest of the dike is accessible, the final assessment is dependent on the measure of storage and discharge possibilities. If they are restricted in such a way that the wave overtopping will endanger the safety, the final assessment is ”insufficient”. If it causes an unacceptable amount of superfluous water but it does not endanger safety, the final assessment will be ”sufficient”. If it causes no (unacceptable) amount of superfluous water it will get the final assessment ”excellent”. Step 3: Advanced testing The third and final step is the advanced testing, which has to be performed by specialists (the first and second step can be conducted by the bodies responsible for dike monitoring). They have to set up a testing method which is specifically designed for the dike that is being tested. They will check whether the uncertainties in the water level in leading circumstances are covered by the crest height margin and whether its safety will be preserved.

2.4.2 Stability inspection

Just like the height inspection which was described in the previous section, the stability inspection can also be divided into three diﬀerent degrees of detail. The stability of a dike is dependent on more parameters than just the height of a dike, so much more failure mechanisms have to be tested. It also includes parameters that are more diﬃcult to observe than the current height and water level in leading circumstances of the previous section. Therefore the stability testing is split into four main types of failure mechanisms, namely piping, micro instability, sliding of the outer slope and sliding of the inner slope. For each of those four types of mechanisms, the three testing methods (simple, detailed and advanced) are applied.

Step 1: Simple testing The way the first step, the simple testing method, will be applied is dependent on the used construction material and the soil types at the location of the dike. There are 4 different types that can be distinguished, namely primary dikes made of clay, primary dikes made of sand which are built on either a good or a bad water passing soil type. For each of those dike types, a geometrical test and testing of the used design method are performed, where only simple calculations have to be used which can be found in [54]. Because most of the dikes in the Netherlands were built before the design guidelines came into existence, it is necessary that their designs are checked for safety. For instance, sufficient soil research must be carried out. Furthermore, it has to be checked that, at the time of the design of the dike, the designers had sufficient knowledge of the stresses and the potential of the water under leading circumstances. Lastly, the accessibility of the dike when the safety is in danger should be accounted for. Step 2: Detailed testing The second, detailed testing method is based on data collection or based on applying the calculation models of the guidelines (see [55], [56] and [58]). This data collection can only consist of enumerating the existing data or performing some additional soil research. Examples of additional soil research are measuring the water tensions inside the dike or in the subsurface or researching the layering of the subsurface of the area behind the dike. Step 3: Advanced testing The advanced testing method is based on the state of the art knowledge of the specialists on the failure mechanism, advanced calculation models, etc. But before these advanced tests will be performed, there will be some research done by specialists on the feasibility of the advanced testing and the necessity of those models.

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Figure 2.6: Crumbling of basaltic stones [42].

2.5 Dike monitoring in practice

The parties that are responsible for maintenance and inspection of the primary dikes, have to test and report the status of their primary dikes every ﬁve years to the Provincial Parliament in accordance with the guidelines as described in the previous section (see [49] or [47] for an example of such a report). But this is not the only testing, which is done by the responsible parties (for most of the primary dikes, these are the waterboards). They also conduct a so called dike watch (”dijkschouw” in Dutch) with a written report once or twice a year. Unreported dike watches are, in some cases, conducted daily. After storms and other dangerous events, a dike watch will be conducted. In this section, the method how the reported dike watch is conducted is explained brieﬂy.

The most important goal of the dike watch is the prevention of unsafe situations. It also gives the waterboards a good opportunity to get insight into the state of maintenance and they can keep their data of the dikes up to date. The dike watch is a broad visual inspection where the maintenance state of the dike and possible damage are checked. The dike watch splits the primary dikes into four diﬀerent areas of interest, namely the outer slope, the dike crest, the inner slope and the vegetation on the dike.

The ﬁrst part of the primary dikes that is watched carefully is the outer slope. The outer slope of the primary dikes is mostly protected with a layer of (basaltic) stones. The quality of those stones is decreasing with time. This is because after years of exposure to sunlight, salt, water and wind, the basaltic stones will crumble. This can be seen in ﬁgure 2.6, where the smooth basaltic stones are lying next to the crumbled ones. The dike maintains its strength, because those crumbled stones are captured between the smooth stones, but they have to be replaced in time.

The crest of the dike is mostly checked on its height, but also some cracks on this part of the dike are monitored carefully. They can be used to indicate whether a slope of the dike is going to slide downwards. The inner slope is mostly checked for seeping water and resulting wells. These are signs that something has changed with respect to the stability of the dike.

Testing the vegetation on the dike is a legal obligation, which has to be performed every 5 years, [26]. Due to practical reasons, most of the waterboards choose for a division of their primary dikes, so each year one part can be tested carefully. The testing aspects are for example the amount of diﬀerent species and the root penetration. The presence of weed between the stone cover at the slopes also gives a drawback: It makes the quality assessment of the stone covers diﬃcult or even impossible.

POSEIDON, ﬁnal report 17 November 2006 2.5. DIKE MONITORING IN PRACTICE 19

Figure 2.7: The FliMap system [14]

2.5.1 Used measurement techniques for dike monitoring

There are several acquisition techniques in use to obtain information of the dikes. The most common methods at this moment are leveling, GPS-RTK, FliMap r and Ground Penetrating Radar. These methods will be explained in this section. There are also some other measurements techniques where the application of dike monitoring is still in a research stage. For further information, see for example [51] and [11].

Leveling This is the oldest way to obtain height information and deliver data with millimeter precision. This technique is still used, because newer techniques can not meet this order of accuracy. The method is especially used during and after dike reinforcement to monitor the crest height and settlement by measuring the crest height. When these data are stored, future height measurements can be compared with the old measurements to assess the deformation in between. GPS-RTK The GPS-RTK (Real Time Kinematic) technique delivers data with an accuracy of a few centimeters. This method is used in cases where less precise height information is required, for example for measuring profiles, quantity survey and to obtain topographic information. But it is also an used technique to measure horizontal deformation. FliMap r FliMap r (Fast Laser Imaging - Mapping and Profiling) is a system from the company Fugro that uses LiDAR (Light Detection And Ranging) in combination with high-resolution photo and video imagery, to monitor railroads, dikes etc. As platform a helicopter is used. The position of this helicopter is known by the use of GPS-RTK (see figure 2.7). The advantage of a helicopter above an airplane is that a helicopter can fly slower and at a lower height. This means that the point clouds obtained by the laser system are of a higher density, and that means also a higher accuracy, which can be up to decimeter level. Out of this data, a lot of information can be extracted such as height models, profiles and positions of water embankments. Ground-penetrating radar A ground-penetrating radar (GPR) system uses two antennas, which are mostly a fixed distance apart. One is a transmitting antenna, which emits an electromagnetic wave field into the ground, and the other is a receiving antenna, that records this field and its reflections from the subsurface. When an electromagnetic wave propagates through the ground and detects a soil layer where the electric and/or magnetic properties of the ground change, part of its energy will be reflected back to the receiving antenna and part of it will be transmitted through the soil layer. It is mostly used for the detection of soil layers and objects beneath the surface, but also the groundwater level can be detected easily, because it is a strong reflector (after [40]).

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POSEIDON, ﬁnal report 17 November 2006 Chapter 3

Principles of deformation monitoring with radar interferometry

In this chapter, the principles of radar interferometry for deformation monitoring will be explained. The ﬁrst part contains the basic idea of interferometry, which can be used to measure topography and deformation parameters. After that, it will continue with an explanation of the conventional Interferometric Synthetic Aperture Radar (InSAR) method and its main characteristics and limitations. Finally, the more advanced technique ”Persistent Scatter InSAR” (PS-InSAR) will be introduced and the main advantages and limitations of PS-InSAR will be discussed.

3.1 Introduction to InSAR

Since the early 1960’s, radar imagery has played an important role in remote sensing science and has opened a world of new applications in geosciences. Early experiments of synthetic aperture radar (SAR) sensors showed the good performance of the SAR systems in mapping the earth surface and acquisition of physical properties of the earth. In contrast to optical remote sensing sensors, which are passive sensors and measure the sun’s radiation reﬂected from the ground, radar sensors do not need solar illumination. Radar satellites actively illuminate the earth and record the amplitude and phase of the backscattered waves. Furthermore, because radar waves are in the microwave regime of the spectrum (with a typical (long) wavelength of about 5-25 cm) they can travel through clouds. This means that radar satellites can operate day and night and almost independently of meteorological conditions.

Compared with optical sensors, one limitation of a radar or SAR system is in the incapability of measuring angles. ”Similar to a single human eye, which is essentially blind for the diﬀerence in distance to the object, it is impossible for a radar or SAR to distinguish two objects at the same range (but diﬀerent angles) to the instrument. Nature readily provides the simple solution for the problem: the use of two sensors. It worked with two eyes, why not use two radars?” ([37]). This is the basic idea behind the interferometry.

Using the principle of interferometry and by using the phase measurements of two SAR images, it is possible to measure the variations in the distance between the satellite and the earth’s surface due to topography and deformation. Today, InSAR is generally known as a powerful tool for detection of surface displacements over large temporal scales with precision in the cm and even mm range. This possibility causes InSAR to find useful applications in different fields such as earthquake and volcanic studies, glacier monitoring and land subsidence monitoring due to the mining, gas, water, and oil extraction.

The purpose of this chapter is to review the principles of conventional SAR interferometry and to describe a more advanced InSAR technique (PS-InSAR) for deformation monitoring and the main issues concerning the

21 22 CHAPTER 3. DEFORMATION MONITORING WITH RADAR INTERFEROMETRY

Figure 3.1: Phase measurement, [19] interpretation of its results.

3.2 Conventional InSAR

In this section, the main characteristics of conventional InSAR are discussed. First the interferometric parameters are described, followed by the limitations of conventional InSAR. Despite the valuable application of InSAR in mapping the topography, the focus is here on the application of InSAR in deformation monitoring.

3.2.1 Basic idea

Deformation monitoring using InSAR is based on the principle of distance measurements with electromagnetic waves. If the sensor transmits a pulse to the object and records the return pulse, the time difference between these two pulses shows the distance between the sensor and the object. In other words, the time delay of the echo (reflected pulse) measures the distance of the sensor to the object. This time delay can be measured as the phase difference between transmitted and received wave. With two acquisitions, the difference in measured phases shows the variation in the sensor-object distance.

Similarly, a SAR sensor transmits a signal to the earth and measures the amplitude and phase of the backscattered signal. The phase of the signal that is backscattered from the radar target on the earth, is related to the sensor-target distance. A SAR image is actually a set of pixels characterized by both amplitude and phase values. In interferometry the amplitude of the received wave is ignored. Instead, the phase of the wave is used. Assume that two different radar images are obtained from exactly the same position in space. If nothing has changed, the measured phase of the second image should be exactly the same as the previous phase measurement in the first image. If there is any change in distance between the satellite and the earth’s surface due to deformation, the phases will differ (see figure 3.1). This phase difference shows the deformation in the direction of the satellite’s Line of Sight (LOS). By creating an image of these phase changes, it is possible to map deformation with the precision of a small fraction of the radar wavelength. This image is called an interferogram. The phase changes occur in the interferogram as fringes (see figure 3.2).

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Figure 3.2: Interferogram of Bam : The interferogram of Bam (Iran) constructed from two radar images, one before and one after an earthquake has taken place. Each of the colored interference fringes is equivalent to a 28 mm contour (half the wavelength) of surface deformation in the satellite’s LOS. The phase measurements are relative, so to calculate the deformation at each point one should count the fringes from the edge of the interferogram to that point and multiply it by 28 mm.

The above discussion is based on the assumption that both images have exactly the same acquisition geometry and that the only change between two images is the deformation of the surface. However, in practice there are other factors causing differences between two images, such as atmospheric conditions, acquisition geometry and scattering characteristics of the targets. These factors superimpose some phase differences on the interferometric phase measurements. These effects will be described in the next section, as well as other parameters that affect the interferometric phase observations.

3.2.2 Main interferometric parameters

As mentioned before, the InSAR technique for deformation monitoring is based on phase shift measurements. However, not only a deformation of the surface causes a phase change, also other factors introduce additional phase shifts. So, the interferometric phase observation per resolution cell (pixel) contains the contribution of diﬀerent factors [37]:

φ = 2πk + φtopo + φdefo + φatmo + φscat + φnoise 4πB⊥ 4π = 2πk + H + D + φ + φ + φ . (3.1) λR sin θ λ atmo scat noise

Where:

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φatmo Phase shift due to the atmospheric delay φdefo Phase shift due to deformation φnoise Noise (e.g. thermal noise, coregistration errors, and interpolation errors) φscat Phase shift due to a change in the scatter characteristics of the earth surface φtopo Topographic phase λ Radar wavelength θ Incidence angle B⊥ Perpendicular baseline (distance between the satellites) D Deformation in the radar LOS H Height above the reference frame k Phase ambiguity, the unknown integer number of full phase cycles. R Slant range from the master platform to the earth surface

As can be seen in equation 3.1, there are diﬀerent parameters that aﬀect the interferometric phase observation. Because the feasibility of the InSAR technique for this particular application depends on these parameters, we shortly describe each parameter in this section.

The interferometric parameters can be divided into two main groups [36]: design parameters and environmental parameters. The main design parameters are the radar wavelength, the perpendicular baseline, the time interval between the image acquisitions (temporal baseline), the incidence angle and inclination, and the total number of available images. The second group, the environmental parameters, consists of the earth’s atmosphere, the earth’s surface, and the speciﬁc deformation characteristics.

Design parameters

Radar wavelength: As deformation in the LOS is measured as a fraction of the wavelength, the precision and accuracy of the estimated deformation depend directly on the radar wavelength. This implies that the shorter the used wavelength, the more accurate the deformation vector that can be obtained. However, as short wavelengths are scattered by small objects, random movements of these small objects disturb the phase signal analysis. So in this case a larger wavelength is often preferred. On the other hand, a very large wavelength (larger than 24 cm) will suffer more from disturbances caused by the ionosphere and other radio interference. Perpendicular baseline: The perpendicular baseline has two major influences on the phase observation. First, the perpendicular baseline determines the sensitivity to a difference in topographic height. As can be seen in equation 3.1, the topographic phase is proportional to the perpendicular baseline. This implies that, if the perpendicular baseline is zero, the topographic phase will be zero as well. This situation is ideal for deformation measurements as the superposition of topographic phase is removed. However, the assumption that two images are taken from exactly the same location is unlikely in practice and phase observations usually contain a topographic phase. Using external elevation models or high quality InSAR acquisition without deformation signal (Differential InSAR), topographic phase can be removed. Because of an inaccuracy in the elevation models, some residuals from the topographic phase are left. In this case, after removing topography, equation 3.1 becomes [37]:

4πB⊥ 4π φ∆ = 2πk + ∆H + D + φ + φ + φ , (3.2) H λR sin θ λ atmo scat noise Where: φ∆H the differential phase ∆H the topographic phase residual The second effect of a perpendicular baseline on the phase observation is due to looking at the earth from a different imaging geometry. This difference causes the radar reflection at the earth’s surface to be changed and introduces a new effect as the phase noise. So, the phase noise is proportional to the perpendicular baseline. In radar interferometry, this effect is called geometrical decorrelation. Temporal baseline: Another design parameter is the temporal baseline. This parameter is a multiple of the satellite’s revisit interval, which is for example 35 days for the ERS-1, ERS-2, and Envisat missions. The temporal baseline should be large enough to detect the deformation mechanism of interest. On

POSEIDON, ﬁnal report 17 November 2006 3.2. CONVENTIONAL INSAR 25

the other hand, a large temporal baseline causes the phase observation to become noisier due to the temporal decorrelation. This effect is because of the changes in scattering characteristics of the targets in large time interval and makes it difficult to find corresponding pixels in two images. Incidence angle, inclination and number of images: Other design parameters are the incidence angle, the inclination and the number of available images. Using different combinations of interferograms, the effect of the incidence angle and the inclination can be altered. The fact that most of the radar satellites are in a near-polar orbit leads to difficulties in deriving the north-south component from the LOS deformation. This leads to worse accuracies in the north-south component. A satellite with an inclination of about 60 or 120 degrees would enable the processors to solve all three components properly [60]. The total number of acquisitions is important because many different images enable the processors to recognize high-quality pixels and to optimize the ratio between the deformation signal and atmospheric error signal [36].

Environmental parameters

Atmosphere: The atmosphere delays the radio waves and introduces an additional phase shift in the observation (φatmo). The amount of atmospheric disturbance depends on the climate conditions and the local weather situation. The magnitude of these delays can be up to several centimeters. Since a potential deformation is measured relatively between points in the image, a larger distance between points results in an increase in the atmospheric error signal [36]. Deformation characteristics: Deformation characteristics are other important parameters which can define the potential the InSAR technique for particular application. Deformation mechanisms are very difficult to recognize if they have a similar impact on the measurements as the satellite orbit error or the atmospheric phase shift. Furthermore, the velocity of the deformation plays an important role. For instance, a sudden deformation due to an earthquake or a landslide is easier to detect than slow deformation due to subsidence or tectonic movements. Another issue is that the deformation gradients between neighboring pixels should be smaller than the radar wavelength in order to be detectable. Land surface: The most important environmental factor is the reflective surface of the earth. SAR interferometry only works under coherent conditions, where the received reflections are correlated between the two SAR images [37]. Therefore, any change in reflection characteristics in the pixel area causes the loss of coherence or (temporal) decorrelation. For example, a water area is useless for interferometry due to the fast changes in the water’s physical characteristics. Usually, urban areas have a better coherence in time than agricultural and heavily vegetated lands. As an illustration, the city of Bam and the town of Baravat have a very low degree of correlation (see figure 3.2) because of the high amount of damage due to the earthquake and also because of the existence of vegetation areas in the region.

The effect of changes in the scattering characteristics of the resolution cell was shown by (φscat) in equation 3.1. If scattering characteristics of a resolution cell are exactly the same for both acquisition then (φscat=0). However, φscat is not zero in practice because of two reasons. Firstly, when the temporal baseline is too high, the land surface changes its scattering characteristics and causes temporal decorrelation. Secondly, due to the different looking angle the reflection of the resolution cell differs and causes the geometrical decorrelation.

3.2.3 Main limitations of conventional InSAR

Based on the discussion of the last section, the main limitations of the conventional InSAR method for deformation monitoring can be listed as:

1. Temporal decorrelation: The change in the reﬂection characteristics of the earth’s surface within a resolution cell results in temporal decorrelation. This eﬀect makes the InSAR measurements unfeasible in vegetated areas and in other areas where the scattering characteristics or the positions of the scatters change in time within a resolution cell.

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2. Geometrical decorrelation: The different viewing angles from the two platforms (due to the non-zero perpendicular baseline) to the same resolution cell on the ground cause a spectral shift in the observation and introduce a noise defined as geometric decorrelation. This effect limits the number of image pairs suitable for interferometric application, and keeps one from fully exploiting the available datasets [33].

3. Atmospheric inhomogeneities: The spatially and temporally variable state of the atmosphere superim- poses a new error signal that infers with the deformation signal. Atmospheric disturbances can strongly compromise the accuracy of the deformation monitoring.

In addition to these main limitations, the interferograms are aﬀected by two kinds of ambiguities. Firstly, phase diﬀerences are given in fractions of cycles (all pixels have a phase between 0 and 1), not as integer numbers of cycles. Secondly, interferograms provide a relative phase change, no absolute changes. This means that it is necessary to know a point with null deformation and refer all measurements to it.

3.3 Persistent Scatterer InSAR

In this section the Persistent Scatterer technique, also known as PS-InSAR will be explained. First there will be a subsection that deals with the basic concepts of this technique. The second part deals with the main issues of interpreting the PS-InSAR results.

3.3.1 Concept of PS-InSAR

The PS-InSAR technique is an advanced InSAR technique that has been developed to overcome the main limitations of conventional InSAR. These limitations are all caused by the lack of coherence in images due to the geometric and temporal decorrelation and atmospheric effects: the PS-InSAR technique aims at finding some features in the radar images that remain coherent over long time intervals, hereafter called Persistent Scatterers (PSs). In other words, PSs are isolated points with constant backscatter characteristics in time, so the φscat is comparable for these points. The PS-InSAR technique is a multi-interferogram technique which uses an extensive archive of satellite radar data to find these isolated points that are coherent in all radar images. Figure F.7 shows the detected PSs in the Harlingen area in the Netherlands. The color of the points represents the deformation velocity for each PS.

The ﬁrst advantage of PS-InSAR is that temporal and geometrical decorrelations are minimal in this technique. Due to the stable phase behavior of PSs in time, temporal decorrelation becomes minimal in PS-InSAR. Fur- thermore, because of the small dimension of PSs with respect to the resolution cell, geometrical decorrelation is also minimal, which leads to good coherence even for interferogram pairs with a large perpendicular baseline. Therefore, all available images can be exploited for interferometric analysis.

Another advantage of PS-InSAR is that the used different interferograms allow us to estimate the atmospheric phase and to remove this effect from the final results. Based on different temporal and spatial behavior, the contribution of topography, deformation and atmosphere can be estimated and separated from each other. Topography is not dependent on time, but scales linearly with the perpendicular baseline. Deformation is independent of the baseline, but is correlated in time. Atmosphere is independent of baseline, uncorrelated in time, but spatially correlated per interferogram [36].

The PS scatterers are usually small features (small with respect to the pixel size) with a dominant reflection in a resolution cell. Figure 3.3 shows the difference between the distributed scattering pixel and the pixel with dominant scatterer (or PS), and shows the different phase behavior for different resolution cells. Most of PSs are man made features, so there is a high density of them in urban areas and on infrastructures such as bridges, roads, dams and dikes. Also in mountain areas, some rocks and boulders can play the role of natural PSs.

POSEIDON, ﬁnal report 17 November 2006 3.3. PERSISTENT SCATTERER INSAR 27

Figure 3.3: Diﬀerent scattering resolution cell

The ﬁnal result of the PS-InSAR technique, after removing the atmospheric eﬀect, is a deformation time series for each PS. An important characteristic of these time series is that it shows the PS deformation in all images with respect to the master image (time reference). Also, the deformation of the PS is relative to the reference point. (This reference point is chosen in an image with the assumption of zero deformation). Using these time series it is possible to model the deformation behavior during time. Figure 3.4 shows these time series for one PS and the estimated linear deformation model for this point. Using a linear model, it is possible to estimate the velocity of deformation (the slope of the linear model).

Summarizing: By using all available images and removing the atmospheric signal, the PS-InSAR technique takes conventional InSAR one step further to derive relatively precise displacement and velocity estimation at speciﬁc points on the ground with an accuracy of 1 mm/year.

