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Advances in Remote Sensing for Natural Resource Monitoring

1. Aufl.

von: Prem C. Pandey, Laxmi K. Sharma
179,99 €
Verlag:	Wiley-Blackwell
Format:	PDF
Veröffentl.:	18.01.2021
ISBN/EAN:	9781119616023
Sprache:	englisch
Anzahl Seiten:	528

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Titelbeschreibung

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: <ul> <li>Provides comprehensive coverage of advances and applications of remote sensing in natural resources monitoring</li> <li>Includes new and emerging approaches for resource monitoring with case studies</li> <li>Covers different aspects of forest, water, soil- land resources, and agriculture</li> <li>Provides exemplary illustration of themes such as glaciers, surface runoff, ground water potential and soil moisture content with temporal analysis</li> <li>Covers blue carbon, seawater intrusion, playa wetlands, and wetland inundation with case studies</li> <li>Showcases disaster studies such as floods, tsunami, showing where remote sensing technologies have been used</li> </ul> This edited book is the first volume of the book series Advances in Remote Sensing for Earth Observation.

Inhaltsverzeichnis

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 181 11.5.4 Suitable Sites for Rainwater Harvesting Structures 182 11.6 Conclusions 185 Acknowledgment 186 References 186 12 Structural Control on the Landscape Evolution of Son Alluvial Fan System in Ganga Foreland Basin 189 Manish Pandey, Yogesh Ray, Aman Arora, U.K. Shukla, and Shyam Ranjan 12.1 Introduction 189 12.2 Study Area 192 12.2.1 Geomorphological Setting of SAFS 192 12.2.2 Geology of the Son Valley and SAFS 196 12.2.3 Drainage 196 12.2.4 Climate 197 12.3 Materials and Methods 198 12.3.1 Data Used 198 12.3.2 Preprocessing of DEM 199 12.3.3 DEM Derived Parameters 199 12.3.4 Conceptual Background 199 12.3.4.1 Quantitative Measure of River Basin Dynamics/Reorganization 200 12.3.4.2 X (χ)-Metrics and Cross-Divide χ-Anomaly 200 12.3.4.3 Rationale Behind Experimental Use of χ-Transform for Alluvial Stream Long Profiles 203 12.3.5 Normalized Channel Steepness Index (ksn) and Channel Concavity Index (θ) Computation 205 12.3.6 Stream Sinuosity 205 12.3.7 Hypsometric Curve (HC) 206 12.4 Results and Discussion 206 12.4.1 Zones of (dis)equilibrium Over SAFS in Ganga Foreland Basin (GFB) 206 12.4.2 Sinuosity of Streams and Drainage Behavior Over SAFS 211 12.4.3 Extent of SAFS vis-à-vis Evolution of Ganga Plain 212 12.5 Conclusion and Recommendations 214 Acknowledgments 215 References 215 12.A Appendix A: Supplementary Figures 226 12.B Field Evidences of Neotectonic Activity (Source: Google Earth Pro) 240 12.C Longitudinal Profile of the Ganga and its Right Bank Tributaries Flowing over SAFS 242 12.D Lines of Cross-Sectional and Longitudinal Profiles 244 12.E SAFS Profiles from Pandey 2014 245 Section IV Water Resource Monitoring 247 13 Managing the Blue Carbon Ecosystem: A Remote Sensing and GIS Approach 249 Parul Maurya, Anup Kumar Das, and Rina Kumari 13.1 Introduction 249 13.2 Blue Carbon Ecosystem 249 13.2.1 Distribution 250 13.2.2 Mangrove 251 13.2.3 Seagrass 251 13.2.4 Salt Marshes 252 13.3 Factors Affecting Carbon Storage in Blue Carbon Ecosystems 253 13.4 Carbon Storage in the Blue Carbon Ecosystem 254 13.5 Pathways of Carbon in the Blue Carbon Ecosystem 254 13.6 Evaluation of Long-Term Carbon Deposition in Sediments 255 13.7 Ecosystem Services 256 13.8 Threats to Coastal Blue Carbon Ecosystems 256 13.9 Economy of Blue Carbon Ecosystems 257 13.10 Management 258 13.11 Conservation of Blue Carbon Ecosystem: A Remote Sensing Approach 258 13.11.1 Role of Optical Remote Sensing 259 13.11.2 Mapping the Mangrove Cover and Change Detection 259 13.12 Quantification of Biophysical Variables 260 13.12.1 Phenology 260 13.12.2 Role of Hyperspectral Remote Sensing 260 13.12.3 Mangrove-Mapping and Dynamics Studies Using Radar Data 261 13.12.4 Dependence on Frequency 