Buch, Englisch, 528 Seiten, Format (B × H): 175 mm x 250 mm, Gewicht: 1072 g
ISBN: 978-1-119-61597-2
Verlag: Wiley
Sustainable management of natural resources is an urgent need, given the changing climatic conditions of Earth systems. The ability to monitor natural resources precisely and accurately is increasingly important. New and advanced remote sensing tools and techniques are continually being developed to monitor and manage natural resources in an effective way. Remote sensing technology uses electromagnetic sensors to record, measure and monitor even small variations in natural resources. The addition of new remote sensing datasets, processing techniques and software makes remote sensing an exact and cost-effective tool and technology for natural resource monitoring and management.
Advances in Remote Sensing for Natural Resources Monitoring provides a detailed overview of the potential applications of advanced satellite data in natural resource monitoring. The book determines how environmental and - ecological knowledge and satellite-based information can be effectively combined to address a wide array of current natural resource management needs. Each chapter covers different aspects of remote sensing approach to monitor the natural resources effectively, to provide a platform for decision and policy. This important work:
- Provides comprehensive coverage of advances and applications of remote sensing in natural resources monitoring
- Includes new and emerging approaches for resource monitoring with case studies
- Covers different aspects of forest, water, soil- land resources, and agriculture
- Provides exemplary illustration of themes such as glaciers, surface runoff, ground water potential and soil moisture content with temporal analysis
- Covers blue carbon, seawater intrusion, playa wetlands, and wetland inundation with case studies
- Showcases disaster studies such as floods, tsunami, showing where remote sensing technologies have been used
This edited book is the first volume of the book series Advances in Remote Sensing for Earth Observation.
Autoren/Hrsg.
Weitere Infos & Material
List of Abbreviations xix
List of Contributors xxix
List of Editors xxxv
Preface xxxvii
Section I General Section 1
1 Introduction to Natural Resource Monitoring Using Remote Sensing Technology 3
Prem Chandra Pandey and Laxmi Kant Sharma
1.1 Introduction 3
References 6
2 Spectroradiometry: Types, Data Collection, and Processing 9
Prem Chandra Pandey, Manish Kumar Pandey, Ayushi Gupta, Prachi Singh, and Prashant K. Srivastava
2.1 Introduction 9
2.2 Literature Review 10
2.3 The Types of Spectroradiometry 12
2.3.1 Spectroradiometry 13
2.3.2 Photometry and Colorimetry 13
2.4 Principle of the Spectroradiometer 13
2.5 Radiance Measurement 16
2.5.1 Factors Affecting Spectral Reflectance Measurements 17
2.5.2 Data Processing 18
2.5.2.1 Radiometric Calibration 18
2.5.2.2 Reflectance/Transmittance 19
2.5.2.3 Radiance/Irradiance/Emissivity 20
2.5.2.4 1st Derivative 20
2.5.2.5 2nd Derivative 20
2.5.2.6 Parabolic Correction 20
2.5.2.7 Other Methods 21
2.6 Data Collection 21
2.7 Generation of the Metadata 21
2.7.1 Continuum Removal 22
2.8 Applications of ASD in Agriculture and Forestry 23
2.9 Future Importance, Limitations, and Recommendations 23
Acknowledgment 24
References 24
3 Geometric-Optical Modeling of Bidirectional Reflectance Distribution Function for Trees and Forest Stands 28
Nour El Islam Bachari, Salim Lamine, and Khaled Meharrar
3.1 Introduction 28
3.2 Model Description 29
3.2.1 Sunlit Surfaces 31
3.2.2 Shaded Surfaces 31
3.2.3 Forest Stand Modeling 32
3.3 General Shape of the Apparent Luminance 33
3.4 Simulation and Discussion 35
References 39
Section II Vegetation Resource Monitoring (Forest and Agriculture) 43
4 Mapping Stand Age of Indonesian Rubber Plantation Using Fully Polarimetric L-Band Synthetic Aperture Radar 45
Bambang H. Trisasongko
4.1 Introduction 45
4.2 Methodology 46
4.2.1 Test Site and Dataset 46
4.2.2 Processing 47
4.3 Results and Discussion 48
4.3.1 Scattering Behavior 48
4.3.2 Classification Using Backscatter Coefficients 50
4.3.3 Classification Using Model-Based Decomposition 51
4.3.4 The Role of Combining Datasets 51
4.3.5 The Best Subset 52
4.4 Conclusion 55
Acknowledgments 55
References 55
5 Responses of Multi-Frequency Remote Sensing to Forest Biomass 58