3.3.2 Main issues in interpretation of PS-InSAR results

Eﬃcient use of the PS-InSAR technique for deformation monitoring depends on a correct interpretation of its results. However, there are a lot of diﬀerent factors which should be considered in this interpretation. This section will summarize some of the main issues related to the interpretation of the estimated deformation using PS-InSAR.

Location of PSs: The interpretation of PS-InSAR data is dealing with the opportunistic nature of this technique. This means that the number and location of persistent scatters can not be predicted or optimized beforehand as they depend on the dielectric properties of the target materials and the geometry of the surfaces in relation to the satellite. So, it makes it difficult to define which specific features or deformation phenomena will be monitored. For example, the pixel size for ERS-1 images is 20x4 meters. The detected deformation in such an area could be due to the different features. Interpretation of the estimated deformation usually requires defining a scatterer object in the resolution cell.

Deformation in LOS direction: All deformations measured with PS-InSAR are projections of the real deformation in the LOS direction of the radar satellite. So, it is not possible to decompose this deformation into the North, East, or Up deformation. However, using more than one observation (e.g. deformation from both ascending and descending track), it is possible to decompose this measured deformation into

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Figure 3.4: Example of time series

the interesting deformation parameters in other directions. The detail of deformation decomposition can be found in section 4.3 about inverse modeling.

PS selection: The possible errors in the PS detection procedure are another topic that should be considered in the interpretation of the ﬁnal results of PS-InSAR. The detected PSs are points that passed the testing procedure in PS processing. Therefore two kind of errors are distinguished:

1. Type-I error: These points are the coherent points that are rejected and have not been detected as PS, whereas they should have been accepted. These errors are usually because of high deformation rate or signiﬁcant nonlinearity in deformation. 2. Type-II error: These points are incoherent radar targets that show, by coincidence, a high coherence and are detected as PS. These are falsely accepted points. They are usually isolated points with high estimated deformation rate and without side lobes.

For the interpretation of the results, the type-I error is not a problem. Only, it should be considered that there may be undetected nonlinear or large deformation in the area. However, type-II errors should be found as outliers and should be removed from the ﬁnal results.

Reference point: The reference point is the point within the study area to which all deformation measurements are relative. Therefore, if the absolute deformation of points is needed, it is important that the reference point itself is not moving over time. However, in many applications we are interested in only relative deformation in the study area and instability of the reference point does not cause any problem. It should be considered during the interpretation of the results that all estimated deformations are relative to this point.

Side lobes: Due to the sinc pattern of the reflected radar wave, usually the neighboring pixels of a PS are also affected by PS reflection and are detected as PS. So, there are some imaginary PSs that are not real objects. These pixels are around the real PS pixel. These imaginary PSs are called side lobes. Since the amplitude of the reflected wave of the side lobes is smaller than the PS’s main lobe, these points can be filtered based on their amplitude. However, the estimated deformation for side lobes is the same as the deformation of the PS’s main lobe. So, they are no problem in the deformation monitoring application.

POSEIDON, ﬁnal report 17 November 2006 3.3. PERSISTENT SCATTERER INSAR 29

Figure 3.5: Possible deformation for buildings

The only thing that should be considered is that all these points correspond to one PS and they are not separate PSs.

High displacement rate (phase unwrapping): The derived deformation rate with the PS-InSAR technique is in the direction of the satellite’s LOS. A measurement of a displacement in the LOS direction is limited to a fraction of the radar wavelength. This means that the PS technique is, just like conventional interferometry, only able to measure the wrapped part of the phase shift in the range of -λ/2 to +λ/2 (e.g. for wavelength of 28 mm, it means -14 mm to 14 mm). With PS-InSAR, this ambiguity is solved using phase unwrapping methods that calculate the correct number of phase cycles. These need to be added to each wrapped phase measurement. However in areas with a deformation rate where more than one phase cycle of displacement has occurred between two acquisitions, the phase unwrapping may fail. So, in such an area the estimated deformation rate is inaccurate. This implies that large deformation components can not be measured properly with this technique.

Significantly non-linear motion: The detection and identification of PSs is dependent on rather conservative types of deformation such as linear deformation [35]. In the case of significant non-linear motion, the employed algorithm may average out this deformation. So, an isolated coherent target that exhibits a complicated deformation pattern may not be identified. Generally, it is necessary that the linearity assumption for deformation mechanism is valid for a particular area during sampling time. Otherwise, some existing deformation will not be detected and the detected deformations also become incorrect and unreliable.

Autonomous movements: A PS-InSAR measurement might be of good accuracy, but is not in fact related to the expected deformation mechanisms. It may be autonomous deformation of one PS, for example one building in the area. Figure 3.5 shows some possible deformations of a building and its surrounding. In case A the building undergoes an autonomous movement with respect to its surrounding due to a bad foundation. Case B and C show a deformation of the surroundings due to compaction or gas extraction. In PS-InSAR applications that try to detect the deformation of particular buildings, these autonomous movements are no diﬃculty in the deformation interpretation. However, when the objective of PS- InSAR in a particular application is the detection of spatial deformation such as subsidence due to gas extraction, these autonomous movements should be detected and excluded from the collection of PSs which have deformation due to subsidence. Figure 3.6 shows another example of an autonomous movement. A house rolls over due to its inappropriate foundation and compaction of the ground underneath it. Because of its close distance to the dike, the detected deformation may be interpreted as dike deformation. However, it is an autonomous movement of the dike and is not related to the interested deformation, which can be subsidence of the dike for example.

Quality of results: The quality assessment of the PS-InSAR is still a research question. Generally, with perfect conditions, the relative LOS precision for the deformation rate can reach sub-millimeters. However, there are a lot of variable factors which affect the final quality of estimated deformation rate and can affect the final interpretation also. Some of these factors are: the temporal distribution of SAR data, the number

POSEIDON, ﬁnal report 17 November 2006 30 CHAPTER 3. DEFORMATION MONITORING WITH RADAR INTERFEROMETRY

Figure 3.6: Autonomous movement due to settlement

of used images, the spatial distribution and characteristics of the target, the land cover characteristics, the rate of deformation, the linearity of deformation, the validity of reference point, the distance of the measurement from the reference point, the uncompensated topography and the atmospheric artifacts, etc. Considering all these factors reveals that the overall quality assessment for PS-InSAR is not a straight forward task and requires an in-depth understanding of these issues. These parameters are variable for diﬀerent areas and diﬀerent deformation mechanisms. More details about the quality of the dike monitoring results can be found in chapter 5.

POSEIDON, ﬁnal report 17 November 2006 Chapter 4

Estimation of dike deformation parameters

In this chapter the PS-InSAR technique and the application to measure deformation of dikes come together. A deformation normally has components in North, East and Up-direction. However, radar only measures the deformation in the direction of the radar LOS. In general there are two approaches to solve the unknown components of the deformation; namely forward and inverse modeling. Inverse modeling solves the unknowns based on the available measurements. Forward modeling determines how the radar observations will look like, when the deformation is given. Both techniques are introduced and discussed in this chapter. Before the used models are presented, the ﬁrst section treats the question which deformation mechanisms can be detected that cause the measured deformation. Some cannot be detected at all, for others the probability of detection might be low. This determines which deformation mechanisms are actually modeled. The second section is about the application of forward modeling, followed by inverse modeling.

4.1 Detection of deformation mechanisms with PS-InSAR

Although radar is very suitable for deformation detection, not all deformation caused by the diﬀerent dike deformation mechanisms can be detected. Also, for some deformation mechanisms the probability of detection is low. This section discusses for all deformation mechanisms whether they can be detected with the PS-InSAR technique or not. To decide which kinds of deformation can be detected, the temporal and spatial behavior of the underlying mechanisms, see section 2.2 and the characteristics of the data acquisition, e.g. the revisit period of the satellite, have to be taken into account.

4.1.1 Discussion of detectability of deformation mechanisms

For this discussion it is assumed that there are PSs, on one or both sides of the dike. Without this assumption there might be no detection and classiﬁcation possible at all. The fact that there are PSs implies that the deformation will be detected. It makes sense that a large scale phenomenon, i.e. strong spatial correlation, is easier to detect than a small scale phenomenon, i.e. no spatial correlation. This is because of the fact that the probability that there is a PS, inﬂuenced by the deformation mechanism, is larger for a large scale phenomenon. So, a strong spatial correlation increases the probability of detection. This probability determines whether it makes sense to model a certain deformation mechanism or not. Table 4.1 summarizes the results of this discussion.

31 32 CHAPTER 4. ESTIMATION OF DIKE DEFORMATION PARAMETERS

Deformation mechanism Detectable Deformation due to a precursor sliding Yes Deformation due to a precursor sliding of the inner slope Yes Deformation due to a precursor sliding of the outer slope Yes Deformation due to erosion of the top and inner slope No Deformation due to erosion of the outer slope No Deformation due to erosion of the foreland No Deformation due to piping No Deformation due to seepage Yes Deformation due to sliding of the protective cover Yes Horizontal deformation of a dike Yes Settlement Yes Subsidence Yes Swelling Yes

Table 4.1: Deformation mechanisms potentially detectable with PS-InSAR.

Deformation due to a precursor sliding: Sliding of the whole dike results in large deformation (meter level) in a short time period. This deformation is very large with respect to the radar wavelength. Because of unwrapping problems and temporal decorrelation, the probability of detection is very small, assuming that the coherence is the same. Here, the inﬂuence of the spatial correlation is not taken into account. The probability of detection becomes larger for a spatially correlated signal. However, sliding announces itself by a small elastic and plastic deformation in the horizontal and vertical plane. Note that this only holds true for peat dikes. The fact that there is some spatial correlation makes the probability of detection of these kinds of deformation likely. This probability also increases when this eﬀect can be measured on both sides of the dike.

Deformation due to a precursor sliding of the inner slope: Also a sliding of the inner slope results in a large deformation (meter level) in a very short time period. Because of the same reasons as for deformation due to a precursor sliding, the probability of detection of these kinds of deformation is very low. However, normally this process announces itself by a small deformation over a certain time period, which might be a couple of years. The fact that there is some spatial correlation makes the probability of the detection of these kinds of deformation high. The assumption that there are PSs on the inner side of the dike, might be a problem when the slope is fully covered with grass, which is mostly the case for the inner slope.

Deformation due to a precursor sliding of the outer slope: Sliding of the outer slope is in fact the same process as sliding of the inner slope, only this process takes place at the other side of the dike. Using the same argumentation, it can be stated that the detection of these kinds of deformation has a high probability.

Deformation due to erosion of the top and inner slope: Erosion of the top and the inner slope of the dike is a local process, so the spatial correlation is low. When the inner side and the top of the dike are fully covered with grass, which is the case most of the times, this deformation is hardly detectable because of the low amount of PSs there, i.e. vegetation has a bad coherence. Only when there is an object on the dike that gives a good reﬂection, the deformation can be seen. Also these kinds of deformation are due to extreme circumstances, like overﬂowing and wave overtopping. Normally, this only happens when there is a high water level in combination with a strong wind. It is common practice to inspect the dikes after such circumstances, so the damage will be detected and repaired if necessary as soon as possible. A possible detection can be seen as a jump or a loss of coherence in the time series. When the deformation is large with respect to the radar’s wavelength, the probability of detection becomes very small due to a possible unwrapping error. Concluding, it can be said, that this deformation mechanism might be detected, but the probability of detection is low.

Deformation due to erosion of the outer slope: The diﬃculties with the detection of erosion of the outer slope are more or less covered in the discussion about the erosion of the inner slope. But also another

POSEIDON, ﬁnal report 17 November 2006 4.1. DETECTION OF DEFORMATION MECHANISMS WITH PS-INSAR 33

eﬀect is important: the erosion of the outer slope is likely to be under water, so it is not detectable with radar anyhow.

Deformation due to erosion of the foreland: Erosion of the foreland takes place below water level most of the time, so it cannot be detected with radar at all.

Deformation due to piping: Deformation due to piping is a very local eﬀect, which causes holes in the land close to the dike. When there is a PS in or close to this hole it may be detected. However, the fact that this deformation is spatially uncorrelated and that the probability that a PS coincides with a hole is low, gives a low probability in the detection of deformation due to piping.

Deformation due to seepage: Seepage can theoretically be measured with radar. A high water level over a longer time period will push the ground water table behind the dike upwards, which may result in a small elastic uplift of the land behind the dike. When the water level gets back to its normal level, the land gets also back to its normal state. This can be seen as an outlier in the time series. Notice that normally these periods of a high water level are maximally a few weeks. A revisit period of 35 days reduces the probability of detection.

Deformation due to sliding of the protective cover: Sliding of the protective cover is mostly a relatively slow process over a stretch of dike. The fact that there is some spatial correlation, gives a high probability of detection for this kind of deformation.

Horizontal deformation of a dike: A horizontal deformation of a dike can have several causes. First, there is a deformation due to a high water level which causes a more or less elastic, horizontal deformation of a dike stretch. However, a small plastic deformation is not excluded. Also nipping ice can cause a horizontal deformation for a stretch of dike, but this is only true for small dikes. The elastic deformation will look like an outlier in the time series. However, these kinds of deformation can be large with respect to the radar wavelength, which makes the probability of detection very low. Normally a high water level is just a few weeks, while the revisit period of the satellite is ﬁve weeks. This will also decrease the probability of detection. The plastic deformation has a high probability to be measurable with radar. First of all the eﬀect is measurable on both sides of the dike, secondly there is spatial correlation.

Settlement: Settlement is a process that occurs on the whole dike and even on the land behind the dike and on the outer foreland. Partly, the deformation is due to compaction of the dike itself, partly because of compaction of the underneath soil layers. The magnitude of settlement depends on the age of the dike. When the dike becomes older, the settlement becomes less. The fact that this eﬀect can be measured on both sides of the dikes, in combination with the spatial and temporal correlation gives a high probability in detecting these kinds of deformation.

Subsidence: Subsidence is usually a spatially and temporally correlated phenomenon, which covers a whole area, so not only the dikes. Many studies have proven that this type of deformation is quite well measurable with radar, see for instance [44], [52] and [61].

Swelling: In the case of swelling, the dike becomes saturated with water due to rain or a high water level. This may results in deformation of the whole dike or only one side of the dike. The fact that this eﬀect can be measured on both sides of the dikes, in combination with the spatial correlation makes the detection of these kinds of deformation likely.

4.1.2 Superposition of deformation mechanisms

The interpretation of the detected deformation becomes more difficult when there are more than one deformation mechanisms acting on the dike. The PS displacement is in this case a superposition of displacements due to different deformation mechanisms. In practice, this is not unlikely; a new built dike has always deformation due to settlement. But at the same time it is possible that there is also a deformation due to a high water level, or deformation due to seepage. However to show the effect of each deformation mechanism, the developed models assume only one cause of deformation.

POSEIDON, ﬁnal report 17 November 2006 34 CHAPTER 4. ESTIMATION OF DIKE DEFORMATION PARAMETERS

4.2 Forward modeling

Most models in real life applications contain more unknowns than observations, which implies that the system is not solvable. One method to deal with this situation is forward modeling, which will be discussed in this section. It starts with an introduction of the concepts of forward modeling. Some general considerations are made about forward modeling with respect to inverse modeling. After that the model deﬁnition and the general input parameters are described, even as the developed models for the relevant deformation mechanisms, as identiﬁed in section 4.1, are discussed.

4.2.1 General considerations about forward modeling

In general, with forward modeling one tries to determine what a given sensor would measure in a given formation and environment. Generally, this is done by applying a set of theoretical equations to the sensor response. This set of theoretical equations (the forward models) can be 1D, 2D or 3D. The more complex the geometry, the more factors can be modeled, but the longer the computing time will be.

In the case of the detection of dike deformation, the sensor is the radar and the forward models are the feasible deformation mechanisms. In chapter 3 it is stated that the radar cannot measure the full deformation vector, which contains the deformation in the North (Y), East (X) and Up (Z) direction. It only measures the deformation in the radar LOS. This means that with inverse modeling some assumptions about the direction of the deformation have to be made. Another option could be that forward modeling is used to determine the full deformation vector. Forward modeling also requires assumptions, for instance on the validity of the used model for a particular situation. Another important question is whether the models are a good description of the reality.

4.2.2 General input parameters

In this section the used simple model and the general parameters are described.

Figure 4.1: A dike body’s cross-section of the used model.

For the discussion of the different models, a very simple model is specified that represents a dike. Figure 4.1 shows a cross section of this model. The slopes are specified by γ, the base width of the dike is specified by l (in meters) and the crest height of the dike by h (in meters). The three general parameters are the direction of the length axis of the dike, the heading of the satellite and the incidence angle, each of them will be briefly explained.

Direction of the length axis of the dike: The orientation of the length axis of the dike determines its sensitivity for the radar LOS deformation. Assume for instance that the orientation of the length axis of a dike is perpendicular to the satellite’s orbit. Now the radar is not sensitive for a deformation in the

POSEIDON, ﬁnal report 17 November 2006 4.2. FORWARD MODELING 35

direction parallel to this orbit, because the radar LOS vector is perpendicular to the direction of the movement.

Heading of the satellite: The heading of the satellite is specified as the azimuth (αh). This parameter specifies whether the satellite is in an ascending or a descending orbit. Assume that a dike lies parallel to the orbit of an ascending satellite. A deformation away from the satellite perpendicular to this orbit is than seen as a motion towards the satellite in a descending orbit. In other words, the sign of the deformation is reversed, see figure 4.2.

Incidence angle: The other parameter related to the satellite is the incidence angle (θ). The incidence angle is the angle between the radar beam incident on a surface and the line perpendicular to the local vertical of the ellipsoid, see ﬁgure 4.2.

Figure 4.2: A deformation away from a satellite in an ascending orbit perpendicular to this orbit, is seen as a motion towards a satellite in a descending orbit. The dashed line illustrates the dike after deformation. It can be clearly seen that the distance from the earth to the satellite is increased for an ascending satellite while it is decreased for a descending satellite.

4.2.3 Modeling of deformation mechanisms

In this section the diﬀerent models of the relevant deformation mechanisms will be presented. First some general considerations about the way of modeling are discussed, followed by a description of the input parameters.

Deformation due to a precursor sliding: One of the indicators of a precursor sliding is compaction of the dike in combination with an elastic horizontal displacement. For the compaction of the dike the same model is used as for settlement. For the horizontal deformation the same model is used as for the horizontal deformation of a dike. The deformation due to a precursor sliding is a combination of those two processes. The deformation magnitude can be specified by the use of two parameters. The first parameter dz top (see figure 4.3), specifies the deformation of the crest of the dike in the vertical direction. Notice that the deformation magnitude is maximal at the top and zero at the foot of the dike. For every point between those points a linear relationship is assumed. The second parameter dx top (see figure 4.3), specifies the deformation of the crest of the dike in horizontal direction. Also here the deformation magnitude is maximal at the top and zero at the foot of the dike. For every location between those points a linear relationship is assumed.

Deformation due to a precursor sliding of the inner slope: Deformation due to a precursor sliding of the inner slope has components in the vertical direction and in the direction perpendicular to the length-axis of the dike. It is assumed that the length of the deformation vector is the same over the full width of

POSEIDON, ﬁnal report 17 November 2006 36 CHAPTER 4. ESTIMATION OF DIKE DEFORMATION PARAMETERS

Figure 4.3: Model of a deformation due to sliding.

the inner slope. However, the decomposition into two components depends on the distance to the top of the dike. In figure 4.4 this decomposition is visualized. Here α is the parameter that depends on the distance to the dike’s length axis. A point on the crest of the dike only deforms in the vertical direction (α = 90), a point on the foot of the dike only deforms in the direction perpendicular to the length-axis of the dike (α = 0). The deformation magnitude can be specified by the use of the parameter dSlope which is the deformation vector parallel to the slope, (see figure 4.4). How this will look in practice is visualized in figure 4.5.

Figure 4.4: The decomposition of the deformation vector.

Figure 4.5: Model of a deformation due to sliding of the inner slope.

Deformation due to a precursor sliding of the outer slope: This type of deformation mechanism uses the same model as the one that is used for the sliding of the inner slope of the dike. The only difference is that the process takes place at the outer side of the dike. Figure 4.6 visualizes how this type of deformation is modeled. Deformation due to seepage: When the water level is high, water pressure can cause seeping of water under the dike. This may cause an uplift of the land behind the dike. It is assumed that the uplift is the same for the whole area behind the dike. The deformation magnitude can be specified by the parameter dz foreland (see figure 4.7), which specifies the uplift of the land behind the dike. Deformation due to sliding of the protective cover: The sliding of the protective cover is modeled as a deformation along the slope of the dike. Because of the fact that the inner slope of the dike is mostly covered by grass, the model assumes this kind deformation only at the outer slope of the dike. A

POSEIDON, ﬁnal report 17 November 2006 4.2. FORWARD MODELING 37

Figure 4.6: Model of a deformation due to sliding of the outer slope of the dike.

Figure 4.7: Model of a deformation due to seepage.

deformation along the slope has components in the vertical direction and in the direction perpendicular to the length-axis of the dike. The magnitude of these components depends on the slope angle of the dike. The deformation magnitude can be speciﬁed by the use of the parameter dSlope which is the deformation vector parallel to the slope. How this will look in practice is visualized in ﬁgure 4.8.

Figure 4.8: Model of a deformation due to sliding of the protective cover.

Horizontal deformation of a dike: To model this kind of deformation, the assumption is made that the amount of deformation of a certain point only depends on the height of the dike. This implies that the maximum amount of deformation can be found at the crest of the dike. At the foot of the dike, there is no deformation at all. For every point between those points a linear relationship is assumed. Another assumption is that there is only deformation in the direction perpendicular to the length-axis of the dike. Figure 4.9 shows the consequence of this way of modeling, i.e. only the steepness of the inner and outer slope changes. The inner slope becomes steeper, while the outer slope becomes less steep. The deformation magnitude can be specified by the parameter dx top (see figure 4.9), which specifies the deformation of the crest of the dike in horizontal direction.

Settlement: Settlement results in two diﬀerent kinds of deformation. First, there is a deformation due to a compaction of the dike itself. Secondly, there is a deformation due to a compaction of the layer underneath. Here it is assumed that the compaction of the dike itself, for a certain point, only depends on the height of the dike for that particular point. This means that this deformation is maximal at

POSEIDON, ﬁnal report 17 November 2006 38 CHAPTER 4. ESTIMATION OF DIKE DEFORMATION PARAMETERS

Figure 4.9: Model of a deformation due to horizontal deformation.

the top and zero at the foot of the dike. For every point between those points a linear relationship is assumed. Then there is a deformation due to compaction of the soil layer underneath the dike. The total deformation is the sum of these two independent components, and its magnitude can be speciﬁed by the parameters dz top and dz base (see ﬁgure 4.10).