261 13.12.5 Species Identification 261 13.13 Conclusion 262 Acknowledgment 262 References 262 14 Appraising the Changing Climate and Extent of Snow in the Kashmir Himalaya Using MODIS Data 269 Seema Rani 14.1 Introduction 269 14.2 Study Area 270 14.3 Materials and Methods 271 14.4 Results and Discussions 273 14.4.1 Trend in Air Temperature 273 14.4.2 Trend in Snow Cover Area 275 14.4.3 Variations in SCA Under Elevation Zones 278 14.5 Conclusion 282 Acknowledgments 283 References 283 15 Knowledge-Based Mapping of Debris-Covered Glaciers in the Greater Himalayan Range 287 Swagata Ghosh and Raaj Ramsankaran 15.1 Introduction 287 15.1.1 Overview of Ablation Pattern of Glaciers in the Western Himalaya 288 15.1.2 Overview of Glacier Mapping Techniques 288 15.2 Study Area 290 15.3 Data Sources 291 15.4 Methodology 292 15.4.1 Pre-Processing of Satellite Data 293 15.4.2 Knowledge-Based Approach 295 15.4.2.1 Segregation of Snow and Ice from Other Land Covers Using Spectral Index 295 15.4.2.2 Segregation Between Snow and Ice Types Using Spectral Indices 298 15.4.2.3 Segregation of Supraglacial Debris Types from Non-Glacier Area 298 15.5 Results and Discussions 299 15.5.1 Accuracy Assessment of Supraglacial Covers Mapping of Pensilungpa Glacier 303 15.5.2 Knowledge-Based Approach Versus Manual Digitization for Mapping Pensilungpa Glacier 304 15.5.3 Uncertainty Analysis 306 15.5.4 Knowledge-Based Approach Versus Supervised Classification for Mapping Pensilungpa Glacier 307 15.5.5 Evaluation of Spatiotemporal Application Potential of the Knowledge-Based Approach 311 15.6 Summary and Conclusions 312 15.7 Future Scope 315 References 315 16 Seawater Intrusion and Salinity Mapping in Coastal Aquifers: A Geospatial Approach 323 Tanushree and Rina Kumari 16.1 Introduction 323 16.1.1 Water Stress in Coastal Aquifers Due to Salinity: A Global Concern 323 16.1.2 Salinization of Aquifers in Semiarid Regions 324 16.1.3 Seawater Intrusion: Basic Concept 324 16.1.4 Various Approaches to Study Seawater Intrusion 325 16.2 Aquifer Vulnerability Concept 326 16.2.1 Vulnerability Types 327 16.2.1.1 Intrinsic Vulnerability 327 16.2.1.2 Specific Vulnerability 327 16.2.2 Aquifer Vulnerability Due to Seawater Intrusion 327 16.2.3 Methods to Assess Vulnerability 327 16.2.3.1 Sensitivity Analysis 328 16.2.4 Significance 331 16.2.5 Geophysical Approaches 332 16.2.5.1 Electromagnetic Surveys 332 16.2.5.2 Time Domain Electromagnetic (TDEM) 333 16.2.5.3 Frequency Domain Electromagnetic (FEM) 333 16.2.5.4 Self-Potential 333 16.2.5.5 Ground Penetrating Radar 333 16.2.6 Numerical Model for Explaining Seawater Intrusion 334 16.2.7 Remote Sensing for Salinity Mapping 334 16.2.7.1 Optical Remote Sensing for Salinity Mapping 334 16.2.7.2 Hyperspectral Remote Sensing 335 16.2.7.3 Microwave Remote Sensing for Salinity Mapping 335 16.3 Conclusion 336 Acknowledgments 337 References 337 17 Wetland-Inundated Area Modeling and Monitoring Using Supervised and Machine Learning Classifiers 346 Swapan Talukdar, Sakshi Mankotia, Md Shamimuzzaman, Shahfahad, and Susanta Mahato 17.1 Introduction 346 17.2 Study Area 348 17.3 Data Sources and Methods 349 17.3.1 Data Sources 349 17.3.2 Methods for Wetland-Inundated Area Mapping 349 17.3.2.1 Methods for Machine Learning Classifiers 350 17.3.2.2 Method for Supervised Classifiers 352 17.3.3 Methods for Accuracy Assessment of Wetland-Inundation Area Mapping 352 17.3.4 Methods of Modeling Wetland Landscape Transformation 353 17.4 Results and Discussion 353 17.4.1 Wetland Mapping Using Different Classifiers 353 17.4.2 Validation of the Methods 354 17.4.3 Spatiotemporal Analysis of Hydrological Variability of the Wetlands 356 17.4.4 Fragmentation Analysis of the Hydrological Variability 357 17.5 Conclusion 360 Acknowledgment 360 References 360 18 A Focus on Reaggregation of Playa Wetland scapes in the Face of Global Ecological Disconnectivity 366 Laxmi Kant Sharma, Rajashree Naik, and Prem Chandra Pandey 18.1 Introduction 366 18.2 Global Ecological