CONTENTS
Acknowledgements !
Table of Contents iii
List of figures vi
List of tables ix
List of abbreviations x
Chapter 1 General Introduction 1
1.1Justification and need to estimate irrigated rice yield using
earth observation 2
1.2 Opportunities and challenges of using RS for crop yield estimation 5
1.3 Objectives of the thesis 8
Chapter 2 Mapping rice cropping patterns 13
2.1Introduction 15
2.2Data and methods 18
2.2.1Rice cultivation in the Mekong delta 18
2.2.2 Data 19
2.2.3 Image classification 20
2.2.4 Construction of the rice cropping pattern map 22
2.2.5Validation 23
2.3 Results 23
2.3.1Unsupervised classification 23
2.3.2 Rice cropping pattern map 25
2.3.3 Validation 29
2.4 Discussion and conclusions 29
Acknowledgment 33
Chapter 3 LaHMa: a new method to map landscape heterogeneity 35
3.1 Introduction 37
3.1.1 Spatial hererogeneity 37
3.1.2 Hyper-temporal NDVI Images 39
3.1.3 The ISODATA clustering technique and cluster separability
Indices 40
3.2 Materials and Method 43
3.2.1 Data 43
3.2.2 Method 44
3.3 Results 47
3.2.1ISODATA clustering of the hyper-temporal NDVI image
Datasets 47
3.2.2 The ISODATA generated land unit maps and their NDVI
Profiles 49
3.2.3 The landscape heterogeneity maps 50
3.3 Discussion 51
Chapter 4 Remote sensing of leaf area index for irrigated rice 55
4.1 Introduction 57
4.2 Materials 59
4.2.1 Study area 59
4.2.2 MODISdata 60
4.2.3 In situ LAI 61
4.2.4 Leaf chlorophyll content 61
4.3 Methods 62
4.3.1Comparison of in situ LAI and MOD15A2 LAI 62
4.3.2 The SLC model 63
4.3.3 LAI estimation based on the look-up table inversion 65
4.4 Results and Discussion 67
4.4.1 Comparison of in situ LAI and MOD15A2 product 67
4.4.2 LAI estimation from LUT inversion 70
4.5 Conclusion 75
Acknowledgement 76
Chapter 5 Coupling remotely sensed LAI with a crop growth model for rice yield estimation 77
5.1 Introduction 81
5.2 Materials and Methods 83
5.2.1Data 83
5.2.2 LAI estimation through soil-leaf-canopy RTM using MODIS reflectance data 84
5.2.3 Yield estimation using ORYZA2000 crop model 85
5.3 Results and Discussion 87
5.3.1Rice LAI estimation by SLC model 87
5.3.2 Assimilation of SLC LAI into ORYZA200 model and rice yield
Estimation 88
5.4 Conclusion 91
Acknowledgement 93
Chapter 6 General Discussion: Earth observation for rice heterogeneity mapping and yield estimation 95
6.1 Hyper-temporal SPOT VGT NDVI for rice cropping pattern
Mapping 96
6.2 A comparison of SPOT VGT and MODIS Terra NDVI data for
mappingagroecological heterogeneity at landscape level 97
6.3 Seasonal LAI estimation for irrigated rice by inversion of
radiative transfer model 98
6.4 Forcing remotely sensed LAI into ORYZA2000 crop growth
simulation model for rice yield estimation 99
6.5 Conclusions 100
6.6 Recommendations: future research and development 102
Bibliography 105
Summary 129
Samenvatting 131
Publications 133
Curriculum vitae 135
ITC Dissertation List 137