Figure 4.10: Model of a deformation due to settlement.

Subsidence: In case of subsidence not only the dike will deform, but also the surrounding area. In the model it is assumed that the deformation magnitude of the dike and the surrounding area is the same and that there is only deformation in the z-direction. The deformation magnitude can be speciﬁed by the parameter dz sub (see Figure 4.11), which speciﬁes the deformation of the top of the dike in z-direction.

Figure 4.11: Model of a deformation due to subsidence.

Swelling: In the case of swelling, the deformation rate can be different for each part of the dike. However, one assumption is that the direction of the deformation is perpendicular to the dike. This means that a deformation of the crest of the dike has only a component in the z-direction. A point on the slope of the dike has a component in the x- and z-direction. In the example, the deformation due to swelling is largest for the outer side of the dike, see figure 4.12. The deformation magnitude can be specified for the inner slope (dinner slope), the top (dtop) and the outer slope of the dike (douter slope). With these models it is possible to calculate the radar LOS, for different heading directions and orientations of the dike. Here equation 4.1 can be used, because all terms are known. This results in a map,

POSEIDON, ﬁnal report 17 November 2006 4.3. INVERSE MODELING 39

Figure 4.12: Model of a deformation due to swelling.

where each grid cell represents a PS. The colors indicate the magnitude of the deformation in the radar LOS.

4.3 Inverse modeling

The goal of inverse modeling is to derive deformation parameters from the observations. So, ﬁrst the PS- InSAR observations and interesting deformation parameters are deﬁned. After that, the mathematical model for inverse modeling is described.

Observations: The PS-InSAR observations are deformation rates in the LOS direction of the satellite. Based on different satellite orbits, there are two kind of observations: observations from ascending orbits, and observations from descending orbits. But instead of using only the estimated linear deformation rates as observations, also all measurements which created the time series of the PSs can be considered as the observations. The main parameters to define these observations, i.e. to define the LOS direction for each observation, are the incident angle and the satellite heading (azimuth). Figure 4.13 shows these two parameters for both ascending and descending observations.

Deformation parameters: The interesting deformation parameters are deﬁned as three deformation components in three directions with respect to a dike. Figure 4.14) shows these three components in the dike coordinate system.

dy: deformation component in the length axis of a dike

dx: deformation component perpendicular to the length axis of a dike

dz: deformation component in up direction (dz=du)

An important parameter to deﬁne the orientation of the above components with respect to the geographical coordinate system (North, East, Up), is the azimuth of the length axis of a dike. Figure 4.14 also shows the relation between the dike coordinate system and the geographical coordinate system.

Now, with these observations and deformation parameters, the inverse modeling problem becomes the decomposition of the observed LOS deformation to the dx, dy, and dz components.

As PS-InSAR observations are only sensitive to the deformation towards or away from the satellite in LOS direction, the observed deformation implies a non-uniqueness. That is, the observations are only the projection of the 3D deformation vector, with the components (dn, de, du) in north, east, and up direction respectively, to one LOS component (dr) (see ﬁgure 4.15) The deformation in the LOS can be calculated with equation 4.1 [37]:

POSEIDON, ﬁnal report 17 November 2006 40 CHAPTER 4. ESTIMATION OF DIKE DEFORMATION PARAMETERS

Figure 4.13: The observation geometry A) Heading of ascending orbit, B) Heading of the descending orbit, C) Incidence angle for ascending orbit, D) Incidence angle for descending orbit

Figure 4.14: A) Dike coordinate system, B) Relation of dike coordinate system and geographical coordinate system.

POSEIDON, ﬁnal report 17 November 2006 4.3. INVERSE MODELING 41

Figure 4.15: Deformation components

3π 3π dr = du cos θ − sin θ dn(cos(αh − ) + de sin(αh − ) (4.1) 2 2

Where: θ incidence angle αh satellite heading dr observed deformation in range direction (LOS) du deformation in Up direction dn deformation in North direction de deformation in East direction

Because of the projection of the 3D deformation vector to the LOS deformation, it is not possible to decompose the observed deformation to the north, east, and up components. Even when using two observations, composition of ascending and descending observations, it is possible to derive only two out of three components (two observation and two unknowns). To be able to retrieve all of the three components, some assumptions about one or two components are necessary, based on some prior knowledge about the characteristics of the expected deformation mechanisms.

Below, three cases of possible observations are considered. For each case, the system of observation equations for the inverse modeling is developed, followed by a discussion about the possible assumptions that should be made.

Case 1: Only one observation (ascending or descending): We ﬁrst consider the case that only one observation is available (ascending or descending). In this case it is possible to assume no horizontal deformation and project the observed deformation in LOS into the vertical component. However, this is not a very realistic assumption for some deformation mechanisms. Therefore, the use of this assumption needs more prior knowledge about the expected deformation. For example, in the case of subsidence, it is likely that there is no horizontal deformation, so the observed deformation is only because of the vertical deformation (dz). Then the second term of equation 4.1 becomes zero. In this case, the observation equation for inverse modeling becomes:

dr = cos θdu (4.2)

Case 2: Two observations (ascending and descending): In this case, we consider that both ascending or descending observations are available. To derive the three deformation components from only these two

POSEIDON, ﬁnal report 17 November 2006 42 CHAPTER 4. ESTIMATION OF DIKE DEFORMATION PARAMETERS

observations, an assumption on one of the three components is necessary. In dike monitoring, as the deformation in the length direction of the dike is not very likely, it is possible to assume zero deformation in this direction (dy=0). With this assumption, it is possible to derive dx and dz from the ascending and descending observations. In order to use equation 4.1 for inverse modeling, it is necessary to transform the deformation in North and East directions into the horizontal deformation parameters(dx and dy). Using the rotation with rotation angle the azimuth of the dike, we have:

de cos γ sin γ dx = a a (4.3) dn − sin γa cos γa dy

Where: dx deformation perpendicular to the lenght direction of dikes dy deformation in the lenght direction of dikes γa azimuth of lenght axis of dike

Using the assumption that dy=0, equation 4.3 becomes:

de cos γa = dx (4.4) dn sin(−γa)

Substitution of 4.4 into 4.1 and using some veriﬁcation, we have:

dr = du cos θ − dx sin θ cos(αh − γa) (4.5)

Using equation 4.5 for both ascending and decending observations, we can write the system of observation equations as:

dasc cos θ − sin θ(α − γ ) = ha a (4.6) ddesc cos θ − sin θ(αhd − γa)

Where: dasc observed deformation in ascending track ddesc observed deformation in descending track αha heading of ascending orbit αhd heading of descending orbit Assuming independent observations, it is possible to write 4.6 as the Gauss-Markov model:

E{y} = Ax; Dy = Qyy (4.7)

Where:

2 cos θ − sin θ(αha − γa) σdesc 0 du A = , Qyy = 2 , x = cos θ − sin θ(αhd − γa) 0 σdesc dx

Finally, the solution of 4.7 gives the estimated deformation parameters (dx and dz) for each PS-InSAR point:

T −1 −1 T −1 T −1 xˆ = (A Qyy A) A Qyy y Qxˆxˆ = (A QyyA) (4.8)

Case 3: More observations (ascending and descending for diﬀerent points): In last case, the observation equation for only two observations was derived. Despite the fact that there are only two possible observations for each PS, with some assumption about the spatial behavior of the expected deformation mechanisms, it is possible to use more observations for the estimation of the deformation parameters. Using more observations will also increase the accuracy of the ﬁnal estimation of the parameters. Lets assume homogeneous deformation mechanisms. This means that the deformation parameters are the same for the whole, or some interesting part of the dike. Then the unknown parameters (dx and dz)

POSEIDON, ﬁnal report 17 November 2006 4.3. INVERSE MODELING 43

for all PSs on that part of the dike become the same, while we can use all observations of these PSs in our system of observation equations:

dasc1 cos θ − sin θ(αha − γa)  dasc2   .  . .      .   .      dz E{ dascm } =  cos θ − sin θ(αha − γa)      dx  ddasc1   cos θ − sin θ(αhd − γa)       ddasc2   .       .   .       ddascn   cos θ − sin θ(αhd − γa)     

2 σdasc1 2  σdasc2  .    .   2  D{y} =  σdascm  (4.9)  2   σddesc1   2   σ   ddesc2   .   2   σ   dascn  The solution of the equation 4.9 is (using Best Linear Unbiased Estimation (BLUE)):

T −1 −1 T −1 T −1 xˆ = (A Qyy A) A Qyy y Qxˆxˆ = (A QyyA) (4.10)

Where: xˆ BLUE of the unknown parameters Qxˆxˆ variance covariance matrix of the BLUE

Sensitivity of observations to different deformation components: As can be seen in equation 4.10, the final precision of the estimated deformation parameters is dependent on the radar acquisition geometry with respect to the dike (A-matrix) and the precision of the observations (Qyy). The precision of the observations is already given as the results of the PS processing. However, the A-matrix depends on geometric parameters such as the incident angle, the heading angles, the number of observations, and the azimuth of the dike. Therefore for different satellites and different orientations of the dike the final precision of the estimated deformation parameters are altered. Assuming uncorrelated observations, with the same standard deviation, we have:

2 T −1 Qxˆxˆ = σ (A A) (4.11)

The square root of the diagonal terms of Qxˆxˆ give the standard deviation of the estimated deformation parameters. If the standard deviation of the observations is equal to one, the diagonal terms provide a measure of the effect of geometry on these estimates in terms of relative measurement error. Figure 4.16 shows this sensitivity for different orientations of a dike in the Netherlands for the ERS satellite. The used parameters in this case are an incidence angle of 23 degrees and a heading of 347 and 193 degrees for ascending and descending orbits respectively. As we expected, the standard deviation of the dx component becomes larger when increasing the azimuth of the dike from 0 to 90 degrees. The reason for this effect is that the sensitivity to the deformation component in North-South direction, e.g. dx when the azimuth of the dike is 90 degrees, is weak due to the near polar orbit of the ERS satellite.

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Figure 4.16: Sensitivity (standard deviation in mm) of estimated deformation parameters to the dike orientation .

POSEIDON, ﬁnal report 17 November 2006 Chapter 5

Case study methodology

In this chapter the methodology is presented that was used for conducting the case studies. It starts with a description of how the case study locations are chosen, followed by an overview of the relevant datasets and their proposed expectations. After that some explanation is given about the georeferencing method and the choice of the reference point. Next some considerations are described about the time series analysis, hypothesis testing and quality assessment. The methodology part ends with a description of the determination of the feasibility of the results.

5.1 The choice of the case study locations

In this section the choice of the case study locations is discussed. This choice was ﬁrst limited by the availability of the radar data. These data were available for parts of the provinces Groningen, Friesland, Noord-Holland and Flevoland. From these areas, the locations were chosen where the dikes were visible, mainly focusing on that dikes that belong to the primary water barriers, i.e. the dikes along the IJsselmeer and the Waddenzee. A closer look at these images already made clear that some interesting features were visible. This resulted in the following list of potential case study locations:

• The IJsselmeer dikes around the Noord-Oostpolder;

• The dikes around the island of Marken;

• The dikes around the complex of Kornwerderzand;

• The dike near Harlingen;

• The IJsselmeer dikes near Lelystad in Flevoland;

• The dike near Lauwersoog;

• The dike near Delfzijl.

Selection of the case study was based on available data, amount of interesting locations and the time limitations of the project. Finally the ﬁrst four case studies where chosen.

45 46 CHAPTER 5. CASE STUDY METHODOLOGY

5.2 Data gathering

The datasets that might be interesting for the analysis of the case studies will be discussed in this section. A more detailed description of the datasets can be found in Appendix A. The datasets below are listed in the order of importance.

Radar data This dataset contains an overview of the used images, the Multi Reflectivity Map (MRM), a file with the location, height, deformation and coherence for every PS. Also the time series of the atmospheric residuals and the time series for the non linear movements are included. The MRM is used to distinguish between the main points and sidelobes. The other files are used to generate the time series and calculate the parameters of interest. Topographical map 1:10.000 The topographic vector map (Top10vector) is used as a topographical background. This map is used for georeferencing of the PSs if no better alternatives where available. It also provides an overview of the area of interest and gives information about objects close to the dikes, this is used to derive the causes of the reflection. DTB-wet and DTB-dry The Digital Topographical Files (DTB) of the wet and dry infrastructure at scale 1:1000 together form the DTB2000. These datasets contain very detailed and precise information about the geometry of dikes and highways. This makes these datasets very useful for the georeferencing of the PSs. It also provides detailed information about the objects on and close to the dike, this is used to derive the causes of reflection. Validation datasets Validation datasets, for instance leveling, tachymetry or GPS data, can be used to validate the PS-InSAR technique. AHN The estimated heights of the PSs can be used for the georeferencing of the PSs, i.e. to decide whether the reflection comes from the top or foot of an object. Geotechnical profiles These profiles show the structure of the subsurface of the dike and the underlying soil layers. It might be that the measured deformation is related to the soil type below the dikes. The geotechnical profiles can be used to verify this hypothesis. Soil map and borehole measurements Both the soil map (scale 1:50.000) and borehole measurements can be used as an alternative when no geotechnical profiles are available. The soil map only provides information about the first meter below the surface, borehole measurements contain very detailed information about the subsoil layers, but only for the borehole locations. Technical drawings Technical drawings of a dike give information about the structure of dike; cross profiles, information about the used materials, foundation, etc. This information possibly helps with the interpretation of the PSs. Aerial photography Available aerial photographs (also accessable from Google-Earth) can be used to get a first impression of the areas of interest; a first indication what causes the PSs can be given. Time series ground water levels These time series show the fluctuations in the ground water level for some points. It might be that the measured deformation is related to the fluctuations in the ground water level. The time series can be used to verify this hypothesis. Time series water level IJsselmeer These time series show for some points the fluctuations of the water level in the IJsselmeer. It might be that the measured deformation is related to the fluctuations in water level. The time series can be used to verify this hypothesis.

5.3 Preparation of the data

Before starting the interpretation of the radar data, some preparation steps have to be conducted, namely: the georeferencing and the selection of a new reference point. Both steps will be discussed in this section.

POSEIDON, ﬁnal report 17 November 2006 5.4. TIME SERIES ANALYSIS 47

5.3.1 Georeferencing

To determine which object is causing the scattering, it is essential to georeference the PSs. The PSs, which where supplied in the ’Rijksdriehoeks’ (RD) reference system, are shifted with respect to their true locations because of an error in the starting time of the acquisition by the ERS satellite. This shift is the same for all the PSs in one radar image and can be up to hundreds of meters. In a normal georeferencing procedure, ground control points are selected to ensure an accurate georeferencing. Ground control points are geographical features of known location that are recognizable on images and can be used to determine the geometrical correction. However, for this research such ground control points (like corner reﬂectors) are not available. This reduces the accuracy of the georeferencing. In this project, the radar data is georeferenced with respect to a topographical dataset. The procedure for both ascending and descending dataset consists of the following steps:

• Selection of coordinates for at least 2 corresponding points in the PSs dataset and the used topographical background map, like the DTB-wet or the Top10vector;

• Calculation of the mean shift in the coordinates between these corresponding points;

• Apply the shift to the PSs.

After this procedure, the standard deviations of the diﬀerences between the old coordinates and the transformed coordinates for the control points are calculated. This standard deviation represents the relative precision of the georeferencing. The absolute precision is assumed to be equal to the precision of the used dataset.

5.3.2 Selection of the reference point

The estimated deformation with the PS-InSAR technique is relative with respect to a certain reference point, i.e. a point with a height, deformation rate and residuals equal to zero, and a coherence of one. The heights, deformation and coherence of all the other points are with respect to this reference point. This point is randomly chosen from a list of points with coherence above a certain threshold. This implies that the reference point in an ascending dataset is independent from the reference point in a descending dataset, which makes the interpretation of the combined datasets not straightforward. For a correct interpretation and a correct derivation of the deformation parameters, the reference points have to be redeﬁned. There are several possibilities to ensure a straightforward interpretation of the combined ascending and descending datasets. First of all, it is possible to choose a stable reference point in both datasets. This method implies the availability of ground truth data, but even when it is clear that a certain area is stable, there is a probability that a point is just noise or an autonomous movement. To overcome this problem, not a single reference point is chosen, but the mean of a number of points in a certain area can be put to zero. Another method is to choose a point that occurs in both the ascending and descending dataset. However, when this point in reality deforms horizontally, the interpretation is again not straightforward. Notice that this eﬀect can be seen in the whole combined dataset, which might be unrealistic. When this is the case, another reference point has to be chosen. In both approaches the values for the deformation rate, heights and residuals of the new reference points becomes zero and the coherence one. All other PSs have to be corrected, to make them relative with respect to the new reference point.

5.4 Time series analysis

In this step, we visualize the deformation time series for each PS point which was detected as deformation in the last step. Some characteristics of these time series are visually analyzed to check the validity of linear model, and to check other possibilities for phase unwrapping.

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Figure 5.1: Linear model vs. alternative models.

Validity of linear model: The time series are visually checked to see whether the linear model is valid or not. We also check for a possible alternative model for some particular time series. Figure 5.1 shows the example of time series with a linear model and two alternative models.

Check Phase Unwrapping: We visually verify the other possibilities for phase unwrapping. This means that we visualize not only the estimated deformation time series but also these time series with + and - one cycle (in our case 28 mm), to see whether any other possibility for phase unwrapping is likely or not. Figure 5.2 shows this visualization. In these time series, red points show the results of the current phase unwrapping solution. Blue and black points respectively show the time series with + 28 mm and - 28 mm. For example, we verify whether the alternative solution for phase unwrapping (dashed line) is feasible or not.

5.5 Detection of deformation

The goal of this step is to ﬁnd or detect the PSs on the dike that show deformation. For each PS point, there are four possibilities:

Outliers: These are PSs that contain only noise. These points are the result of type II errors of PS processing (3.3.2) which are regarded as coherent points and detected as PS, but actually they are not. These falsely detected PSs are spatially uncorrelated (isolated points), usually with a high deformation rate, low coherence and without sidelobes. Autonomous movements: These points are the results of an autonomous deformation of one PS. These PSs are spatially uncorrelated, usually with sidelobes. Interpretation of these autonomous movements needs more investigation. Deformation: The PSs that show spatially correlated behavior on dikes, with absolute deformation rate larger than 1 mm/year can be classiﬁed as deformation areas. These points usually have sidelobes. Stability: Stable points can be deﬁned as points that have an absolute deformation rate smaller than 1 mm/year. These points are usually spatially correlated and have sidelobes.

Based on their spatial behavior (correlation), deformation rate and sidelobes, PSs can be classiﬁed to one of these four classes. Outliers are detected based on uncorrelated behavior, high deformation rate and bad coherence. The other three classes can be subdivided in two hypotheses:

Null-hypothesis: point is stable (no deformation) Alternative hypothesis: the point is not stable.

POSEIDON, ﬁnal report 17 November 2006 5.6. CLASSIFICATION OF DEFORMATION 49

Figure 5.2: Other possibilities for phase unwrapping.

If the null-hypothesis is rejected, so the point is not stable, we will test whether the detected deformation is spatially correlated or not. If not there are autonomous movements. In general, the decision between autonomous movement and deformation is not very straight forward and needs more consideration. It is possible that some deformation mechanisms are local deformation and show the same behavior as autonomous movements. Figure 5.3 shows the decision tree for this classiﬁcation.

5.6 Classiﬁcation of deformation

The goal of this step is to decide for each detected deformation area which deformation mechanism is feasible and classify the detected deformation in diﬀerent deformation mechanisms. The important factors for this decision are:

1. Difference in ascending and descending observations (due to the horizontal movements, or deformation in only one side of the dike). 2. Spatial correlation of PSs with points close to the dike. That is, we investigate whether only the points on dikes show deformation or also the points close to the dike (e.g. for subsidence it is more likely that the points close to the dike also show deformation). 3. Magnitude of deformation rate. (different deformation mechanisms have different magnitude) 4. Temporal behavior: From time-series analysis, temporal behavior of the detected deformation can be derived. 5. Deformation direction: using inverse models, it is possible to derive vertical and horizontal deformation. (Only in cases that we have both ascending and descending observation).

Figure 5.4 shows these factors for different deformation mechanism. Based on their difference in these factors, PSs can be classified to different mechanisms. Figure 5.5 shows the decision tree for this classification in the

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Figure 5.3: Decision tree for deformation detection.

Figure 5.4: Characteristics of deformation mechanisms.

POSEIDON, ﬁnal report 17 November 2006 5.7. QUALITY ASSESSMENT 51

Figure 5.5: Decision tree deformation classiﬁcation: two observations

Figure 5.6: Decision tree deformation classiﬁcation: one observation case that both ascending and descending observations are available. In the situation that only one kind of observation (ascending or descending) is available, with assumption that horizontal deformation is zero, we can classify the detected deformation (see ﬁgure 5.6).

In addition to these factors, which are only based on radar observations, there is also other information. Examples of these kinds of information are: soil maps, technical drawings of dikes, water levels, etc. These can also be used to interpret the detected deformation and to assign it to one of the deformation mechanisms.

5.7 Quality assessment

Quality as deﬁned in geodesy is divided into internal and external precision and internal and external reliability. The internal precision says something about the dispersion of the estimated measurements, while the external precision is the dispersion of the estimated unknown parameters. Internal reliability is a measure of the model

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error that can be detected with a certain probability, whereas the external reliability is deﬁned as the inﬂuence of this model error on the estimated unknown parameters. Precision and reliability are independent components of the quality description. A high precision of the measurements does not imply a reliable estimation of the unknown parameters and vice versa. Because of the fact that the time series cover a long time span, even with large noise in the observations, it is easy to obtain a deformation rate with a high precision, assuming that the deformation is linear over time. However, this assumption is not necessarily true and has to be checked with hypothesis testing, which is a reliability aspect. The temporal distribution of the measurements and spatial distribution of the PSs are regarded as deterministic quantities. Also the ambiguities are assumed to be known and deterministic. In this section the internal and external precision are discussed. For this project the reliability of the linear model is tested with the Global Overall Model test. This is described at the end of this section.

5.7.1 Internal precision

The internal precision describes the dispersion of the estimated measurements. This is calculated using the propagation law of the variances.