Disconnectivity 367 18.3 Playa Wetland scapes 367 18.3.1 Importance 368 18.3.2 Threats 368 18.3.3 Playas of India 370 18.4 Indian Playa Wetland scapes for Global Ecological Connectivity 371 18.5 Reaggregation of Playa Wetland scapes 374 18.6 Recent Approaches Used for Wetland scape Studies 375 18.7 Limitations of Current Wetland scape Studies 377 18.8 Scope of Integrated Playa Wetland scape Modeling 380 Acknowledgment 381 References 381 Section V Disaster Monitoring of Natural Resources 389 19 Flood Damage Assessment in a Part of the Ganga-Brahmaputra Plain Region, India 391 Rajesh Kumar 19.1 Introduction 391 19.2 Study Area 393 19.3 Materials and Methods 393 19.4 Results and Discussion 395 19.4.1 Flood-Prone and Flooded Areas 395 19.4.2 Flood Damage and Flood Protection Works 396 19.4.3 Trends in Flood Damage and Peak Flood Discharge 398 19.5 Conclusions 400 Acknowledgments 401 Declaration 401 References 401 20 Texture-Based Riverine Feature Extraction and Flood Mapping Using Satellite Images 405 Kuldeep, P.K. Garg, and R.D. Garg 20.1 Introduction 405 20.2 Related Work 406 20.3 The Study Area and Data Resources 408 20.4 Methodology 408 20.4.1 Geometric Correction and Image Enhancement 408 20.4.2 Texture Feature Extraction and Optimal Feature Selection 409 20.4.3 Texture-Based Classification 411 20.4.4 Flood Hazard Mapping for Identification of Safe Islands 411 20.4.4.1 Flood Inundation Mapping 411 20.4.4.2 Validation of Flood Extent 412 20.4.4.3 Damage Assessment 412 20.5 Results and Discussions 413 20.5.1 Feature Selection and Classification 413 20.5.2 Flood Hazard Mapping 418 20.5.3 HEC-RAS Processing and Model Validation 419 20.5.4 Flood Damage Assessment 421 20.6 Conclusion 424 Acknowledgment 426 References 426 21 Numerical Simulation and Comparison of Tsunami Inundation for Different Satellite-Derived Datasets for the Gujarat Coast of India 431 Shafique Matin and S.S. Praveen 21.1 Introduction 431 21.2 Study Area 432 21.3 Methodology 432 21.3.1 Extraction of Different Satellite-Derived Datasets 432 21.3.2 Numerical Modeling 434 21.4 Results and Discussion 436 21.4.1 Analysis of Datasets 439 21.4.2 Parallel Transects 440 21.4.3 Perpendicular Transects 440 21.5 Conclusions 442 Acknowledgments 442 References 443 Section VI Future Aspect of Natural Resource Monitoring 445 22 Future Aspects and Potential of the Remote Sensing Technology to Meet the Natural Resource Needs 447 Laxmi Kant Sharma, Rajit Gupta, and Prem Chandra Pandey 22.1 Introduction 447 22.2 Advances in Remote Sensing for Natural Resources Monitoring 449 22.3 Potential Applications in Natural Resource Monitoring 451 22.4 Challenges and Future Aspects 453 22.5 Conclusion 455 Acknowledgment 456 References 456 Index 465

Autorenportrait

Dr Prem C. Pandey is Assistant Professor in the Center for Environmental Sciences & Engineering, Shiv Nadar University, UP, India.Dr Laxmi K. Sharma is Associate Professor, at the Department of Environmental Science, Central University of Rajasthan, Ajmer, India.

Back cover copy

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 Resource 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:<ul><li><bl>Provides comprehensive coverage of advances and applications of remote sensing in natural resources monitoring</bl></li><li><bl>Includes new and emerging approaches for resource monitoring with case studies</bl></li><li><bl>Covers different aspects of forest, water, soil- land resources, and agriculture</bl></li><li><bl>Provides exemplary illustration of themes such as glaciers, surface runoff, ground water potential and soil moisture content with temporal analysis</bl></li><li><bl>Covers blue carbon, seawater intrusion, playa wetlands, and wetland inundation with case studies</bl></li><li><bl>Showcases disaster studies such as floods, tsunami, showing where remote sensing technologies have been used</bl></li></ul>This edited book is the first volume of the book series Advances in Remote Sensing for Earth Observation.