Suman Sinha, A. Santra, Laxmi Kant Sharma, Anup Kumar Das, C. Jeganathan, Shiv Mohan, S.S. Mitra, and M.S. Nathawat
5.1 Background 58
5.1.1 Optical Remote Sensing 59
5.1.2 Microwave Remote Sensing 62
5.1.3 LiDAR Remote/Sensing 63
5.1.4 Synergic Use of Multi-Sensor Data 65
5.2 A Case Study in the Mixed Tropical Deciduous Forest of India 66
5.2.1 Study Area 66
5.2.2 Datasets 67
5.2.3 Methodology 67
5.2.4 Results 67
5.2.5 Conclusion 67
5.3 Uncertainties and Future Scope of Research in Biomass Estimation 71
5.3.1 Summary 71
Acknowledgment 72
References 72
6 Crop Water Requirements Analysis Using Geoinformatics Techniques in the Water-Scarce Semi-Arid Watershed 81
K. Ibrahim-Bathis, S.A. Ahmed, V. Nischitha, and M.A. Mohammed-Aslam
6.1 Introduction 81
6.1.1 Crop Calendar 82
6.1.2 Crop Type Classification 83
6.1.3 Crop Water Requirements 86
6.1.4 CROPWAT Model 86
6.1.5 Meteorological Data 86
6.2 Reference Evapotranspiration (ETo) 86
6.2.1 Effective Rainfall 88
6.2.2 Crop Coefficient (Kc) 89
6.3 Soil Data 89
6.4 Crop Evapotranspiration (ETc) 90
6.5 Irrigation Water Requirement 90
6.6 Conclusion 91
Acknowledgment 92
References 92
7 Biophysical Characterization and Monitoring Large-Scale Water and Vegetation Anomalies by Remote Sensing in the Agricultural Growing Areas of the Brazilian Semi-Arid Region 94
Antônio Heriberto de Castro Teixeira, Janice Freitas Leivas, Edson Patto Pacheco, Edlene Aparecida Monteiro Garçon, and Celina Maki Takemura
7.1 Introduction 94
7.2 Material and Methods 96
7.3 Results and Discussion 99
7.4 Conclusions 104
Acknowledgments 105
References 105
Section III Soil and Land Resource Monitoring 111
8 SMOS L4 Downscaled Soil Moisture Product Evaluation Over a Two Year – Period in a Mediterranean Setting 113
Patrick N.L. Lamptey, George P. Petropoulos, and Prashant K. Srivastava
8.1 Introduction 113
8.2 Experimental Setup 116
8.3 Datasets Description 116
8.3.1 SMOS L4 SM Product (1 km) 116
8.3.2 In-situ Soil Moisture Data 118
8.4 Methodology 119
8.4.1 SSM Extraction from SMOS 119
8.4.2 Pre-Processing of SMOS 119
8.4.3 Agreement Evaluation 119
8.5 Results 120
8.5.1 Station ES-CPA 120
8.5.2 Station N9 122
8.5.3 Station M5 123
8.5.4 Station H7 123
8.5.5 Station K9 124
8.6 Discussion 126
8.7 Conclusions 127
Acknowledgments 128
References 128
9 Estimating Urban Population Density Using Remotely Sensed Imagery Products 132
Dimitris Triantakonstantis, Demetris Stathakis, and Zoi Papadopoulou
9.1 Introduction 132
9.2 Spatial Data Disaggregation–MAUP Problem 134
9.2.1 Spatial Interpolation 135
9.3 Materials and Methods 136
9.3.1 Study Area and Data Sources 136
9.3.2 Areal Interpolation Using Cokriging 137
9.4 Areal Interpolation Using Geographically Weighted Regression (GWR) 138
9.5 Results and Discussion 139
9.6 Conclusions 144
References 145
10 Impact of Land Cover Change on Surface Runoff 150
Apoorv Sood, S.K. Ghosh, and Priyadarshi Upadhyay
10.1 Introduction 150
10.2 Literature 151
10.3 Methodology 152
10.3.1 Supervised Classification 152
10.3.2 SWAT Model 153
10.3.3 SWAT Inputs 153
10.3.4 SWAT Outputs 154
10.4 Methodology 154
10.5 Study Area 154
10.5.1 Justification for Study Area Selection 154
10.6 Data Used 155
10.6.1 Weather Data 156
10.6.2 Satellite Data 158
10.6.2.1 LANDSAT Dataset 158
10.6.3 Digital Elevation Model 158
10.6.4 Soil Map 158
10.7 Results and Discussion 158
10.7.1 LU/LC Classification 158
10.7.2 LU/LC Map 1987 161
10.7.3 LU/LC Map 1997 161
10.7.4 LU/LC Map 2007 161
10.7.5 LU/LC Map 2017 161
10.7.6 Watershed Delineation 163
10.8 SWAT Results 164
10.8.1 HRU Analysis Report 164
10.8.2 Runoff Generated in Sub Basins 164
10.9 Conclusion 167
Acknowledgment 168
References 168
11 Delineation of Groundwater Potential Zone and Site Suitability of Rainwater Harvesting Structures Using Remote Sensing and In Situ Geophysical Measurements 170
Prachi Singh, Akash Anand, Prashant K. Srivastava, Arjun Singh, and Prem Chandra Pandey
11.1 Introduction 170
11.2 Study Area 171
11.3 Data Used and Methodology 172
11.3.1 Data Used 172
11.3.2 Methodology 173
11.3.3 Vertical Electrical Sounding 173
11.3.4 Weightage Calculation 174
11.4 Results and Discussion 175
11.4.1 Land Use and Land Cover (LULC) 175
11.4.2 Soil 175
11.4.3 Hydro-Geomorphology 176
11.4.4 Lithology 176
11.4.5 Drainage Density 178
11.4.6 Lineament Density 178
11.5 Resistivity Survey 179
11.5.1 VES Survey and Cross Section 179
11.5.2 Interpolated Subsurface Soil Profile 181
11.5.3 Groundwater Potential Zone 1