Where Qxˆxˆ is given by: T Qyˆyˆ = AQxˆxˆA (5.1) T −1 −1 Qxˆxˆ = (A Qyy A) (5.2) Where:

A = The design matrix Qyˆyˆ = The variance-covariance matrix of the estimated observations Qyy = The variance-covariance matrix of the observations Qxˆxˆ = The variance-covariance matrix of the estimators

In the case of this project, the observations are not the raw observations, as they are acquired by the satellite. Here, the time series for all the PSs, i.e. the deformation for diﬀerent epochs with respect to t = 0, is regarded 2 2 as the observations, collected in the measurement vector y, with D(y)= 4 × Im mm . For corner reﬂectors the variance equals 22 (see [43]). However for natural scatterers this value is larger, here we choose 42.

Based on these observations, the deformation rate is estimated. In that case, the design matrix A, is given as: T A = (t1 ... tm) , assuming that for t = 0, the deformation is also zero. The estimated deformation rates are used to derive the deformation parameters dx and dz, see section 4.3 on inverse modeling.

2 When the variances of the estimated deformation rates vî are given by σvî ,Qyy becomes a diagonal matrix 2 with on the diagonal the variances σvî . Here i equals the number of PSs that is taken into account. It is assumed that the deformation rates are uncorrelated, that is not the case because of atmospheric effects and unwrapping, see [53]. Normally these values are computed during the processing, however, they were not available yet.

5.7.2 External precision

The external precision describes the dispersion of the estimated unknown parameters. In this project, the estimated unknown parameters are the deformation rates of each PS. When inverse modeling is used to derive the deformation parameters, dx and dz are the estimated unknown parameters, see also section 4.3 on inverse modeling.

The precision of the deformation rate (vˆ) depends on the number and precision of the observations, but also on the temporal distribution of the observations. In fact the precision of the estimated deformation rate is the same for all PSs. This is because of the fact that all PSs have observations in the same epochs, so the

POSEIDON, ﬁnal report 17 November 2006 5.8. FEASIBILITY 53

number and the temporal distribution of the observations are the same. Also the precision of the observations, described by the diagonal matrix Qyy, is the same. The precision of the deformation rate given by the variance 2 T −1 −1 T σvˆ, is calculated with the propagation law of the variances: Qxˆxˆ = (A Qyy A) , with A = (t1 ... tm) . For the precision of the deformation parameters computed with inverse modeling, see section 4.3 on inverse modeling.

5.7.3 Global Overall Model test

The internal reliability is a measure of the model error that can be detected with a certain probability. In other words: the internal reliability describes the performance of the statistical testing of the observations [48]. In this section, the Generalized Likelihood Ratio (GLR) test is used [48]. One possible model error is the error that the linear model is not valid. So, during the testing procedures, this alternative hypothesis Ha has to be tested against the null hypothesis H0 that the linear model is correct. Here the Global Overall Model (GOM) test is used, this is a general test on discrepancies between the observations and the assumed model. This means that the whole vector of observations is checked, but without having a speciﬁc error signature in mind. In this test, the number of independent errors (q) equals the number of observations (m) minus the number of unknowns (n). This implies that there is no redundancy in the alternative hypothesis so the vector with the residuals eˆa becomes zero. In that case, the test statistic T q = m − n can be written as:

T −1 T q=m−n = eˆ0 Qyy eˆ0 (5.3)

The test statistic T q=m−n is distributed as:

2 2 H0 : T q=m−n χ (m − n, 0) , Ha : T q=m−n χ (m − n, λnc) (5.4)

2 Where χ is the Chi-square distribution and λnc is the non-centrality parameter. The null hypothesis will be rejected when:

2 T q=m−n > χα(m − n, 0) (5.5)

Notice that only the GOM test is not sufficient to reject the null hypothesis. Rejection can be caused either by large (functional) errors in the observations (that are not covered by H0), an inappropriate model (H0) for the data at hand, or by a poor specification of the observables noise characteristics in the stochastic model (through matrix Qyy), [48]. In the context of this project, it can be that the deformation is not linear at all, or only for a certain period and not the whole time span. Also outliers in the observations can affect the Overall Model test.

5.8 Feasibility

The optimal product validation is a direct comparison with independent ground based methods such as leveling, tachymetry or GPS, these are the most widely used methods nowadays. The ﬁrst thing to do, is the visual comparison between the measurements, check if they show deformation at the same locations. Notice that the PSs are relative with respect to the reference point. So a possible uplift in the PS-InSAR measurements, while the validation dataset shows subsidence, can be due to a large subsidence of the reference point. To compare the magnitude of the deformation, the deformation in the radar line of sight has to be decomposed in the North, East and Up direction. Here inverse modeling can be used. After that, a scatterplot of both datasets can be made to visualize their correlation.

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However direct comparison is not always possible, because of a lack of quantitative data. For this project images are used from the period 1992-2001, these are already 5 to 15 years old. From the start of the measurements until now lots of things have changed; people left the company, organizations are reorganized etc. However, it is possible to provide qualitative information such as the spatial limits of the deformation area, an approximate assessment of the maximum deformation, the location of damage etc. These statements can be veriﬁed by local experts. For sure this gives no hard numbers like they can be derived with validation datasets.

POSEIDON, ﬁnal report 17 November 2006 Chapter 6

Case studies

6.1 Introduction

In this chapter describes the case studies that we performed, which are Harlingen, Kornwerderzand, Marken and Noordoostpolder. For each case study the methodology is described. This includes a description of the deformation that the radar detects, the analysis of timeseries which follow from the persistent scatterers, estimation of deformation parameters and classiﬁcation of the deformation. The methodology is followed by a section on quality assessment of the measurements and each case study concludes with an overview of the results.

6.2 Case study Harlingen

In this section an overview is given on the results of the case study of Harlingen. Information on the history of the area and the used data can be found in appendix B. This section start with a description of the detected deformation. Finally the results and conclusions with respect to this case study are given.

6.2.1 Detection of deformation

If a histogram is made of the deformation rates in ascending track of the Harlingen area, this leads to ﬁgure 6.1. It can be seen that next to the main peak in the histogram, there is an additional smaller peak on the left hand side. This is what is expected because of the fact that there is a subsidence bowl in the area, this will be further explained in the following section. What also can be seen is that the mean of the histogram is about + 5 mm/year of deformation. This is not very realistic, the hypothesis is that there is mostly subsidence and very little uplift.

In the descending track (see ﬁgure 6.2), the subsidence bowl is not visible as a second peak, but more as a shallower slope on the left hand side of the main peak. Using the assumption that only very little uplift can occur, the total data set can be shifted so that the main peak of the histogram now has very little, or no, deformation. The result of this shift is presented in the ﬁgures 6.3 and 6.4.

Clear is that the result is similar in both tracks. The area is generally quite stable, with exception of the points in the subsidence bowl. Especially in the ascending track, subsidence of up to 40 millimeters occurs. An overview of all data is presented in ﬁgure F.8.

55 56 CHAPTER 6. CASE STUDIES

Figure 6.1: Deformation rate in ascending track Figure 6.2: Deformation rate in descending track

Figure 6.3: Shifted deformation rate in ascending Figure 6.4: Shifted deformation rate in descend- track ing track

Triangles facing upwards are measurements in the ascending track, whereas triangles facing downwards are measurements taken in the descending track. A triangle with a large triangle around it is signiﬁcant deformation. This is deformation of more than 30 mm/year.

The yellow points are stable points, the dark blue points have a large deformation. There is a dark blue area in the middle of the ﬁgure, with some lighter blue points around it. Outside this area more yellow points can be found. This is the subsidence bowl. It can be seen that there is a part of the dike that is also deforming. A comparison with the actual subsidence bowl is made in the next section.

Reference data

The subsidence near Harlingen is monitored by a permanent GPS station in the center of the subsidence bowl. Furthermore each year a leveling campaign is conducted. The estimated absolute subsidence due to salt mining from 1995 until 2005 in the area is shown in ﬁgure 6.5.

From ﬁgure 6.5 it can be seen that the primary dike along the coast has an estimated absolute subsidence of 20 to 70 mm in 10 years. This leads to an approximation of the subsidence of 2 to 7 mm per year. This is respectively 1.8 mm and 6.4 mm per year in the radar LOS.

The stretch of dike with more deformation than 60 millimeter a year is about 10 kilometers long, and lies approximately 15 kilometers to the north of Harlingen. This is in correspondence with the area that subsides

POSEIDON, ﬁnal report 17 November 2006 6.2. CASE STUDY HARLINGEN 57

Figure 6.5: Estimated absolute subsidence due to salt mining [24] with more than 5 millimeter a year in the radar image (Line of Sight deformation).

6.2.2 Quality assessment

The input parameters for the Overall Model test are a standard deviation the measurements of 6 mm. This is a relatively large number. The reason for this is probably the subsidence in the area, which leads to a coherence which is somewhat less than average. The signiﬁcance level is set to 90%.

As can be seen in the ﬁgures F.9 and F.10, the ascending and descending track measurements are of similar quality. About the same percentage is accepted.

The plots on the standard deviation of the residuals from the linear model, ﬁgures F.11 and F.12, show the same behavior as the overall model test ﬁgures. The magnitude of the standard deviation is comparable in ascending and descending track.

The series of measurements of these points deliver an estimation of the subsidence rate in the area. Interesting to know is how accurate this estimation is. For the ascending track, the deformation rate is determined by a series of 31 images. The descending track has a larger series of 74 images. The visible eﬀect of this in the accuracy of the estimation is that the descending track velocity is slightly more accurate than the ascending track. Standard deviation of estimated velocity(mm) is for ascending track 0.47 mm/y and for descending track 0.25 mm/y.

A striking thing to see is that the points in the subsidence bowl usually have a bigger standard deviation than the points on the edge of the bowl. This suggests that a linear model is not the best representation for the data. This is interesting because the deformation due to salt mining should be linear [24]. The non linearity of the data can be explained with the time interval of the salt mining with respect to the time interval of the radar data. The radar data acquisition started 3 years earlier than the start of the mining, which started in 1995. This causes a non-linear subsidence curve, and thus a larger standard deviation from the linear model in the subsiding area. The eﬀect is visualized in ﬁgure 6.6. Although the estimation is linear, the time series show a sharp turn downwards around day -500.

Another explanation for the worse quality of the points in the subsidence bowl is that the processing methods assume only a small deformation. In the subsidence bowl, the deformation is larger than the radar wavelength. This can lead to erroneous estimation.

The link between the Overall Model test ﬁgures and the standard deviation ﬁgures is clearly visible. Points that are rejected in the Overall Model test, have a high standard deviation as well. This can be explained by the following line of reasoning. A rejected point is usually rejected because of either a lot of noise in the

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Figure 6.6: Example of time series in subsidence bowl

Segment ID Length(m) Orientation angle #PSs #points / km dike w.r.t. between 0 heading and 90 satellite degrees North 680 54 54 69 101 Mid-north 1200 65.5 65.5 35 29 Mid-south 1322 45.5 45.5 137 104 South 2902 32.5 32.5 191 66

Table 6.1: The number of PSs for ascending orbit

observation, or a non linear deformation. In both cases, the standard deviation of the residuals from the linear model will be large. The overall model test will reject these points, because the linear model, which goes into the test, does not ﬁt properly. This leads to a big correlation between both datasets.

6.2.3 The number of Persistent Scatterers

The dikes of Friesland cause a lot of PSs, in the Harlingen case the dikes are somewhat comparable to the situation in the Noordoostpolder (see section 6.5). To study the relation between the orientation of the dike and the number of PSs the same method is used as in the case study of the Noordoostpolder. The dike is divided in straight segments, as can be seen in figure 6.7. For all these straight parts, the orientation of the dike is calculated with respect to the heading direction of the satellite. From the center line of each part of dike, an offset of 30 meter is applied to both sides of this line. This leads to a polygon that represents that part of the dike. After that, the number of PSs is counted for each part, the results can be found in table 6.1 and table 6.2. Notice that the sidelobes are also counted. This number of sidelobes will be significant, but the percentage of sidelobes is likely to be the same for all the different parts. This implies that these numbers might only be used in a relative way.

POSEIDON, ﬁnal report 17 November 2006 6.3. CASE STUDY KORNWERDERZAND 59

Figure 6.7: Division of dikes in straight segments

Segment ID Length(m) Orientation angle #PSs #points / km dike w.r.t. between 0 heading and 90 satellite degrees North 680 207 27 4 6 Mid-north 1200 218.5 38.5 5 4 Mid-south 1322 198.5 18.5 4 3 South 2902 185.5 5.5 134 46

Table 6.2: The number of PSs for descending orbit

It can be clearly seen that the amount of PS-points in the descending orbit is quite low in comparison to the ascending orbit.

In ﬁgure 6.8 the relative dike angle is plotted against the number of points using a logarithmic scale. A relation is not obvious; the hypothesis is that the number of PS-points decreases with an increasing angle (0-90 degrees). But due to the low amount of samples of dike segments this hypothesis can not be tested. This could be further researched by using more stretches of dike with more diﬀerent orientations.

6.2.4 Summary of results

1. The dikes above Harlingen subside likely due to salt extraction 2. The detected subsidence of the dikes due to salt extraction is up to 6 millimeter a year for the area 10 kilometers to the north of Harlingen. This corresponds with the estimated subsidence between 1995 and 2005. 3. The subsidence due to the mining appears to be non linear, but this is mainly due to the time interval of the radar acquisitions.

6.3 Case study Kornwerderzand

This section describes the results of the case study of Kornwerderzand. The research methodology and description of quality of the measurements are presented. Finally the results and conclusions with respect to

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Figure 6.8: Relation between the number of points and the angle between the orientation of the dike and the orbit of the satellite

this case study are given. Some background information on this location is presented in appendix C.

6.3.1 Detection of deformation

This section contains a number of steps. First, the method for identifying outliers is discussed. After this, some interesting locations are listed. A more detailed discussion of these locations concludes the section.

Estimation of deformation parameters and classiﬁcation

In the ﬁnal dataset there are a few points or areas that stick out. The locations of these points are: (see ﬁgure F.13)

• The area near the bridges is interesting. The slope between the two roads which lead to the bridges subsides on the eastern side, while the area on the western side of the bridge appears to experience uplift. • At the sluice, on the southern part of Kornwerderzand there are a number of interesting moving points. The area is quite sensitive to erroneous interpretation, because there are a number of possible outliers in it. • The northern breakwater is also interesting. Descending points on this breakwater experience uplift in the line of sight of the satellite.

The identiﬁed interesting locations will be discussed next seperately.

The bridge As can be seen in ﬁgure F.14, the points near the bridge show some interesting behaviour. The bridge of Kornwerderzand consists of 2 independent halves. The bridges are movable in the horizontal plane. On the eastern side of the bridge a number of PSs are located. These scatterers are all in the ascending track. They are located on a slope in the terrain, in between the two halves of the bridge. The

POSEIDON, ﬁnal report 17 November 2006 6.3. CASE STUDY KORNWERDERZAND 61

scatterers show a relatively large deformation rate, of more than 1 millimeter per year. On the western side of the bridge are some scatterers as well. These scatterers are located on the house of the bridge keeper, and on the walls just beneath the bridge. The most interesting about these points is that they show an inverse motion compared to the eastern side of the bridge; they experience uplift. A visit of the area made clear that there are some signs of this deformation in the field as well. The bridge structure shows a clear crack in the vertical wall on the northeastern side of the bridge. This can be seen in figure F.15 and figure F.16. The photographs are taken from the northeast. These signs are expected if the eastern side subsides, while the western side is stable or even shows uplift. The rupture then occurs due to the characteristics of concrete: it can not handle pulling forces.

The sluice The area near the sluice is interesting, because a number of points show different motion, both in ascending as in descending track. Extra caution is needed in this area, since the image is polluted with points that seem to be erroneous. More on the unreliable points is presented later in the section on quality description. There are two points which experience a big uplift; these can be classified as outliers using the characteristics described in the beginning of the section. They are the dark red triangles in the central part of figure F.17. The house next to the sluice appears to subside, whereas the sluice itself has a number of points which show minor uplift. The uplift is not significant, whereas the subsidence is. This location was not investigated during the case study visit, since the area was not noticed as interesting yet at that stage. Data gathering in later stages did not provide any solutions for this problem.

The northern breakwater This area shows some strange deformation on the eastern half, measured by the satellite when ﬂying a descending orbit. The deformation is in the direction of the satellite, and could be interpreted as uplift or horizontal motion. The likelihood of such an event is not that high, since the data on the other slope shows almost no deformation at all.

6.3.2 Quality assessment

In this section some quality parameters are discussed, speciﬁed on the Kornwerderzand case. The ﬁrst topic are some statistics on the area, after that a number of plots are presented illustrating the results of testing procedures.

Statistics

The total length of dike-like bodies in the area of Kornwerderzand is 8207 meters. This total is a bit doubtful, since a large part of the area consists of breakwaters or plain island. The area of Kornwerderzand is 0.4276 square kilometers.

There are in total 2487 points in the area of Kornwerderzand. It must be noted that a large part of this total number of points are sidelobes. They are hard to separate from the main lobe. All sidelobes are used as observation points. This is possible because we are interested in deformation only, and sidelobes do present an accurate deformation rate.

Because the area of Kornwerderzand is not a real dike, the amount of points per stretching meter of dike is no meaningful statistic. The amount of points per square kilometer is a nice statistic however, it enables us to state something on the properties of the radar data. On the artiﬁcial island of Kornwerderzand the satellite measures 5816 points per square kilometer (measured in 2 tracks).

The series of measurements of these points deliver an estimation of the subsidence rate in the area. Interesting to know is how accurate this estimation is. For the ascending track, the deformation rate is determined by a series of 58 images. The descending track has an even larger series, of 74 images. The eﬀect of this on the precision of the estimation is that the descending track velocity is slightly more accurate than the ascending

POSEIDON, ﬁnal report 17 November 2006 62 CHAPTER 6. CASE STUDIES track. Standard deviation of estimated velocity(mm) is for ascending track 0.20 mm/y and for descending track 0.17 mm/y.

Figures

In this section, some figures resulting from the testing scripts are presented. The first test that was performed is the Overall Model Test. This test describes to what extent the measurements behave according to our (linear)model. The input parameter for this step was a standard deviation of 4 mm, and a significance level of 90%.

The main diﬀerence between both tracks appears to be the number of accepted points. The ascending track measurements mostly behave according to our model, whereas the descending measurements appear to be worse (which is due to a longer time interval of the measurements). The coherence is directly dependent on the standard deviation of the individual measurement residuals with respect to the linear model. This is plotted in the ﬁgures F.21 and F.22.

From figure F.21 and figure F.22 we can deduce that the model of the descending points fits worse than the model of the ascending points. This can be a reason for the rejection of the points in the overall model test. This is pointed out more clearly in figure F.23, where the points that are rejected in the overall model test are made black.

If we now make a plot of all points that are not rejected by the overall model test, we get figure F.24. One could defend that the points which are rejected by the overall model test, show no clear linear deformation (with acceptable noise level) and are thus not usable in interpretation of the data. With this statement, we can argue that figure F.24 is the only usable figure to use for interpretation.

The points with the big triangle around it are now points with more or less reliable, significant deformation. If this point is not isolated, something is bound to be happening at this location. Clearly visible in figure F.24 is that there are almost no points with reliable significant deformation, and most points which do answer to this criterion are isolated. Therefore, we can state that the area is generally stable. The only things that move are buildings and other structures, like bridges. These kinds of deformation can be categorized as autonomous movements.

A lot of the points which behaved in a strange way on the northern breakwater, which was ﬁrst considered as an interesting location, are rejected in the overall model test and are thus not visualized in ﬁgure F.24. However, the other 2 locations are still in the picture. The subsiding points at the bridge survived the overall model test, and some subsiding points near the sluice did as well. Most points at the sluice vanished however.

6.3.3 Summary of results

1. The artiﬁcial island of Kornwerderzand is generally stable. 2. There are a number of autonomous movements going on at the structures on the island. These points are not local deformation, because they are measured on structures. 3. The bridge appears to subside on the eastern side, the reaction of that is a slight uplift of the same bridge on the western side.

6.4 Case study Marken

The dikes of the island Marken are a part of the primary dikes of the Netherlands. It is a special part, because the island is of a high importance in both cultural and historical point of view. The area of Marken has been

POSEIDON, ﬁnal report 17 November 2006 6.4. CASE STUDY MARKEN 63

chosen as a case study not only because of the availability of locations with deformation in the PS-InSAR datasets for these dikes, but also because of the prior knowledge of the dikes’ status. A short investigation made clear that a part of the southern part of the ringdike (at the location of the numbers 13 to 15 in ﬁgure F.26) is known to be in a bad maintenance state. The responsible agency for the dikes is RWS, department Noord-Holland. Information about the history of Marken, the dikes and the used datasets can be found in appendix D.

6.4.1 Detection of deformation

As was visualized in ﬁgure F.25 there are many PS-InSAR points in the ascending and descending image of Marken on the Markerwaard dikes, but less points on the ring dike. A short inspection of the PS-InSAR data of the Markerwaard dikes showed that these dikes are stable. They almost all have a deformation less then 1 mm/year in the radar LOS and are therefore spatially correlated. Ascending and descending scatterers show the same deformation rates as well. Most of the points on the Markerwaard dikes have sidelobes, which indicates that these points can not be classiﬁed as noise. Therefore the PS-InSAR points on the Markerwaard dikes are considered as stable points. On both Markerwaard dikes, the Bukdijk as well as the Kruisbaakdijk, one location was chosen as an representative location. At exactly this location both ascending and descending PS-points are available and the time series of those points were analyzed.

For the ring dike the situation is totally different. Only on the western part of the ring dike, near the Kruisbaakdijk, there is a high number of spatially correlated PS-InSAR points, but this holds only for the ascending dataset. Most other points in both ascending and descending dataset are isolated. Also a lot of these points did not have any sidelobes. In total there are 28 scatterers at the entire ring dike. Three of these points have a very low coherence and are therefore classified as an outlier. All the other 25 points (ascending and descending) show deformation rates of about 5 to 15 mm per year. For this reason they are spatial correlated and can be classified as deformation. The position of the PSs are visualized in figure F.26.

6.4.2 Time series analysis

The time series of each of the interesting locations were computed. The time series of some representative locations can be seen in figure 6.9. The corresponding estimated deformation velocity in the LOS, the estimated topographic height and the coherence are also given in these figures. All time series of the PS-InSAR points at the ring dike show the same trend of deformation over the entire time span: around 5 to 15 mm per year. The Bukdijk and Kruisbaakdijk show a deformation of 0.5 to 1 mm per year. It is also clearly visible that there are some deviations of this estimated linear deformation, which can be recognized in all time series of the interesting locations. In the time series of the locations on the ring dike these deviations appear to be periodic or even seasonal, see figure 6.9. Therefore the water level measurements of the Markermeer were consulted, because they might give information about the tidal effects, which could indicate changes in external pressure on the dike. The water levels did not change much in the acquisition period of the radar data.

6.4.3 Estimation of deformation parameters

To be able to determine the mechanism that causes the deformation that is visible in the PS-InSAR datasets, an overview of all estimated deformation velocities at the identiﬁed locations is given in ﬁgure F.41. For proper estimation of the horizontal and vertical components of deformation, data in ascending and descending track is needed. The deformation in vertical direction is preferred, because this deformation is expected to be the largest. The northern part of the ring dike is rebuilt in the period of the measurements, so some settlement, which has mainly a component in the vertical direction, is expected. To study a possible subsidence of the whole island, also some points in the village of Marken were considered.

An overview of the estimated vertical deformation velocities and their variance can be seen in table 6.3. These

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Figure 6.9: Time series for some characteristic locations values are calculated according to the method described in section 4.3. The values are grouped into the areas of the Bukdijk, Kruisbaakdijk, ring dike and the village of Marken.

6.4.4 Classiﬁcation

The assumption is made that the radar only reﬂects at one side of the dike, the outer side, because at this side there is a stone layer. The exact location of the scattering object is not known. There are hardly any ascending and descending PSs available at the same location. This causes diﬃculties when deciding about the deformation mechanism that caused the measured deformation. One deformation mechanism is easily explained, since it is known that the northern dike is reinforced in 1994. Therefore, the deformation mechanisms settlement is assumed to cause the deformation.

ˆ 2 ˆ 2 dz ascending σdz ascending dz descending σdz descending Village Marken -2.5 0.09 -2.0 0.17 Ring dike Marken -6.4 0.20 -9.9 0.82 Bukdijk Marken -0.6 0.06 -0.3 0.21 Kruisbaakdijk -1.2 2.09 1.0 0.37 Marken Total of Marken -2.1 0.03 -2.4 0.06

Table 6.3: Estimated vertical deformation velocities (mm/y) and their variance.

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From table 6.3 can be seen that the magnitude of the estimated deformation velocity in the village of Marken diﬀers from the estimated deformation velocity of the ring dike. Therefore it is safe to state that the measured deformation on the ring dike can not be caused by just subsidence of the whole island. However, it is very well possible that the island of Marken is subsiding a bit due to compaction of a the peat layer below the entire island. The geotechnical proﬁles show that there is a peat layer below the entire ring dike at a depth of 5 meter. The ring dike shows a larger deformation rate than the village. The southern part of the ring dike is older and weaker than the northern part. Because of a lack of PS-InSAR points at the southern part of the dike, no assumption on the deformation mechanism can be made yet.

The Bukdijk and Kruisbaakdijk are quite stable, which can be explained by the fact that they were built on a stable layer, about 50 years ago. Before the dikes were built, a so called ”cunet” was dug. This means that the weak peat layers where dredged away and were replaced by a layer of sand.

6.4.5 Quality assessment

The precision of the estimated deformation parameter is described with use of the standard deviation of estimated velocity. This precision was 0.31 mm/year for the ascending track and 0.35 mm/year for the descending track. To be able to describe the reliability of the assumed linear deformation model, the Global Overall Model (GOM) test was conducted. The results of the applied overall model test with a power of 90% and a standard deviation of 6 mm can be seen in figure F.27 and figure F.28. Normally, for corner reflectors a standard deviation of 2 mm is used. The big difference is due to the fact that corner reflectors are ideal scatterers; the natural scatterers give worse reflections. The large amount of rejected PS-InSAR points can be clarified with a closer look on the standard deviation of the residuals from the linear deformation model for each PS-InSAR point (see figure F.29 and F.30). This picture shows that the standard deviations of almost all PS-InSAR points are in the interval of 5 to 10 mm. The points that are accepted have a high coherence value and are also the points with a high number of sidelobes. The isolated PSs are not accepted, this is most likely due to the big standard deviation of the residuals. Other reasons can be that the used linear model is not valid or the atmospheric estimation can be improved.

One of the used datasets is the leveling and GPS measurements from RWS (see [46]). The leveling data and the GPS measurements can be used to validate the PS-InSAR measurements. Of the ring dike there is leveling data available from 1996, 1997, 1998 and 2001. The locations of these measurements can be seen in ﬁgure F.31. The leveling was conducted using steel tubes in a concrete shell (numbers in red) and yellow spots painted at the path on the crest of the dike. The measurements are with respect to NAP and connected with level marks (numbers in orange). Some GPS measurements were performed with the use of four reference points (numbers in green) to get information on the horizontal movement of the dikes.

For the validation of the radar data, the leveling data of the steel tubes between 1996 and 2001 was used. The results of the leveling measurements can be seen in ﬁgure F.32. The yellow marks on the path were only used as intermediate locations and were not considered to be stable in the time span of the measurements. The GPS measurements (see ﬁgure F.33) made clear that the vertical deformation is larger than the horizontal deformation.

The total deformation between 1996 and 2001, measured with leveling, is recalculated into a deformation rate per year (see the column ’leveling deformation/yr’ in table 6.4). For each steel tube, all PS-InSAR points in the surrounding of the corresponding tube where selected. Of these PS-InSAR points the mean vertical component of the estimated deformation velocity was calculated, which can be found in column ’mean radar deformation/yr’ in table 6.4. The diﬀerences between the radar and leveling deformation rate can be found in the column ’diﬀerence’.

It must be taken into account that the leveling data do have a known reference, namely the used benchmark at the top of the dike, whereas the location of the PS-InSAR measurements is not known exactly. It is assumed that the radar reﬂects at the wave breaking stones. This means that the deformation rates of the leveling and PS-InSAR are not necessarily the same.

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Tube # PS- mean leveling Difference Difference Difference Double InSAR radar deforma- between between difference # deformation/yr two two radar and tion/yr points points leveling (radar) (leveling) 9 1-5 -3,6 -4,4 0,8 12 6-12 -5,7 -5,2 -0,5 2,2 0,8 1,4 23 14-15 -13,3 -10,8 -2,5 7,6 5,6 2,0 49 26-27 -15,1 -10,8 -4,3 1,8 0,0 1,8 55 25 -7,3 -8,8 1,5 -7,8 -2,0 -5,8 61 23 -13,5 -12,8 -0,7 6,2 4,0 2,2 64 19-22 -14,7 -11,6 -3,1 1,2 -1,2 2,4 70 17-18 -14,8 -9,8 -5,0 0,2 -1,8 2,0 73 16 -17,3 -12,4 -4,9 2,5 2,6 -0,1

Table 6.4: Overview radar and leveling measurements (mm).

Figure 6.10: Scatter plot of the PS-InSAR and leveling measurements

In order to be able to provide a more reliable comparison between the leveling and PS-InSAR data, the double differences between the PS-InSAR and leveling measurements are calculated. The differences in deformation rate between two following leveling tubes are calculated for both PS-InSAR and leveling data, see columns ’Difference between two points (PS-InSAR)’ and ’Difference between two points (leveling)’. The final double differences can be found in column ’Double difference PS-InSAR / leveling’. To give a better insight in the relation between the PS-InSAR and leveling results a scatter plot was made, see figure 6.10. This scatter plot makes clear that there is correlation between the radar and leveling data.

6.4.6 Summary of results

• The Bukdijk is completely covered with grass and small trees. Most PS-InSAR points can be found on this dike. For this reason it is assumed that the radar signal is reﬂecting on the wave breaking stones at the water side, because normally vegetation suﬀers from temporal decorrelation. It is assumed that this is the case for the ring dike of Marken as well. • There are more PSs at the Bukdijk than at the ring dike. This can be explained by the fact that the ring dike is maintained every 5 years while the Bukdijk is not maintained at all. The wave breaking stones at the ring dike are replaced after several years, this will lead to temporal decorrelation. This makes

POSEIDON, ﬁnal report 17 November 2006 6.5. CASE STUDY NOORDOOSTPOLDER 67

it unlikely that the ring dike can be monitored with PS-InSAR over longer periods than 5 to 10 years. Nipping ice disturbs the wave breaking stones as well. This makes it impossible to detect deformation due to nipping ice.

• To be able to describe the reliability of the assumed linear deformation model, the Global Overall Model (GOM) test was conducted. The points that are accepted have a high coherence value and are also the points with a high number of sidelobes. The isolated PSs are not accepted, this is most likely due to the big standard deviation of the residuals.

• Both PS-InSAR and leveling data show a deformation in the vertical direction of about 10 mm per year at the ring dike. The deformation measured with PS-InSAR appears to be a bit larger than the leveling data. This can be explained by the fact that not the same objects are measured. But because the magnitude is almost the same, it is likely that the measured deformation mechanism is the same. This mechanism is probably compaction of the peat layer below the dike due to the weight of the dike itself. On the northern part of the ring dike there is probably settlement as well, because this part was reinforced in 1994.

• The southern part of the ring dike showed the same magnitude of vertical deformation as the northern part of the ring dike in both PS-InSAR and leveling data. But the GPS data showed also horizontal deformation perpendicular to the length axis of the dike near the locations of some PS-InSAR measurements. According to the civil inspector of Marken this is probably due to a combination of nipping ice and high water. But as mentioned before, nipping ice will disturb the stone layer. This leads to a loss of PSs and makes it not possible to observe the horizontal deformation with PS-InSAR.

• The Bukdijk and Kruisbaakdijk appear to be quite stable. A drawback is that there is no leveling data available of these dikes to verify this statement. The PS-InSAR points in the village of Marken are not completely stable, the mean trend is a small subsidence. This is probably due to compaction of the peat layer below the entire island.

• The conclusions that can be drawn based on the PS-InSAR measurements about the magnitude of the vertical deformation are in correspondence with the measurements of RWS (see [46]). They concluded that a monotonous deformation of 10 to 15 mm per year appeared at the ring dike. But to determine the horizontal deformation mechanism from the PS-InSAR measurements only, more PS-InSAR points in both ascending and descending dataset are needed, so the LOS deformation can be decomposed in a horizontal and vertical component.

6.5 Case study Noordoostpolder

The Noordoostpolder is a part of the so called Zuiderzee Works. The Zuiderzee Works are a man-made system of dams, land reclamation and water drainage works, and they are the largest hydraulic engineering project undertaken by the Netherlands during the twentieth century. The project involved the damming oﬀ of the Zuiderzee, a large, shallow inlet of the North Sea, and the reclamation of land in the newly enclosed water body by means of polders. Its main purpose was to improve ﬂood protection and create additional land for agriculture. In the following section the case study of the Noordoostpolder is described. It contains the results and conclusions of this particular case study. A more extent background information of this case study can be found in E.

6.5.1 Detection of deformation

Based on the methodology, explained in section 5.5, all PSs points that are on the dike or around it were analyzed and classified to outliers, autonomous movement (or local deformation), stable point, and deformation. Figure F.34 shows only the PSs that are located on the dike with the results of the detection step. Based on these results, the dike is classified in three areas and three detected deformation areas were chosen for further analysis (Case A, B, and C in figure F.34):

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The areas which were classiﬁed as autonomous movement contain some isolated PSs (spatially uncorrelated) that show a deformation signal. It is also possible that these points show local deformation mechanisms, i.e. deformation in a small part of the dike. These areas are visualized in ﬁgure F.34 by the orange color that shows that this area needs more investigation.

6.5.2 Time series analysis

For all PSs in case A, B, and C time series analysis was performed to check the validity of linear model and to study other possibilities for phase unwrapping. We visually checked, for all PSs in the detected deformation areas, the possibilities for phase unwrapping and did not see any other solution for the phase unwrapping. The results of this step for the validation of the linear model are presented for each location (A, B, and C) separately.

• Case A: Most of the PSs in this area show a deformation signal in the LOS direction of about 1.6 to 3 mm/year. Also, both ascending and descending observations show approximately the same signal. Figure 6.11 shows some examples of the time series in this area. As it can be seen, the linear model is not feasible for the entire time period. It is more likely to have a linear or exponential trend in the ﬁrst half of the time period, after that, the deformation becomes stable, see the alternative models in ﬁgure 6.12.

Figure 6.11: Some time series for Case A.

• Case B: This part of the dike, show two kinds of PSs that show a different deformation signal. These PSs are divided in two groups: B1 and B2. Figure F.35 shows the location of these two kinds of PSs. Figure 6.13a and figure 6.13b show the time series of one PS in the B1 part for both ascending and descending orbit. These time series are similar to the deformation signal of Case A. The PSs in the B2 segment show a linear deformation over the whole period analyzed radar data, see figure 6.13c

POSEIDON, ﬁnal report 17 November 2006 6.5. CASE STUDY NOORDOOSTPOLDER 69

Figure 6.12: Alternative time series for Case A.

and figure 6.13d. Also, this second group of PSs shows the considerable difference in ascending and descending observations. Comparison of the locations of these two groups of points reveals that they are also spatially separated. So, we concluded that case B can be split up into two parts with different deformation mechanisms. • Case C: The observations in this segment are spatially variable. We detected two different groups of PSs. The first group shows the stable behavior during the whole time period (figure 6.14a) and the second group shows approximately linear deformation signal (figure 6.14b).

6.5.3 Estimation of deformation parameters

Using the approach explained in section 4.3, the detected deformation in the areas A, B, and C were decomposed to the dx and dz. In this section, the results are summarized:

• Case A: Because of the availability of both ascending and descending observations in this segment, it is possible to decompose the detected deformation to the dx and dz. However, as both observations show the same signal (average of 1.7 mm/year), with the same temporal behavior, it is also likely that the horizontal deformation is not signiﬁcant. So, we derived deformation parameters for both situations. The estimated deformation parameters (using decomposition) is dx = - 0.9 mm/year and dz = -1.5 mm/year. With the assumption that dx=0, the deformation in up direction, derived as: dz, becomes -1.95 mm/year. • Case B: We derived the deformation parameters for the cases B1 and B2 separately. As, ascending and descending observations show the same signal in the B1 case, we derived the deformation parameters for this case also with the assumption of no horizontal deformation. For B1, dx = -1.7 mm/year and dz = 1.38 mm/year. With the assumption of no horizontal deformation, dz was estimated as dz = 1.8 mm/year. For B2, dx = -2.1 mm/year and dz = -2.9 mm/year. • Case C: As only ascending observations are available in this part of the dike, it is not possible to derive both deformation parameters. Therefore, with the assumption of dx=0, the estimated deformation in up direction for this segment is dz= -1.42 mm/year. We used only the PSs which had been deﬁned as deformation in the detection step.

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Figure 6.13: Some time series for Case B.

6.5.4 Classiﬁcation

Based on the results of the last step and additional information about the dike, the detected deformation areas (A, B, and C) are classified to different deformation mechanisms. The methodology of this classification has been described in section 5.6.

• Case A: Due to the similarity between both ascending and descending observations, it is assumed that there is no horizontal deformation in this area. With this assumption, we classified the detected deformation as settlement. Besides, we tried to support this result with some additional information and ground truth. According to some engineering drawing(see appendix E), parts of this dike have been improved in 1992; a new sheet piling has been placed in combination with a new layer of rubbles (figure E.4). This was the case for a part of the area of detected deformation. Actually, we have also deformation at the east-west part of the dike. However, as it is mentioned before, parts of the details of these improvements are lost. This is the case for that east-west part. Something happened, but it is not known what, [Mr. J. Boezeman, waterboard Zuiderzeeland, oral communication, 30 October 2006]. The weight of this new layer was about three thousand kilogram per meter. This additional weight results in a compaction of the soil layers under the dike. As there is the clay layer under this part of the dike, this compaction becomes more feasible and it is possible to be observed with our technique as settlement. Due to the fact that settlement has an exponential behavior in time, which is also visible in the time series of this area (figure 6.12), the results are comparable with the expectations. So we can conclude that we measured deformation is due to this new stone layer in this dike segment. • Case B: We analyzed the cases B1 and B2 separately. The deformation signals in the B1 case show more or less the similar behavior as the deformation of case A. Also the results of our method classified this area as settlement. Similarly, this part of the dike has been improved in 1992, also with a new stone layer. So, we expect the same cause of deformation for these two parts of the dike.

POSEIDON, ﬁnal report 17 November 2006 6.5. CASE STUDY NOORDOOSTPOLDER 71

Figure 6.14: Some time series for Case C.

σdx (mm/year) σdz (mm/year) dx= 0, σdz (mm/year) Case A 0.37 0.04 0.36 Case B1 0.10 0.04 0.25 Case B2 0.10 0.04 Not relevant Case C Not relevant Not relevant 0.09

Table 6.5: The external precision of the estimated deformation parameters

For the case B2, our method classiﬁed this part of the dike as deformation due to an imminent sliding of the outer slope or a sliding of the protective cover. For this part we have no additional information. However, it is known that in the Noordoostpolder the protective cover tended to slide away. It might be that that the measured deformation is due to this kind of sliding.

• Case C: In this segment, half of the PSs are stable and the remaining half show a deformation signal. Because of this spatial variability and noisy character of the observations, it is difficult to assign specific deformation mechanism to this segment. As only ascending observations are available, so it is assumed that there is no horizontal deformation, we classified this deformation as settlement. However, the deformation classification and interpretation in this segment becomes very tricky due to the noisy observations, small magnitude of the deformation(0.6-1.4 mm/year), lack of additional deformation and ground truth , and the availability of only ascending observations.

6.5.5 Quality assessment

In this paragraph it is explained how to decide about the feasibility of the results and conclusions based on the PS-InSAR data.

The external precision

In this section the external precision of the estimated deformation parameters is presented. The results are summarized in table 6.5.

As can be seen in table 6.5 the external precision is quite high. It should be noticed that these numbers represent an ideal situation. The number of unknowns is maximal two while the number of observations equals hundreds of points. Also it is clear that the precision of dx depends on the orientation of the dike, like

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it is explained in section 4.3. The orientation of the dike in case B1 and B2 is almost vertical, which implies a good precision. The orientation of the dike in case A is partly vertical and partly not. This will decrease the precision of the estimated deformation in the horizontal direction.

Overall Model Test

To derive the quality of our ﬁnal results, we performed Overall Model Test(see section quality) for all detected PSs on the dike. The results of this test are presented in ﬁgure F.36.

As you can see in this ﬁgure, most of the points that show a deformation signal are rejected in the Overall Model Test. The rejection of the test can be related to diﬀerent issues, see section 5.7. However in our case, we see the high dependency between the rejection of the test and the detected deformation. The main reason for that could be the invalidity of the linear model for the detected deformation mechanisms. There are also some PSs which show a large deformation signal (2 to 4 mm/year) and are accepted in the test, especially in the case B2. As we discussed before, most of the PSs in this part show a linear behavior over the whole time span. But, most of the points which show a deformation signal in the cases A, B1, and C were rejected in the test. This is in agreement with our expectation for these areas, as most of the PSs in these parts do not show a linear behavior over the whole time span. So we can conclude that the linearity of the model for the time interval of the analyzed radar data is not a realistic assumption for the dike deformation mechanisms as detected in this area.

Validation

Like it is stated before, there are no validation datasets available for this case study. This means that the validity of the conclusions cannot be proven. However, especially in the case of settlement there are models that can be used to calculate the expected magnitude of settlement. The formula of Koppejan [45] is a well known formula. For this formula, some constants have to be specified, like the primary and secondary compression constants. These constants are dependent on the soil type and characteristics of the compressed layer. Notice that the settlement is divided into an primary part and a secondary part. The first part is more or less the short scale settlement, the secondary part the long scale settlement. The primary part ended when the deformation become a straight line. Also the old grain pressure has to be calculated, which equals to the ground pressure minus the water pressure. The new grain pressure equals the old grain pressure plus the new load. The last parameter is the level of consolidation (consolidatiegraad) which depends on some ground characteristics. The fact that there is a clay layer below the protective cover on this dike explains why the primary settlement takes a while. Clay let, in opposite to sand, water badly through it. Another important point is that the clay which can be found on those dikes is known as tough clay. This causes high values for the primary and secondary compression constants, which implies a smaller expected deformation. For this project, the expected settlement is not calculated. However, in our case we are on a dike that has already a protective cover for more than fifty years in 1992. This protective cover causes settlement of the dike in the past. As a consequence a new load will not give the same magnitude of settlement as in the case without a protective cover. To take this effect into account, more advanced models have to be used.

6.5.6 The number of Persistent Scatterers

It was already mentioned that the IJsselmeer dikes of the Noordoostpolder have a lot of PSs. In this section, the number of PSs is researched. To study the relation between the orientation of the dike and the number of PSs, the dike is divided in straight segments, see ﬁgure 6.15, so the curved parts of the dike are not taken into account. For all the straight parts, the orientation of the dike is calculated with respect to the heading direction of the satellite. From the centerline of each part of dike, an oﬀset of 30 meter was applied to both sides of the line. This polygon represents the total area for that part of dike. After that, the number of PSs is counted for each part. The results can be found in table 6.6 and table 6.7. Notice that the sidelobes are

POSEIDON, ﬁnal report 17 November 2006 6.5. CASE STUDY NOORDOOSTPOLDER 73

Figure 6.15: Division of dikes in straight segments. also counted. This number of sidelobes will be signiﬁcant, but the percentage of sidelobes is likely to be the same for all the diﬀerent parts. This implies that these numbers might only be used in a relative way.

In figure 6.16 the number of points per kilometer is plotted against the angle between the orientation of the dike and the orbit of the satellite. For ascending orbit, there is a clear relation between the angle and the number of points. The larger this angle, the smaller the number of points. For the first two points, the difference in angle is not really significant, (just 4 degrees). So for the South dike part2, local differences at the dike or the number of sidelobes might cause the larger number of points per kilometer. For descending orbit this trend is less visible, however, the numbers of points for the different parts is also much smaller, notice the logarithmic scale of the y-axis. This can be expected for those parts where the orientation of the dike is almost parallel to the orbit of the satellite. With a right looking radar the ascending satellite is looking to the outer side of the dike, while the descending satellite looks to the inner side of the dike. While the inner side of the dike is fully covered by grass, the outer side has some protective cover, which likely causes these good reflections. For these parts that are more or less perpendicular oriented with respect to the orbit, the differences are more difficult to explain. Probably local differences play a role here. The relation between the

Segment ID Length (m) Orientation Angle between #PSs #Points / km dike w.r.t. 0◦ and 90◦ heading sat. (346◦) South dike part1 5450 104 76 200 37 South dike part2 4520 161 19 2012 445 South dike part3 1060 138,5 41,5 178 168 North dike part1 10640 15 15 2608 245 North dike part2 8180 46 46 720 88 North dike part3 2410 97 83 32 13

Table 6.6: The number of PSs for ascending orbit

POSEIDON, ﬁnal report 17 November 2006 74 CHAPTER 6. CASE STUDIES

Segment ID Length (m) Orientation Angle between #PSs #Points / km dike w.r.t. 0◦ and 90◦ heading sat. (346◦) South dike part1 5450 260 80 43 8 South dike part2 4520 317 43 44 10 South dike part3 1060 294,5 65,5 9 8 North dike part1 10640 171 9 192 18 North dike part2 8180 202 22 62 8 North dike part3 2410 253 73 41 17

Table 6.7: The number of PSs for descending orbit

Figure 6.16: Relation between the number of points and the angle between the orientation of the dike and the orbit of the satellite. number of PSs and the coverage of the dike is also clearly visible in another part of the same dataset. At the north-west of Lemmer, there is a peat dike, fully covered by grass, here no PSs are found.

6.5.7 Summary of results

During this case study, we first tried to detect deformation of the Noordoostpolder dike and in a second step we tried to classify and interpret the detected deformation. The first step resulted in some interesting parts of the dike that show deformation. Two of the interesting parts are classified as settlement. For both parts, we conclude that this settlement is due to improvement works in 1992. In this year, a new stone layer was placed on the outer side of the dike. One part is classified as sliding of the protective cover, which is not unlikely because of experiences in the past. One part is not classified, because of the noisy character and the spatial variability of the measurements. The obvious point is that we can detect deformation of this dike in the level of mm deformation per year. However, classification, interpretation, and finding the reasons of the detected deformation is not a straightforward task and need more additional information about the dike and more advanced technical knowledge about the deformation mechanisms. Also, the quality assessment of the used method for detection and classification needs more ground truth information which is not available for all deformation areas.

POSEIDON, ﬁnal report 17 November 2006 Chapter 7

Conclusions and recommendations

In this chapter the answers are presented at the research questions posed in the introduction. This chapter starts with the answer on the main research question, followed by the answers of the subquestions. The chapter ends with an overview of the recommendations for further research.

7.1 Answer on main research question

In this section the answeron the main research question will be discussed. The main research question as stated in the introduction was:

Is the PS-InSAR technique feasible for dike (deformation) monitoring in the Netherlands from a technical point of view?

In short the answer is yes, the technique is feasible. During this project, deformation of dikes were detected and classiﬁed for some case studies. In almost all cases, a reasonable interpretation was found. The validation datasets, available for some case studies, show comparable results. This technique is especially usable to detect locations on the dikes which need more investigation. However, the interpretation of the PS-InSAR results is not straightforward and needs a strong collaboration of radar and dike experts.

7.2 Conclusions

In this section the conclusions are presented for all the subquestions as deﬁned in the introduction. Each conclusion is followed by a short discussion, where the main line of reasoning is given.

7.2.1 Characteristics of dikes

Research question 1: What are the important characteristics of dikes with respect to PS-InSAR?

The amount of PSs on the dikes depends on the kind of protective cover. Most dikes have a collar mattress (kraagstuk) covered with rubbles on the boundary of water and land. These rubbles acts like natural corner reflectors and cause a lot of PSs. The orientation of the dike does not have a significant influence on the number of points per kilometer.

This technique does not work for dikes which are fully covered by grass: This can be seen in the dataset

75 76 CHAPTER 7. CONCLUSIONS AND RECOMMENDATIONS

of Noordoostpolder where all dikes contain a lot of PSs, except the peat dike near Lemmer, which is fully covered by grass. Only objects on such dikes might cause a reflection. In fact this is expected, vegetation is temporally uncorrelated, which implies a low coherence, and thus no PSs. To increase the applicability in vegetated areas, corner reflectors could be placed on dikes which are fully covered by grass. However, further research is needed to study the feasibility and effectiveness of this solution.

7.2.2 Detection and identiﬁcation

Research question 2: Which types of deformation can be detected and which deformation mechanisms can be identiﬁed?

The deformation due to the following nine deformation mechanisms can potentially be detected with PS-InSAR:

• Deformation due to a precursor sliding

• Deformation due to a precursor sliding of the inner slope

• Deformation due to a precursor sliding of the outer slope

• Deformation due to seepage

• Deformation due to sliding of the protective cover

• Horizontal deformation of a dike

• Settlement

• Subsidence

• Swelling

Different issues affect the deformation detection. The first is the temporal behavior of the deformation mechanism. The probability of detection is small when it occurs in a short time period with respect to the revisit period of the satellite. Some deformation mechanisms are not detectible at all, since they take place below the water level. Another factor may be the magnitude of the deformation with respect to the radar wavelength. A large, near-instantaneous deformation might cause an unwrapping error. This means that in the areas with a deformation rate larger than the wavelength between two radar acquisitions, the estimated deformation become inaccurate. This means that large deformation components cannot be measured properly with this technique. The detected deformation can be classified to these nine deformation mechanisms. Although every deformation might potentially be detected with radar, the probability of correct classification increases for strong spatially correlated phenomena. This probability depends on the number of PSs and on whether the deformation can be detected on both sides of the dike or just one side.

Correct classification of small local deformation without spatial correlation is not likely. Anomalous points, surrounded by other points, that show spatially uncorrelated deformation, frequently need further investigation. There are three possibilities for the interpretation of such points: noise, autonomous movements or local deformation. In the first two cases, the dike does not deform. Interpretation of these PSs usually requires field observations and further investigation about the scattering object and the dike itself. In those cases, the PS-InSAR data might be used to indicate whether further research is necessary.

7.2.3 Quality assessment

Research question 3: What is the quality of the results of the PS-InSAR technique in dike monitoring?

POSEIDON, ﬁnal report 17 November 2006 7.2. CONCLUSIONS 77

According to the heading of the satellites (north-south), the radar is most sensitive to vertical deformation, reasonably sensitive to east-west deformation and not very sensitive to north-south deformation. For a dike with an orientation perpendicular to the heading direction of the satellite, only the deformation in the z- direction can be measured. The consequence of this is that not all possible deformation components can be measured and the interpretation may become diﬃcult. We can assume that a deformation along the length axis of a dike is not likely. New satellite missions in the future with other orbital conﬁgurations may solve this problem.

The precision of the derived deformation rates and components is in the order of sub millimeters.

The quality of the estimated deformation rates and components depends on diﬀerent factors, such as spatial distributions of the PSs, land cover, rate of motion and linearity of deformation. An important issue is the assumption about the linearity of the deformation. In the current processing steps, it is assumed that the deformation is linear over the full measurement period. However, the assumption of linearity is related to the time interval of the analyzed radar data with respect to the temporal behavior of the deformation mechanism, i.e. the assumption for a particular deformation mechanism might be only valid on a short time interval. There are several possibilities where the assumption of linearity over the full measurement period is not correct:

1. There is deformation over the full measurement period, however the deformation is not constant over time (a clear example is settlement). 2. The deformation is linear, but does not cover the full measurement period, just a part. 3. The deformation is not linear, and does not cover the full measurement period. These are the elastic movements. 4. The superposition of different deformation mechanisms can cause a non-linear behavior in time. This can be due to the fact that different deformation mechanisms have different temporal behavior.

All of these factors and also opportunistic nature of the technique require expert interpretation, i.e. collaboration of radar experts and dike experts.

Interpretation of the measurements on dikes is optimal when:

1. Both ascending and descending measurements are available. In this case it may be possible to derive the full deformation vector, assuming that the deformation along the length axis of a dike equals zero. When only ascending or descending measurements are available, only for spatially correlated phenomena on a curved dike an indication about the directions of the deformation can be derived. Deformation perpendicular to the length axis of the dike implies that the magnitude of the deformation is not the same over the whole, curved dike. 2. There is a single deformation mechanism. A possible superposition of deformation mechanisms may harm the spatial correlation of a certain deformation mechanism. 3. PSs are found on both sides of the dike. Some deformation mechanisms inﬂuence both sides of the dike, see section 2.2. PSs on both sides help in the evaluation of the diﬀerent possibilities for these mechanisms.

7.2.4 PS-InSAR with respect to the needs

Research question 4: To what extent does PS-InSAR fulﬁll the needs for dike deformation monitoring in the Netherlands?

According to the ”Voorschrift Toetsen op Veiligheid”, the dikes in the Netherlands should be monitored every ﬁve years. Based on its large spatial coverage and its short revisit period (monthly), PS-InSAR technique can

POSEIDON, ﬁnal report 17 November 2006 78 CHAPTER 7. CONCLUSIONS AND RECOMMENDATIONS

eﬀectively be applied as an indicator method to continuously monitor the dikes of extended areas to detect locations which needs a more detailed investigation. However, this technique cannot be used for dikes that are fully covered by vegetation.

Also the opportunistic nature of this technique makes the successful application of this method dependent speciﬁc condition, such as the number and location of the PSs.

Furthermore this technique can contribute to the scientiﬁc researches about dike deformation monitoring. Until now, no measurements of dike deformation are available with millimeter precision, which have the same spatial and temporal coverage. Since general knowledge on the behavior of a dike at millimeter level is limited, PS-InSAR can be used to provide new insights in the behavior of a dike at those scales.

7.3 Recommendations for further research

In this section, some recommendations for further research are given. These recommendations were collected mainly from the conclusions, but also from the rest of this report, where justiﬁcation may be found. The list is certainly not exhaustive, but only provides some suggestions to make a next step in this research.

1. The present research focused on the technical feasibility. To make the technique operational for practical use the economical feasibility should be studied next. 2. Study the integration of this technique with other measurement techniques to fulfill all the demands for dike deformation monitoring. 3. Study the use of other assumptions about the behavior of the deformation mechanism over time. For instance, the use of a linear model for a variable time period or the use of non-linear models. 4. Study the feasibility of the use of corner reflectors as reference points in the radar images and as PSs on dikes. 5. Study the possibilities of other radar satellites, such as RADARSAT-1, ALOS, TerraSAR-X and RADARSAT- 2. Also cross interferometry (using images from different satellites with different acquisition geometry) have to be studied. 6. Study a pre-operational system. 7. Improve the algorithms of PS processing, especially for PS detection, atmospheric effect estimation, and quality assessment.

POSEIDON, ﬁnal report 17 November 2006 Appendix A

List of used datasets

In this appendix the datasets are explained which were relevant for the project. A division is made, based on the importance of the datasets. The ﬁrst dataset is the most important, whereas the last ones are convenient but not really important to have. For each dataset there is also described what the expectation of these data is.

Radar datasets

Content: The radar datasets contain the processed persistent scattering data and the Multi Reﬂectivity Map (MRM). Example: See ﬁgure A.1 Supplier: TUDelft

Reference frame: pixel coordinates Vector or raster: raster Way of acquisition: ERS 1 and 2 satellite

Topographical map 1:10.000

Content: This is a detailed vector map made by the Topografische Dienst Kadaster; the topographic survey agency of the Netherlands. Example: See figure A.2 Supplier: Topografische Dienst Kadaster

Reference frame: RD Vector/raster: vector Way of acquisition: Aerial Photography

DTB-wet and DTB-dry

Content: These Digital Topographical Files (DTB) of the wet and dry infrastructure at scale 1:1000 form together the DTB2000. These datasets contain very detailed and precise information about the geometry of dikes and highways. It also contains information about the altitude of the ground level and objects near the dikes. The DTB2000 is a vector map.

79 80 APPENDIX A. LIST OF USED DATASETS

Figure A.2: Example top10vector www.kartograﬁe.nl

Figure A.1: Example radar data

Figure A.4: Example lenght proﬁle

Figure A.3: Example DTB-wet www.geo-loket.nl

Example: See ﬁgure A.3 Supplier: This map is free for education purposes; it is available at Rijkswaterstaat; the Directorate General of public works and water management

Reference frame: RD Vector/raster: vector Way of acquisition: aerial photography + additional terrestrial measurements

Ground truth datasets

Content: For instance leveling, tachymetry or GPS data. This data can be provided in excel-sheets, length profiles or Move3 files. Example: See figure A.4 Supplier: The responsible agency for the maintenance of the dike. This can be Rijkswaterstaat or a waterboard. Way of acquisition: leveling

POSEIDON, ﬁnal report 17 November 2006 81

AHN

Content: Height maps of the Netherlands, with a sampling rate of about once every 5 meter. Example: See ﬁgure A.5 Supplier: Rijkswaterstaat; the Directorate General of public works and water management

Reference frame: RD Vector/raster: raster Way of acquisition: laser altimetry from airplane

Figure A.6: Example geotechnical proﬁle www.geodatabank.nl

Figure A.5: Example AHN www.ahn.nl

Figure A.7: Example soil map 1:50000 www2.bk.tudelft.nl Figure A.8: Example aerial photograph

Geotechnical Proﬁles

Content: These proﬁles show the structure of the subsurface of the dike and the underlying soil layers. Example: See ﬁgure A.6 Supplier: Geodelft Way of acquisition: drillings

Soil map and Borehole measurements

Content: The soil map 1:50.000 only provides information about the ﬁrst meter, borehole measurements contains very detailed information about the soil layers, but only for the borehole locations.

POSEIDON, ﬁnal report 17 November 2006 82 APPENDIX A. LIST OF USED DATASETS

Example: See ﬁgure A.7 Supplier: In principle this dataset is owned by Alterra, but this data can also be viewed online at http://www.bodemdata.nl/ Similar data can be retrieved at www.dinoloket.nl.

Reference frame: RD Vector/raster: vector Way of acquisition: auger points

Technical drawings

Content: Technical drawings of a dike give information about the structure of dike; cross proﬁles, information about the used materials, foundation, etc. Supplier: The responsible agency for the maintenance of the dike. This can be Rijkswaterstaat or a waterboard.

Aerial photography

Content: Aerial photography usually has a better resolution than satellite imagery. With this photo’s it becomes very easy to get an overview of the situation on the case study locations. Example: See ﬁgure A.8 Supplier: Most of the municipalities have for their maintenance work digital aerial photos. Also the Cadastre is a provider of digital aerial photography: see website: http://www.kadaster.nl/ . Also the whole Netherlands is covered with high resolution aerial photography in Google Earth and you can ﬁnd them at: http://www.vanuitdelucht.nl/. Another option to get aerial photographs is via www.beeldportal.nl.

Reference frame: pixel coordinates Vector/raster: raster Way of acquisition: Aerial photography

Ground water level charts

Content: These time series show for some points the ﬂuctuations in the ground water level. Supplier: These data is available at www.Dinoloket.nl.

Water levels IJsselmeer

Content: These time series show for some points the ﬂuctuations of the water level in the IJsselmeer and Markermeer. Supplier: One of the so called ’Dienstkringen’ of Rijkswaterstaat, like the IJsselmeerkring or go to the operators of the sluices at, for example, Kornwerderzand.

POSEIDON, ﬁnal report 17 November 2006 Appendix B

Background information Harlingen

The following appendix describes the background information of the case study performed at Harlingen. The ﬁrst part gives an overview of the history and the current situation of the area. After that there is a section in data, which data was used and how it was prepared so that it was ready for interpretation.

Introduction

One of the natural recources in the Netherlands is salt, this is rock salt (halite) and magnesium salt. These types of salt, that are about 300 million years old, can be found underground in certain layers or in pillars. Salt mining in the Netherlands is performed on a few locations; one of these salt mines is near Harlingen (Sexbierum) and is exploited by the Frisia Company. In Friesland salt has been extracted since 1995, this is done at a record depth of 2800 meters.

The salt is extracted by injecting water that dissolves the salt; the substance that results from this is pumped to the surface and dried [28]. In the underground salt layer caverns form because of the extraction. Due to the pressure and temperature at the depth of 2800 meters the salt behaves like a thick liquid. The consequence is that the salt slowly ﬂows into the extraction caverns, resulting in subsidence of the whole area with a speed of up to 20 to 40 mm a year for the case of Harlingen. Locally the absolute subsidence can be up to a few decimeters with a legally allowed maximum of 35 cm for the area near Harlingen.

Data

In this section some information is given about the datasets that where used for the case study of Harlingen. Also there is an explanation of what needed to be done to prepare the data for further interpretation.

Used data sets

The datasets used for this case study are:

1. PS-InSar data

2. Top10 vector

83 84 APPENDIX B. BACKGROUND INFORMATION HARLINGEN

3. Google earth 4. Subsidence data

Figure F.37 gives an impression of what this data looks like. Clearly visible is the subsidence bowl due to the salt mining in the area. The dike lies on the edge of the subsidence bowl. All points on the dike appear to be spatially correlated. At ﬁrst sight no there are no points which behave diﬀerent than usual. The tables B.1 and B.2 give an overview of all acquisition dates of the PS-InSAR data.

Satellite Orbit Date Btemp (days) B (m) E1 03910 (master) 14-Apr-92 0 0

E1 3910 14-Apr-92 0 0 E1 4411 19-May-92 1638 35 E1 4912 23-Jun-92 1952 70 E1 5413 28-Jul-92 1110 105 E1 5914 01-Sep-92 1790 140 E1 6415 06-Oct-92 1952 175 E1 6916 10-Nov-92 2732 210 E1 7918 19-Jan-93 1509 280 E1 8419 23-Feb-93 2079 315 E1 8920 30-Mar-93 2877 350 E1 9421 04-May-93 1596 385 E1 9922 08-Jun-93 1671 420 E1 10423 13-Jul-93 1924 455 E1 10924 17-Aug-93 1811 490 E1 11425 21-Sep-93 1990 525 E1 11926 26-Oct-93 2277 560 E1 12427 30-Nov-93 2798 595 E1 19785 27-Apr-95 1751 1108 E1 20286 01-Jun-95 1755 1143 E1 20787 06-Jul-95 2382 1178 E1 24795 11-Apr-96 1616 1458 E1 25797 20-Jun-96 2349 1528 E1 26298 25-Jul-96 2183 1563 E1 40326 01-Apr-99 1836 2543 E1 41328 10-Jun-99 2476 2613 E1 44835 10-Feb-00 1357 2858 E2 3118 24-Nov-95 2190 1319 E2 3619 29-Dec-95 2134 1354 E2 4120 02-Feb-96 1728 1389 E2 4621 08-Mar-96 2612 1424 E2 5122 12-Apr-96 1635 1459 E2 6124 21-Jun-96 2436 1529 E2 7126 30-Aug-96 2051 1599 E2 8128 08-Nov-96 1765 1669 E2 9130 17-Jan-97 2217 1739 E2 10132 28-Mar-97 2384 1809 E2 11134 06-Jun-97 1998 1879 E2 12136 15-Aug-97 2179 1949 E2 13138 24-Oct-97 2325 2019 E2 14140 02-Jan-98 1740 2089 E2 15142 13-Mar-98 1991 2159

Table B.1: Ascending stack, track 258, continued on next page

POSEIDON, ﬁnal report 17 November 2006 85

Satellite Orbit Date Btemp (days) B (m) E2 16144 22-May-98 2709 2229 E2 17146 31-Jul-98 1560 2299 E2 18148 09-Oct-98 2261 2369 E2 19150 18-Dec-98 1666 2439 E2 20152 26-Feb-99 2495 2509 E2 21154 07-May-99 1960 2579 E2 22156 16-Jul-99 2392 2649 E2 23158 24-Sep-99 1157 2719 E2 24160 03-Dec-99 2809 2789 E2 24661 07-Jan-00 1719 2824 E2 25162 11-Feb-00 1201 2859 E2 26164 21-Apr-00 2219 2929 E2 26665 26-May-00 2480 2964 E2 28168 08-Sep-00 2243 3069 E2 29170 17-Nov-00 2424 3139 E2 35182 11-Jan-02 1413 3559 E2 35683 15-Feb-02 2014 3594 E2 36685 26-Apr-02 1651 3664 E2 37186 31-May-02 1682 3699 E2 37687 05-Jul-02 2141 3734 E2 38188 09-Aug-02 2157 3769 E2 39190 18-Oct-02 2937 3839 E2 40192 27-Dec-02 2698 3909 E2 41194 07-Mar-03 2689 3979 E2 41695 11-Apr-03 1272 4014 E2 42697 20-Jun-03 1755 4084 E2 43198 25-Jul-03 1749 4119 E2 43699 29-Aug-03 2028 4154 E2 44200 03-Oct-03 2138 4189 E2 44701 07-Nov-03 2898 4224 E2 45202 12-Dec-03 1555 4259 E2 45703 16-Jan-04 1703 4294 E2 46204 20-Feb-04 2147 4329 E2 48208 09-Jul-04 1664 4469 E2 49210 17-Sep-04 2878 4539 E2 51214 04-Feb-05 2578 4679 E2 52216 15-Apr-05 2394 4749 E2 53218 24-Jun-05 1897 4819 E2 54220 02-Sep-05 2690 4889 E2 55222 11-Nov-05 1619 4959 E2 56224 20-Jan-06 2427 5029

Table B.1: Ascending stack, track 258

Satellite Orbit Date Btemp (days) B (m) E1 04304 (master) 12-May-92 0 0

E1 4805 16-Jun-92 35 -159 E1 5807 25-Aug-92 105 -199 E1 6308 29-Sep-92 140 -269

Table B.2: Descending stack, track 151, continued on next page

POSEIDON, ﬁnal report 17 November 2006 86 APPENDIX B. BACKGROUND INFORMATION HARLINGEN

Satellite Orbit Date Btemp (days) B (m) E1 6809 03-Nov-92 175 253 E1 7310 08-Dec-92 210 -733 E1 7811 12-Jan-93 245 -300 E1 8312 16-Feb-93 280 -10 E1 8813 23-Mar-93 315 -552 E1 9314 27-Apr-93 350 5 E1 9815 01-Jun-93 385 -982 E1 10316 06-Jul-93 420 -1291 E1 10817 10-Aug-93 455 -114 E1 11819 19-Oct-93 525 10 E1 12320 23-Nov-93 560 22 E1 19678 20-Apr-95 1073 -420 E1 20179 25-May-95 1108 -493 E1 20680 29-Jun-95 1143 -1640 E1 21181 03-Aug-95 1178 -137 E1 21682 07-Sep-95 1213 -1643 E1 22183 12-Oct-95 1248 299 E1 22684 16-Nov-95 1283 -882 E1 23185 21-Dec-95 1318 249 E1 23686 25-Jan-96 1353 -286 E1 24187 29-Feb-96 1388 143 E1 24688 04-Apr-96 1423 -457 E1 25189 09-May-96 1458 289 E1 25690 13-Jun-96 1493 -983 E1 26191 18-Jul-96 1528 -1 E1 43225 21-Oct-99 2718 -328 E1 44728 03-Feb-00 2823 -1065 E2 1508 04-Aug-95 1179 -208 E2 2009 08-Sep-95 1214 -1728 E2 2510 13-Oct-95 1249 765 E2 3011 17-Nov-95 1284 -1726 E2 3512 22-Dec-95 1319 -100 E2 5015 05-Apr-96 1424 -578 E2 6017 14-Jun-96 1494 -1095 E2 6518 19-Jul-96 1529 -258 E2 7019 23-Aug-96 1564 -1252 E2 7520 27-Sep-96 1599 -673 E2 8021 01-Nov-96 1634 676 E2 8522 06-Dec-96 1669 -1054 E2 9023 10-Jan-97 1704 -555 E2 10025 21-Mar-97 1774 -728 E2 10526 25-Apr-97 1809 -935 E2 11027 30-May-97 1844 -879 E2 11528 04-Jul-97 1879 -806 E2 12029 08-Aug-97 1914 -600 E2 12530 12-Sep-97 1949 -535 E2 13031 17-Oct-97 1984 -311 E2 13532 21-Nov-97 2019 -267 E2 14033 26-Dec-97 2054 -223 E2 14534 30-Jan-98 2089 -730 E2 15035 06-Mar-98 2124 -1175 E2 15536 10-Apr-98 2159 -1057

Table B.2: Descending stack, track 151, continued on next page

POSEIDON, ﬁnal report 17 November 2006 87

Satellite Orbit Date Btemp (days) B (m) E2 16037 15-May-98 2194 -85 E2 16538 19-Jun-98 2229 -35 E2 17039 24-Jul-98 2264 -666 E2 17540 28-Aug-98 2299 -286 E2 18041 02-Oct-98 2334 280 E2 18542 06-Nov-98 2369 322 E2 19043 11-Dec-98 2404 -1524 E2 19544 15-Jan-99 2439 -821 E2 20045 19-Feb-99 2474 708 E2 20546 26-Mar-99 2509 -1033 E2 21047 30-Apr-99 2544 -892 E2 21548 04-Jun-99 2579 260 E2 22049 09-Jul-99 2614 -1129 E2 22550 13-Aug-99 2649 668 E2 23051 17-Sep-99 2684 -497 E2 23552 22-Oct-99 2719 -675 E2 24053 26-Nov-99 2754 -747 E2 24554 31-Dec-99 2789 296 E2 25055 04-Feb-00 2824 -580 E2 25556 10-Mar-00 2859 -685 E2 26057 14-Apr-00 2894 -592 E2 26558 19-May-00 2929 -501 E2 27059 23-Jun-00 2964 -1224 E2 27560 28-Jul-00 2999 -702 E2 28061 01-Sep-00 3034 278 E2 28562 06-Oct-00 3069 -632 E2 29063 10-Nov-00 3104 -402 E2 29564 15-Dec-00 3139 399 E2 31067 30-Mar-01 3244 838 E2 32069 08-Jun-01 3314 -2121 E2 32570 13-Jul-01 3349 -1147 E2 33071 17-Aug-01 3384 -1594 E2 33572 21-Sep-01 3419 -2336 E2 34073 26-Oct-01 3454 -2143 E2 35075 04-Jan-02 3524 -1024 E2 35576 08-Feb-02 3559 -371 E2 36578 19-Apr-02 3629 -1053 E2 37580 28-Jun-02 3699 436 E2 38081 02-Aug-02 3734 -1110 E2 38582 06-Sep-02 3769 267 E2 39083 11-Oct-02 3804 -80 E2 39584 15-Nov-02 3839 -348 E2 40586 24-Jan-03 3909 -1142 E2 41087 28-Feb-03 3944 -42 E2 42089 09-May-03 4014 -1483 E2 42590 13-Jun-03 4049 -937 E2 43091 18-Jul-03 4084 -456 E2 43592 22-Aug-03 4119 195 E2 44093 26-Sep-03 4154 541 E2 44594 31-Oct-03 4189 -861 E2 45095 05-Dec-03 4224 -1017 E2 45596 09-Jan-04 4259 -560

Table B.2: Descending stack, track 151, continued on next page

POSEIDON, ﬁnal report 17 November 2006 88 APPENDIX B. BACKGROUND INFORMATION HARLINGEN

Axis Ascending Descending x-axis 57 -75 y-axis 30 -29

Table B.3: Shift diﬀerences in meters

Axis Ascending Descending x-axis 11.49 9.16 y-axis 6.75 6.91

Table B.4: Standard deviation in meters

Satellite Orbit Date Btemp (days) B (m) E2 46097 13-Feb-04 4294 -303 E2 46598 19-Mar-04 4329 62 E2 47099 23-Apr-04 4364 -1252 E2 47600 28-May-04 4399 -455 E2 48101 02-Jul-04 4434 -75 E2 48602 06-Aug-04 4469 -591 E2 49103 10-Sep-04 4504 -420 E2 49604 15-Oct-04 4539 38 E2 50105 19-Nov-04 4574 -1470 E2 50606 24-Dec-04 4609 -983 E2 51608 04-Mar-05 4679 -623 E2 52109 08-Apr-05 4714 -878 E2 52610 13-May-05 4749 -354 E2 53111 17-Jun-05 4784 30 E2 53612 22-Jul-05 4819 -429 E2 54113 26-Aug-05 4854 -1099 E2 55115 04-Nov-05 4924 -1226 E2 55616 09-Dec-05 4959 -747 E2 56117 13-Jan-06 4994 -1043 E2 56618 17-Feb-06 5029 -562

Table B.2: Descending stack, track 151

Data Preparation

The next sections are an explanation of the steps that were needed to be taken to combine the diﬀerent datasets and transform them so that they could be interpreted.

Georeferencing The PS-Radar points have been georeferenced in 3 steps, as described in section 5.3

Table B.3 presents an overview of the magnitude of the oﬀset in meters that needed to be corrected for by the georeferencing.

Table B.4 presents the standard deviation of the shift in meters, for both the ascending and the descending track. It can be seen that that inaccuracies remain in the order of 6 to 12 meters. Also visible is that the standard deviations in the y-direction are signiﬁcantly smaller than in the x-direction. This can be explained by the fact that the pixel size is 2 x 10 meters, with the satellite ﬂying approximately in y-direction this translates into a more accurate determination of the y coordinate.

POSEIDON, ﬁnal report 17 November 2006 Appendix C

Background information Kornwerderzand

The following chapter describes the background information of the case study performed at Kornwerderzand. The ﬁrst part describes the history and the current situation of the area. Also an overview of the area is given.

Introduction

Kornwerderzand is a speciﬁc part of the Afsluitdijk, it is part of the primary water barrier system of the Netherlands but it also has other functions. It contains a small and a big sluice to let ships pass, and a series of scouring sluices called the ’Lorentzsluizen’. This controls the water level of the IJsselmeer together with the ’Stevinsluizen’, the water from the IJsselmeer is shed into the Waddenzee. Kornwerderzand is also a small village with about 26 inhabitants. It is part of the municipality of Wunseradeel belonging to the province of Friesland. Kornwerderzand is also of military importance because of its strategic position and its water regulating function ([12] and [23]).

Figure C.1: Location of Kornwerderzand

Figure C.2: Aerial overview of Kornwerderzand

89 90 APPENDIX C. BACKGROUND INFORMATION KORNWERDERZAND

History of Kornwerderzand

In 1921 it was decided to build the Afsluitdijk, for a long time this decision was blocked by the department of war. A possible enemy from the east could use the Afsluitdijk to invade the province of Noord Holland. Because of this it was decided to build a system of defense-works on Kornwerderzand and on Den Oever. The construction works on Kornwerderzand were financed by the builder of the Afsluitdijk: RWS. In 1931 the building works of the fortification of Kornwerderzand started and they were finished in 1934.

Figure C.3: Construction of the Afsluitdijk

During April 1939 the Dutch army started using the complex and in May 1940 there was heavy fighting against the Germans. Due to the effectiveness of the complex it was the only Dutch defense work that withstood the German assault. In 1943 three additional bunkers where built by the Germans. After the second World War the complex was discarded, in the 80’s the department of Defense wanted to get rid of it so it was handed over to the original builder: RWS. It was their intention to cover the bunkers with sand and make them inaccessible but, due to the efforts of an action group, the bunkers were restored and transformed into a museum. In 2001 the defense-works of Kornwerderzand were declared a national Dutch heritage site.

Current situation

The law states that the status of the water barriers should be inspected at least once every 5 years. In the most recent inspection of the Afsluitdijk it did not pass the test [13]. Over nearly the entire length the height of the dike is not suﬃcient, and the structures on the dike are not strong enough (this includes the locks and the scouring sluice at Kornwerderzand).

Nearly all structures at Kornwerderzand date back from the construction of the Afsluitdijk, so by now they are 85 years old. Due to the harsh circumstances (strong wind and salty water) it is understandable that the structures are showing signs of deterioration. This is why RWS had decided to renovate the complex and build another series of scouring sluices further along the Afsluitdijk.

Data

Used data sets

The datasets used for this case study are:

1. PS-InSar data

POSEIDON, ﬁnal report 17 November 2006 91

2. Top10 vector

3. AHN

4. (Aerial photos/Google earth)

For a detailed overview of all acquisition dates of the PS-InSAR data, see table B.1 and B.2 in appendix B.

Data preparation

The next sections are an explanation of the steps that were needed to be taken to combine the diﬀerent datasets and transform them into one coordinate frame so that they could be interpreted.

Georeferencing

The PS-Radar points have been georeferenced in 4 steps, as described in section 5.3 :

1. Determination of PS-point and probable scattering source

2. Determination of both coordinates

3. Calculation of shift in x- and y-components

4. Application of shift and verifying the result

In table C.1 there is an overview of the amounts of oﬀset that needed to be corrected for by the georeferencing.

Axis Ascending Descending x-axis -56 63 y-axis -24 25

Table C.1: Shift diﬀerences

Choice of reference point

In the descending track the reference point was located near Breezanddijk. In the ascending track there were 2 reference points, one near Workum and the other in the province of Noord-Holland. This is because the network on the Afsluitdijk was very weak. This led to a bad determination of for instance the atmospheric eﬀects. A second reference point solved this problem.

The choice of reference point is not important if one only wants to determine relative deformation. Diﬀerences between points in the same track can be identiﬁed and used to determine the deformation.

Statistical determination of deformation

A histogram can be made of the deformation rate in ascending and descending track of the whole dataset which contains Kornwerderzand. This leads to ﬁgure C.4 and ﬁgure C.6

POSEIDON, ﬁnal report 17 November 2006 92 APPENDIX C. BACKGROUND INFORMATION KORNWERDERZAND

Figure C.4: Histogram of deformation rates of the Figure C.5: Histogram of deformation rates of the whole dataset, ascending track whole dataset, descending track

Figure C.6: Histogram of deformation rates of Figure C.7: Histogram of deformation rates of Kornwerderzand, ascending track Kornwerderzand, descending track

The ﬁgures have an almost normal distribution, but it can be seen that the average is not zero. To get some insight in the behavior of the radar points, some means were calculated. For both the ascending as the descending track, the mean deformation is listed in table C.2. In the descending track, the deformation

track KWZ Total Diﬀerence Ascending 0.3211 -0.3207 0.6418 Descending -0.4582 -0.5177 0.0595

Table C.2: Mean deformation.

of the area of Kornwerderzand is comparable to the deformation of the entire image. In the ascending track this is not the case. Kornwerderzand shows an uplift (in the LOS of the satellite) of 0.64 mm/year compared to the rest of the image. This is a significant difference, mainly because it is an average of more than 1000 points. An actual uplift of the area of Kornwerderzand is unlikely. This leads to the assumption that the explanation of this difference can be found in the quality of the reference point or in the quality of the network in the ascending track. The reference point is probably not the problem, because the deformation in the ascending and descending track seen over the whole image is more or less comparable. For this reason, we assume that the explanation of the difference is in the quality of the whole network. This is likely to occur, because the afsluitdijk consists of just one thin line of measurements enclosed by water. If this is the correct assumption, we should correct for the differences in the ascending track. We can do this by shifting all the values for deformation in such a way so that the average becomes zero. The disadvantage is that we make the assumption that there is no subsidence in the area of Kornwerderzand. This is possible, since the average deformation in the descending track is comparable to the average deformation of the whole image, and the part of the Frisian mainland that we use should be more or less stable. The remaining analysis is performed

POSEIDON, ﬁnal report 17 November 2006 93 with the new, shifted, data. Histograms of the deformation can be constructed. Only points on the island of Kornwerderzand are taken into account.

The irregularities in the data lead to diﬃculties in comparing both datasets. For this reason, we have decided to set the mean deformation of both tracks to zero. This calculation step led to the overview of the data as visualized in ﬁgure F.39.

In Matlab, this plot looks like the plot in ﬁgure F.40.

In ﬁgure F.40 the deformation rate is visualized. Triangles facing up are ascending points, triangles facing down are descending points. A triangle gets a bigger triangle around it if its deformation rate is larger than 1 mm/y. As discussed in chapter 5, these points will be adressed as points with signiﬁcant deformation.

POSEIDON, ﬁnal report 17 November 2006 94 APPENDIX C. BACKGROUND INFORMATION KORNWERDERZAND

POSEIDON, ﬁnal report 17 November 2006 Appendix D

Background information Marken

In the following appendix the background information of the case study of Marken is described. As a start there is an explanation of the history of the area of Marken and a detailed description of the dikes. Then the used datasets are mentioned and the data preparation is explained in detail.

Introduction

The island of Marken is not just a part of the primary dikes of the Netherlands; it is also a special part. This is because the island is of high importance in both cultural and historical point of view. This section gives a brief overview of the history and current situation of the island of Marken. For more information on history and culture, see [9], [15], [10] and [6].

History

The first known documentation of the area around Marken is from the eleventh and twelfth century. Back then the wide peat areas, which are now part of the community Waterland, were reclaimed and used as farmland. At that time Marken was not an island, it was part of the mainland, which was widely stretched and included even a part of the present Markermeer. During the second half of the twelfth century there were many severe storms, which had high water levels and flooding as a result. Due to this superfluous amount of water, the sea reclaimed a large part of the land. At this time, also the ground level was decreasing because of settlement of the peat layer due to the new use of parts of the mainland as arable land. In this period, the area of Marken was not used as arable land, and therefore the ground level did not decrease as fast as the other parts of the mainland and Marken became an island. In 1251, the island of Marken was owned by a monastery, which used the land for agriculture. This lead to subsidence of the island, because the peat layer started to compact as well. In this time, the monks had good knowledge and experience in building dikes and they were the first to build a dike around the island.

In 1345 the monks lost their property and the island of Marken was claimed by the count of Holland, Willem IV. Under his command, the dikes around Marken were neglected and the area flooded more and more. Due to the salt seawater, the silted area was not suitable for agriculture anymore and the citizens of Marken became fishers. To keep their properties safe, the citizens started to build their houses on artificial hills, (”terpen” or ”werven” in Dutch). Because of an increasing population, the houses were built very close to each other. At present, these houses still remain.

When the Afsluitdijk separated the IJsselmeer from the North Sea in 1932, the need for the people of Marken

95 96 APPENDIX D. BACKGROUND INFORMATION MARKEN

to build on artiﬁcial hills was gone because the water level became stable due to a lack of tidal ﬂuctuations. In 1957 the connection to the mainland was established, because the government had plans to reclaim land from the Markermeer and establish the Markerwaard. Also the Bukdijk at the northern part of the island of Marken was designed for that purpose. But due to protests from nature conservationists the establishment of the Markerwaard was stopped and the Markermeer remained.

Current situation

Today, Marken is a part of the Netherlands that is not only well known by the Dutch people, it has also become the image of the Netherlands for foreign tourists. The location of Marken can be seen in figure D.1, the island has only 2000 inhabitants. The function of Marken as a tourist attraction beneficial for the economy, not only the local economy of Marken but also the Dutch economy. But the economy is not the most important factor that makes Marken so special. More important is the cultural-historical value of the island. This makes renovation and renewing difficult, because this is bounded by restrictions and regulations. Not only renovation of the objects on the island, but also renovation of the dikes has to be done conform cultural-historical guidelines.

Figure D.1: Location of Marken [16].

Figure D.2: Old map of Marken [6].

A short investigation made clear that a part of the dikes is known to be in a bad maintenance state and that there are some issues concerning the responsibility of monitoring these dikes. RijksWaterStaat (RWS) wants to hand this responsibility of the primary dikes over to the waterboard according to their national policy, but the waterboard ”Hoogheemraadschap van Uitwaterende Sluizen in Hollands Noorderkwartier” is not willing to take over these responsibilities because of the poor state of the dikes. This prior knowledge about the maintenance state makes the island of Marken interesting for a case study.

Dikes

The dikes of Marken can be divided roughly into two zones, namely the dikes around the island of Marken (the ”ring dike”) and the dikes that should be part of the Markerwaard (the ”Markerwaard dikes”). They will be treated separately in this section. An overview of the dikes of Marken can be seen in ﬁgure F.41.

POSEIDON, ﬁnal report 17 November 2006 97

Figure D.3: Schematical cross-section of the ring dike of Marken

The ring dike

The ring dike has a history that goes way back in time. As stated in the general history, monks made the ﬁrst dikes around Marken in the 13th century, but in the centuries after that these were badly maintained. Therefore after a dike failure, a new part of the dike was built more inland. This way of building made the shape of Marken change and therefore Marken lost a part of its surface area. This can be seen clearly when an old map (see ﬁgure D.2) of the island is compared with a contemporary one.

The southern and western parts of the ring dike were built in the 17th and 18th century, the northern part was reinforced in 1994. The complete ring dike consists mainly of sandy clay and has a height of about 1.7 meter above NAP (the ground level of Marken is about -0.5 meter below NAP). On top there is a sand layer and on the sides there is a clay layer. To keep those two separated, there is a concrete border in between. At the inner slope of the dike this clay layer is covered with grass, at the outer slope it is covered with basaltic rocks, see ﬁgure D.4. A cross section is sketched in ﬁgure D.3.

During the reinforcement in 1994 the northern part of the dike was widened and made higher. This was accomplished by making the clay layer broader and higher. The slope of the dike became less steep as well. The reinforcement started at the most eastern point of Marken, at the lighthouse. During the reinforcement the decision was made that the dike had to be higher than previously thought. Therefore at the location 650 meter from the lighthouse the dike is suddenly about half a meter higher, see ﬁgure D.4.

Figure D.4: Northern part of the ring dike of Figure D.5: Deformed protective cover at the Marken, 650 meter to the west of the lighthouse. southern part of the ring dike of Marken.

The southern part of the ring dike is really diﬀerent from the northern part. At some locations it is clearly visible that the dike does not have its original symmetrical shape anymore. For instance the inner slope is much steeper than the outer slope, this is probably due to some high pressure on the outer slope. This can be becaused by nipping ice or the pressure of the water of the Markermeer against the vulnerable old dike. Also the state of the protective cover of basaltic rocks at the outer slope is not as smooth as the one of the northern dike. It is clearly visible that some deformations have occurred in the past (see ﬁgure D.5).

POSEIDON, ﬁnal report 17 November 2006 98 APPENDIX D. BACKGROUND INFORMATION MARKEN

The Markerwaard dikes

As stated in the general history, the building of the dikes that should be part of the Markerwaard started in 1957. The connection of Marken with the mainland (the ”Kruisbaakdijk”) was established a sooner than the dike at the northern part of the island (the ”Bukdijk”). They are designed exactly the same: The unstable peat layer in the subsurface was removed during the construction of the dikes and this gap was ﬁlled with sandy clay. The height of these dikes is about 2.7 meter above NAP, so they are higher than the ring dike.

The dike connecting Marken with the mainland is like the ring dike maintained by RWS. The Bukdijk is not maintained at all, because it does not have a water blocking function. This maintenance consists of big maintenance works every ﬁve years and normal maintenance every year. But the weak spots in the southern part of the ring dike are checked every week. During these big maintenance works new wave breaking rocks are put at the foot of the dike. Also they ﬁll subsided parts of the pavement at the top of the dike with sand and check the border between the sand and clay. For the big maintenance works, the dikes are leveled as well. The yearly normal maintenance is conducted in a visual way, looking for signs of possible deformation or instability. During this normal maintenance a large number of pictures of the dike is made in a systematic way, with a digital camera from the top of a car.

Data

The general case study methodology as described in the first section of chapter 5 is used as well for the case study of Marken. But because not all datasets are available for Marken in particular, the used methodology for Marken differs somewhat. Because of this reason the specific datasets used for Marken and the data preparation are described in this section.

Used datasets

As described in appendix A, many datasets were collected in the context of the POSEIDON project. Unfor- tunately, not all of these datasets were available for all the case study locations. The following datasets are available for the case study of Marken:

• Radar data (MRM and PS-InSAR data) • Top10vector • AHN • Leveling and GPS data (deformation- and horizontal measurements) • Maps with geotechnical proﬁles • Soil map and borehole measurements • Water levels Markermeer

The soil map and borehole measurements are not used, because there is a better alternative available: Geotech- nical length proﬁles of the ring dike. Whereas the soil map describes the layering of the surface until the maximum depth of 1 meter below the subsurface, the geotechnical proﬁles describe the subsurface of the dikes up to a depth of 20 meters.

Another dataset that was available for the Marken case study was leveling data, which included a report of a deformation study of the ring dike of Marken in 2002 (see [46]). In this research the markers on the ring dike were leveled (the actual leveling was conducted in 2001) and compared these measurements with older

POSEIDON, ﬁnal report 17 November 2006 99

Ascending dataset Descending dataset Used satellites ERS 1 and 2 ERS 1 and 2 Date master image 17-Jan-1996 (orbit 03891) 10-Jan-1997 (orbit 09023) Time interval slave images 1992-2000 (not in 1994) 1992-2000 (not in 1994)

Table D.1: Characteristics PS-InSAR datasets Marken.

Ascending Descending Correction value in x direction 58 -39 Correction value in y direction 41 9

Table D.2: Correction values georeferencing (in meters). leveling measurements of 1994, 1996, 1997 and 1998. They also measured the ring dikes with GPS-RTK, where 4 reference stations were used.

The characteristics of the PS-InSAR datasets are summarized in table D.1. This table includes the used satellite for both ascending and descending dataset, but also the acquisition periods are given. For a detailed list of the acquisition dates, see E.2 and E.3 in appendix E.

Data preparation

This section gives a description of the preparation of the PS-InSAR data. This includes the georeferencing of the PS-InSAR points and the choice of the reference point.

Georeferencing

For Marken the PS-InSAR points are georeferenced with the use of the Top10vector. This was the most detailed topographic map that was available for the Marken area. Table D.2 gives an overview of the estimated correction values for all the ascending and descending PS-InSAR points.

Choice reference point

To make the ascending and descending PS-InSAR points comparable with each other, a different reference point is chosen at a location where PS-InSAR points give reflections from the same object. The new reference point is preferably a point that lays in a stable area. For Marken this reference point was not chosen on the island itself but on the mainland. This because the number of available PS-InSAR points on the island of Marken was not that high. There were no locations where it was clear that both ascending and descending PS-InSAR points were reflections of the same object. Therefore the reference point is chosen on the flat roof of a building in Volendam. The new reference point is assumed to be stable. This is because the new reference point did not move much with respect to the old reference point. Furthermore, the deformation value is comparable with the other PS-InSAR points in its surrounding area, so there is spatial correlation. This makes it unlikely that the new reference point is an autonomous movement or noise. The radar datasets were processed for a relatively small area, because the atmospheric effect could then be estimated in a better way. Therefore it is assumed that the atmospheric effects are small.

POSEIDON, ﬁnal report 17 November 2006 100 APPENDIX D. BACKGROUND INFORMATION MARKEN

POSEIDON, ﬁnal report 17 November 2006 Appendix E

Background information Noordoostpolder

This appendix contains the background information of the case study conducted to the IJsselmeer dikes in the Noordoostpolder. It starts with an introduction of the Noordoostpolder, some historical aspects are covered, and a defense is given why this area is chosen. The next section provides a small introduction about the dikes in the Noordoostpolder. Here, the structure and previous maintenance works of the dikes are discussed. This is followed by an overview of the used data sets for this particular case study and a description of some relevant aspects concerning the preparation of the datasets and the choice of the reference point.

Historical aspects

Original plans for the works date back to the seventeenth century, but it took until 1916 when a severe flood struck the Netherlands before the Dutch parliament finally agreed. This results in the so called Zuiderzeewet from 1918. In 1919 the Zuiderzee Works Department was set up. From 1920 to 1924 they worked on a small dike, for testing purposes. After that a 40 ha test polder, called Andijk, was made from 1926-1927 in the Zuiderzee as a test run for making the Wieringermeerpolder. The creation of this polder started in 1927. Originally the polder would have been created after the completion of the Afsluitdijk, but there was a severe lack of agricultural ground in that time. So they decided to start earlier. Draining of the Wieringermeerpolder was finished on 21 August 1930. After the construction of the Afsluitdijk, which was finished in 1932 they start in 1936 with the preparation works for the Noordoostpolder. This polder, with a total area of about 480 km, is in fact the first IJsselmeerpolder. In 1937 the building of the dikes was contracted. Two years later the dikes between Urk and Lemmer were closed, followed by the closing of the dike at the side of the province Overijssel near Vollenhove in 1940. After that, the draining works started, which ended in 1942. At the end of the Second World War, work was started on draining the Flevopolder, a polder with an area of almost 1000 km. Another large polder was planned in the Markermeer, creation of which was heavily debated until the plans were officially abandoned in the early 2000s. A new province, Flevoland, was created out of the Noordoostpolder and the Flevopolder in 1986, thereby completing the Works. For an overview of all the works on the map, see figure E.1.

101 102 APPENDIX E. BACKGROUND INFORMATION NOORDOOSTPOLDER

Figure E.1: The Zuiderzee Works [27].

Figure E.2: The locations where ground improvements are carried out [1].

The choice of this case study

A ﬁrst look on the PS map shows a lot of PSs on the IJsselmeer dikes of the Noordoostpolder. Also it was already known that some parts of these dikes show a deformation with respect to other parts of this dike. However, still there was no conclusive explanation what is happening here. This open question lead to the selection of this case study.

The structure of the dike

According to [1] and [2], different types of dikes are built around the Noordoostpolder. Also the preparation works differs for different areas. The dikes at the south of Urk, indicated with III and IV in figure E.2, are founded on an improved ground layer. Here, the soft soil layer is excavated and replaced by a stable layer. Only a small part of the dike at the north of Urk is also founded on an improved ground layer.

The type of dike from Lemmer to Schokland is the same [2], so only this type of dike is discussed in this section. Notice the diﬀerence in time between the two engineering drawings; [1] from 1937, [2] from 1955. In 1937 there was water on both sides of the dike, so also the inner slope had to be protected to prevent erosion. In [1] it can be seen that the inner slope also contains some stone layers. In [2] these stone layers are not visible any more, so probably they were removed when the polder was completely drained in 1942. In ﬁgure E.3, a cross section is of the dike is given, taken from [2]. Here it can be seen that the top layer of the dike, the top of the outer slope and the whole inner slope are covered by a clay layer with a thickness of 0.30 meter. Below that clay layer, there is a thick boulder clay layer at the outer side of the dike, which becomes smaller to the top and the inner side of the dike. At the foot of the inner slope, the thickness of

POSEIDON, ﬁnal report 17 November 2006 103

Figure E.3: Cross-section of the dike from 1956 [1]. this layer increases again. The dike is founded on a sand layer, which is also the material of the core of the dike. On the outer slope of the dike, different protective covers can be found. On the foot of the outer slope, the collar mattress (kraagstuk) can be found. This layer is on the boundary of water and land. Usually this consists of geotextile, with on top mats of willow branches. The whole collar mattress is covered by rubbles ((stortstenen). The collar mattress prevents that the waves and water flow flush away the sand. So it protects the dike for erosion below the water level. Next to the collar mattress there is a sheet piling with a size of 0.08 by 1.80 meter. Behind this sheet piling they put basaltic blocks of different sizes. Then there is another sheet piling, with a size of 0.08 by 0.40 meter. This is the left boundary of a road, which is made of concrete columns or blocks (not clearly indicated at the engineering drawing). The right boundary consists of a concrete border with behind it again concrete columns of two different sizes. From that point, the remaining part of the outer slope, but also the top and the inner slope are covered with grass. Notice that [2] is an engineering drawing made for maintenance works. Especially the protective covers changed with respect to [1]. This kind of maintenance works done from time to time for different parts of the dike. In the next section an overview is given of what is known about these kinds of works.

Maintenance of the dike

The dikes and polders in the IJsselmeer area were created by the Zuiderzee Works Department, which was also responsible for the dikes until 1986. This department fell under the responsibility of the State. In 1986, the responsibility for the dikes in the Noordoostpolder and Flevopolder was handed over to the province Flevoland. They established two waterboards, which became, among other things, responsible for the maintenance of the dikes. For the Noordoostpolder, this was done by the waterboard Noordoostpolder. In 2000 these two waterboards merged into waterboard Zuiderzeeland which is currently responsible for more than 200 kilometers of dike. Due to the transfer of the responsibility in 1986 a completing program was carried out on the dikes, during the end of the eighties and begins of the nineties. Many details about these works and also previous maintenance works are lost. This is because of the several reorganizations that have been taken place. Another reason is that all people from RWS involved in this completing program, retired on pension after the ends of the works, [Mr. J. Boezeman, waterboard Zuiderzeeland, oral communication, 30 October 2006]. However, according to Boezeman, the main part of the maintenance works that was done before 1987 was the reinforcement of the protective cover, which tended to slide away. This can be seen clearly during a period of high water. The parts of the dike where the cover was below the water level were indicated and repaired as soon as the water level decreased. Also from the completing program, some details are lost.

We have one engineering drawing from that time, March 1992, where some works are indicated, see [3]. On this drawing, some parts of the dike are indicated where a new sheet piling had to be placed and where they put new rubles, see ﬁgure E.4.

One of the agreements between the province, waterboard and the State was that the State takes care that the dikes became according to the current safety norms. In 1989, the Minister of Transport, Public Works and Water Management decided that the dikes of the Noordoostpolder and the Flevopolder had to resist an overﬂowing of the IJsselmeer, under circumstances that occurs maximal once per 4000 years. This so called

POSEIDON, ﬁnal report 17 November 2006 104 APPENDIX E. BACKGROUND INFORMATION NOORDOOSTPOLDER

Figure E.4: Locations where in 1992 a new sheet piling is placed in combination with a new layer of rubbles. The details can be seen in the small map, which show the outer slope of the dike.

’1/4000-norm’ is written in the law on the water barriers of the Netherlands (Wet op de Waterkering) in 1996. Not all the dikes fulﬁlled this new norm, so a dike enforcement program was executed, which is more or less ﬁnished for the Noordoostpolder.

Data

This section contains an overview of the used datasets for this project. The general expectations of these datasets are listed in section 5.3, the details of these datasets can be found in A. This description is followed by a table where the used radar images are listed.

The used datasets

Table E gives an overview of the used datasets for this case study. If necessary some remarks are made about the use or availability.

The ascending and descending radar images, used during the processing are listed in table E.2 and table E.3. The dates of the ﬁrst and last image for ascending orbit are 3 May 1992 and 6 December 2000 respectively, for descending orbit these dates are 25 August 1992 and 15 December 2000. As can be seen, there is a gap in the dataset between December 1993 and April 1995. During that time interval, the ERS-1 satellite was used for other purposes. After 1996, the ERS-1 acted as a backup satellite, only activated for special occasions. In 1995 the ERS-2 satellite, which is almost completely similar to the ERS-1, became operational. This satellite is still operational, but has some problems with one of the gyroscopes, which makes that not all images are useful.

POSEIDON, ﬁnal report 17 November 2006 105

Dataset Remarks 1. Radar data (ascending + descending orbit) 2. Topographical map 1:10.000 (Top10vector) 3. DTB (DTB2000) This dataset was only available for a small part of the southern dike. 4. AHN 5. Validation datasets, like leveling data, No validation datasets were available. According to tachymetry or GPS measurements Mr. Boezeman [Mr. J. Boezeman, waterboard Zuiderzeeland, oral communication, 25 October 2006] the IJsselmeer dikes of the Noordoostpolder are never monitored in order to detect deformation. 6. Geotechnical profiles of the dikes The geotechnical profiles do not cover all the dikes. Only the dikes at the south of Urk, are fully covered. 7. Engineering drawings A few engineering drawings related to the dikes are available. According to Mr. Boezeman, [Mr. J. Boezeman, waterboard Zuiderzeeland, oral communication, 30 October 2006], much is lost due to several reorganizations. 8. Borehole measurements and Soil map (1:50.000) These datasets are used when no geotechnical profile was available. 9. Time series ground water level The locations of these time series cover the whole Noordoostpolder. For the Noordoostpolder, as subset of the available data was made, based on the measurement period of the radar. 10. Time series water level IJsselmeer There are time series available for different locations in the IJsselmeer. Here the time series is used from the station at Lemmer. 11. Orthophotos Orthophotos are only available for a small area. This limits the use of this dataset for visualization purposes.

Table E.1: Overview of the used datasets

POSEIDON, ﬁnal report 17 November 2006 106 APPENDIX E. BACKGROUND INFORMATION NOORDOOSTPOLDER

Satellite Orbit Date Btemp (days) B (m) E2 03891 (master) 17-Jan-96 0 0

E1 04182 3-May-92 -1354 -1138 E1 04683 7-Jun-92 -1319 -1284 E1 05184 12-Jul-92 -1284 -898 E1 05685 16-Aug-92 -1249 -68 E1 06186 20-Sep-92 -1214 -85 E1 06687 25-Oct-92 -1179 456 E1 07188 29-Nov-92 -1144 896 E1 07689 3-Jan-93 -1109 -413 E1 08190 7-Feb-93 -1074 119 E1 08691 14-Mar-93 -1039 729 E1 09192 18-Apr-93 -1004 859 E1 09693 23-May-93 -969 -869 E1 10194 27-Jun-93 -934 -690 E1 10695 1-Aug-93 -899 -893 E1 11196 5-Sep-93 -864 -234 E1 11697 10-Oct-93 -829 421 E1 12198 14-Nov-93 -794 833 E1 12699 19-Dec-93 -759 1048 E1 19556 11-Apr-95 -281 -727 E1 20558 20-Jun-95 -211 -19 E1 21059 25-Jul-95 -176 -372 E1 21560 29-Aug-95 -141 537 E1 22061 3-Oct-95 -106 -402 E2 02388 4-Oct-95 -105 -787 E2 03390 13-Dec-95 -35 -313 E2 04392 21-Feb-96 35 -140 E1 24566 26-Mar-96 69 47 E2 04893 27-Mar-96 70 80 E1 25067 30-Apr-96 104 -821 E2 05394 1-May-96 105 -762 E1 25568 4-Jun-96 139 629 E2 05895 5-Jun-96 140 718 E2 06897 14-Aug-96 210 664 E2 07899 23-Oct-96 280 -348 E2 09903 12-Mar-97 420 55 E2 10404 16-Apr-97 455 195 E2 10905 21-May-97 490 -358 E2 11406 25-Jun-97 525 45 E2 11907 30-Jul-97 560 5 E2 12408 3-Sep-97 595 189 E2 12909 8-Oct-97 630 -479 E2 14412 21-Jan-98 735 333 E2 15414 1-Apr-98 805 414 E2 15915 6-May-98 840 148 E2 16416 10-Jun-98 875 115 E2 17418 19-Aug-98 945 -121 E2 17919 23-Sep-98 980 29 E2 18420 28-Oct-98 1015 319 E2 19422 6-Jan-99 1085 1010 E2 21426 26-May-99 1225 -168

Table E.2: Ascending stack, track 029, continued on next page

POSEIDON, ﬁnal report 17 November 2006 107

Satellite Orbit Date Btemp (days) B (m) E2 22428 4-Aug-99 1295 717 E2 24432 22-Dec-99 1435 -583 E2 24933 26-Jan-00 1470 189 E2 25434 1-Mar-00 1505 68 E2 26436 10-May-00 1575 261 E2 27438 19-Jul-00 1645 -440 E2 28440 27-Sep-00 1715 -262 E2 29442 6-Dec-00 1785 -119

Table E.2: Ascending stack, track 029

Satellite Orbit Date Btemp (days) B (m) E2 09023 (master) 10-Jan-97 0 0

E1 05807 25-Aug-92 -1599 93 E1 06308 29-Sep-92 -1564 367 E1 06809 3-Nov-92 -1529 966 E1 07310 8-Dec-92 -1494 492 E1 08312 16-Feb-93 -1424 436 E1 08813 23-Mar-93 -1389 489 E1 09314 27-Apr-93 -1354 1106 E1 09815 1-Jun-93 -1319 -707 E1 10316 6-Jul-93 -1284 -818 E1 10817 10-Aug-93 -1249 170 E1 11819 19-Oct-93 -1179 772 E1 12320 23-Nov-93 -1144 950 E1 19678 20-Apr-95 -631 -104 E1 20680 29-Jun-95 -561 -781 E1 21181 3-Aug-95 -526 358 E2 01508 4-Aug-95 -525 326 E2 02009 8-Sep-95 -490 -964 E1 22183 12-Oct-95 -456 634 E2 03011 17-Nov-95 -420 -974 E1 23185 21-Dec-95 -386 475 E1 24187 29-Feb-96 -316 682 E2 05015 5-Apr-96 -280 -155 E2 06017 14-Jun-96 -210 -305 E2 07019 23-Aug-96 -140 -682 E2 08021 1-Nov-96 -70 1090 E2 10025 21-Mar-97 70 1 E2 11027 30-May-97 140 -250 E2 12029 8-Aug-97 210 172 E2 13031 17-Oct-97 280 150 E2 14033 26-Dec-97 350 -39 E2 15035 6-Mar-98 420 -525 E2 16037 15-May-98 490 711 E2 17039 24-Jul-98 560 -342 E2 18041 2-Oct-98 630 689 E2 19043 11-Dec-98 700 -944 E2 20045 19-Feb-99 770 1220

Table E.3: Descending stack, track 151, continued on next page

POSEIDON, ﬁnal report 17 November 2006 108 APPENDIX E. BACKGROUND INFORMATION NOORDOOSTPOLDER

Figure E.5: The windmills near the IJsselmeer dikes in the Noordoostpolder

Satellite Orbit Date Btemp (days) B (m) E2 21047 30-Apr-99 840 -157 E2 22049 9-Jul-99 910 -122 E2 23051 17-Sep-99 980 -160 E2 24053 26-Nov-99 1050 197 E2 25055 4-Feb-00 1120 -466 E2 25556 10-Mar-00 1155 -23 E2 26558 19-May-00 1225 550 E2 27059 23-Jun-00 1260 -797 E2 28061 1-Sep-00 1330 420 E2 28562 6-Oct-00 1365 104 E2 29063 10-Nov-00 1400 434 E2 29564 15-Dec-00 1435 299

Table E.3: Descending stack, track 151

Preparation of the data

Along the IJsselmeer dike from Urk to Lemmer, the Dutch energy company Essent placed 25 windmills in 1987 and another 25 windmills in 1991, see ﬁgure E.5. These windmills, acts like a kind of corner reﬂectors. In both ascending and descending datasets, almost all windmills are clearly visible. This is because they are surrounded by grass, so the windmills are the only objects that remain coherent. These windmills are used for the georeferencing of the radar data.

For that part of the dike, only the topographical map 1:10.000 (Top10vector) is available. In this map the locations of the windmills are indicated with a symbol. All the visible windmills in both ascending and descending datasets are used for the georeferencing. Because of the sidelobes, the multi reﬂectivity map is used to identify the main lobes. After that the coordinates are extracted from both the radar data and the Top10vector. The mean shifts, for ascending and descending orbit, in North (North) and East (East) direction are given in table E.

The standard deviation of the differences between the ’true’ and translated coordinates represents the relative precision of the georeferencing between the translated radar data and the Top10vector. It can be clearly seen that the precision is quite good, which is due to the reflection characteristics of the windmills. Notice that the PS is located somewhere in the resolution cell, which has a resolution of 2 by 10 meter. This explains why the standard deviation is in the meter level. The difference in ascending and descending orbit is due to the used number of points. Because of the fact that the windmills are almost on the vertical, the relative precision is

POSEIDON, ﬁnal report 17 November 2006 109

Nr. of used ∆East (m) σEast (m) ∆North (m) σNorth (m) points Ascending 18 57 2,61 36 1,29 Descending 31 -60 1,61 13 1,47

Table E.4: Results of the georeferencing better in North direction. The absolute precision is assumed to be equal to the precision of the Top10vector.

Choice of the reference point

The windmills give an excellent opportunity for the choice of the reference point. This is because of the fact that the windmills are clearly visible in both ascending and descending datasets. The windmills are founded on a stable layer by piles with a length of 8 - 12 meter, depending on the subsoil layers, [Mr. C. van Driessen, Essent, oral communication, 27 October 2006]. On top of these piles, there is a concrete plate, where the windmill is placed on. It is never monitored whether these windmills subsides or not. However, the expectation is that this is not the case and until now there are no indications that this expectation is not correct. It is possible that the windmills subside because of a subsidence of the layer where the windmill is founded on. In that case, subsidence is not visible, because the surrounding also subside. But also here, there are no indications for subsidence. It is possible that the windmills move, because of wind. In a wind of gale force 8 - 9, the top can deforms up to 0.5 meter. Under normal conditions, this deformation is not visible. For this case study, one of these windmills is chosen as a reference point.

POSEIDON, ﬁnal report 17 November 2006 110 Appendix F Color images

Figure F.1: Overﬂowing [41] Figure F.2: Wave overtopping [25]

Figure F.3: Nipping ice at the Houtribdijk, the Figure F.4: Piping [41] dike between Lelystad and Enkhuizen [21]

Figure F.5: An example of a plastic horizontal sliding. Here, the dike of Wilnis, a small town Figure F.6: An example of sliding of the inner 30 km southeast of Amsterdam, slid meters aside. slope: This happened in January 2004 near Stein, This happened during a long, hot period in the a town in the Southeast of the Netherlands. In summer of 2003. The dryness caused the peat this case, overﬂowing or wave overtopping did not dike to dry and therefore it became lighter. The cause the sliding of the inner slope, but a leaking strength of the dike appeared to be no match for water pipeline caused saturation of the dike. [29] the water pressure. [7]

111 Figure F.7: Persistent Scatterers in the area of Figure F.8: Radar data Harlingen Harlingen

Figure F.9: Overall Model Test results in ascend- Figure F.10: Overall Model Test results in de- ing track (blue=accept, red=reject) scending track (blue=accept, red=reject)

Figure F.11: Standard deviation of residuals from Figure F.12: Standard deviation of residuals from linear model, ascending track linear model, descending track

112 Figure F.14: Zoom in on area of the bridge (esti- Figure F.13: Interesting areas at Kornwerderzand mated deformation in mm/year)

Figure F.15: Side of the bridge Figure F.16: Visible deformation cracks

Figure F.17: Zoom in on sluice area (estimated Figure F.18: Overview of the North dike (esti- deformation in mm/year) mated deformation in mm/year)

113 Figure F.19: Overall Model Test results for as- Figure F.20: Overall Model Test results for decending track scending track

Figure F.21: Standard deviation of residuals from Figure F.22: Standard deviation of residuals from linear model ascending track linear model descending track

Figure F.23: Rejected points in OMT are repre- Figure F.24: Accepted measurements sented in black

114 Figure F.25: Locations of ascending and descend- Figure F.26: Persistent scatter locations case ing PS-InSAR points of Marken. study Marken

Figure F.27: Result of applying the global overall Figure F.28: Result of applying the global overall model test for the ascending PS-InSAR data. model test for the descending PS-InSAR data.

Figure F.29: Standard deviation of residuals from Figure F.30: Standard deviation of residuals from linear deformation model for the ascending PS- linear deformation model for the descending PS- InSAR data. InSAR data.

115 Figure F.32: Length proﬁle with leveling measure- Figure F.31: Locations of leveling (in red), NAP ments of RWS, November 1996 (in dark blue), De- reference points (in orange) and GPS measure- cember 1997 (in pink), November 1998 (in yellow) ments (in green) of RWS [46]. and November 2001 (in light blue) [46].

Figure F.33: GPS measurements of RWS of November 1996 (in dark blue), December 1997 (in pink), November 1998 (in yellow) and November Figure F.34: The results of the detection step. 2001 (in light blue) [46].

Figure F.36: The results of the Overall Model Test.

Figure F.35: The two groups of PSs for Case B.

116 Figure F.37: Overview of datasets

Figure F.38: Overview of radar data (estimated deformation in mm/year)

Figure F.39: Overview of normalized dataset

Figure F.41: Overview of the dikes and their de- Figure F.40: Normalized dataset in Matlab formation rates from PS-InSAR.

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