本书共有两卷，此为第2卷。主要内容为(1)提供了有关地球科学遥感数据的信息：(2)讨论了MODIS探测器的校正和特点；(3)对当前数据处理方法进行分析和评价；(4)介绍了不同数据中心的数据查询和定购；以及(5)探讨了遥感和地理信息系统产品——网络GIS应用和工具等内容。该书内容既包括现代遥感技术的基础知识，又涉及卫星遥感的前沿领域，有广泛的实用性，可作为遥感、地学、环境、空间信息等地球科学领域的专业参考书。

本书共有两卷。此为第2卷，共有18章，主要内容为(1)提供了有关地球科学遥感数据的信息：(2)讨论了MODIS探测器的校正和特点；(3)对当前数据处理方法进行分析和评价；(4)介绍了不同数据中心的数据查询和定购；以及(5)探讨了遥感和地理信息系统产品——网络GIS应用和工具等内容。

该书作者均为相关领域具有权威性的专家与学者。图书内容既包括现代遥感技术的基础知识，又涉及卫星遥感的前沿领域，有广泛的实用性，可作为遥感、地学、环境、空间信息等地球科学领域的专业参考书。

List of Contributors xv

1 Introduction to Data, Computational Processing and Tools of Satellite Remote Sensing 1

References 9

2 Earth Science Satellite Remote Sensing Data from the EOS Data and Information System 11

2.1 Introduction 11

2.2 EOSDIS Core System 14

2.3 Science Computing Facilities and Science Investigator-Led Processing Systems 14

2.4 Data Access 15

2.5 Perspectives 16

3 Remotely Sensed Data Available from the US Geological Survey EROS Data Center 18

3.1 Introduction 18

3.2 Data Products 19

3.2.1 Aircraft Scanners 23

3.2.2 Satellite Data 25

3.2.3 Derived Satellite Data Products 46

3.3 Conclusions 50

Acknowledgements 51

References 51

4 NASA Direct Readout for Its Polar Orbiting Satellites 52

4.1 Introduction 52

4.2 Context in History 52

4.3 The Next Step 56

4.4 DB Community 57

4.5 Technologies and Data Flows in Direct Broadcast and Direct Readout 58

4.6 A DB Model 60

4.7 Technology Roadmap 61

4.7.1 Multi-Mission Scheduler 62

4.7.2 Real-Time Software Telemetry Processing System 63

4.7.3 Simulcast 69

4.7.4 NEpster 71

4.8 Science Processing Algorithm Wrapper (SPA) 72

4.9 The Future of DB and DR 74

Acknowledgements 75

References 76

5 MODIS Calibration and Characterization 77

5.1 Instrument Background 77

5.2 MODIS Pre-Launch Calibration and Characterization 80

5.2.1 Pre-Launch Calibration of the Reflective Solar Bands 80

5.2.2 Pre-Launch Calibration of the Thermal Emissive Bands 82

5.2.3 Pre-Launch Spatial and Spectral Characterization 83

5.2.4 Pre-Launch Calibration and Characterization Summary 85

5.3 MODIS On-Orbit Calibration and Characterization 86

5.3.1 Reflective Solar Bands Calibration Algorithm and Performance 86

5.3.2 Thermal Emissive Bands Calibration Algorithm and Performance 89

5.3.3 On-Orbit Spatial and Spectral Characterization 91

5.3.4 Special Considerations and Activities 94

5.4 Summary 96

References 96

6 Use of the Moon for Calibration and Char acterization of MODIS,SeaWiFS, and VIRS 98

6.1 Introduction 98

6.1.1 The Lunar Radiometric Model 99

6.1.2 MODIS 99

6.1.3 SeaWiFS 101

6.1.4 VIRS 102

6.2 Lunar Calibration and Characterization of MODIS 103

6.2.1 MODIS Lunar Calibration Approaches and Applications 103

6.2.2 MODIS Lunar Calibration Results 105

6.3 Lunar Calibration and Characterization of SeaWiFS 108

6.3.1 SeaWiFS Lunar Calibration Approaches and Applications 108

6.3.2 SeaWiFS Lunar Calibration Results 110

6.4 Lunar Calibration and Characterization of Visible and Infrared Scanner 113

6.4.1 VIRS Lunar Calibration Approaches and Applications 113

6.4.2 VIRS Lunar Calibration Results 114

6.5 Using the Moon for Inter-Comparison of Sensors' On-Orbit

Radiometric Calibrations 116

6.6 Summary 118

References 118

7 A Review of Remote Sensing Data Formats for Earth System Observations 120

7.1 Introduction 120

7.1.1 Vector and Raster (or Feature and Grid) Data 120

7.1.2 Georectified Data and Georeferenced Data 121

7.1.3 Metadata 122

7.2 Hierarchical Data Format 123

7.2.1 The Physical Layout of HDF 123

7.2.2 Attribute 124

7.2.3 HDF Data Models 125

7.2.4 The HDF SDS Data Model 125

7.2.5 The HDF SD API and Programming Model 126

7.3 HDF-EOS 126

7.3.1 The Point Data Model 127

7.3.2 The Swath Data Model 127

7.3.3 The Grid Data Model 129

7.3.4 The HDF-EOS APIs and Programming Models 129

7.3.5 HDF-EOS Versus Native HDF 130

7.4 HDF5 131

7.4.1 The Physical Layout of HDF5 131

7.4.2 HDF5 Data Models 133

7.4.3 HDF5 API and Programming Model 134

7.5 HDF5-Based HDF-EOS 136

7.5.1 HDF-EOS5 Data Structure 136

7.5.2 HDF-EOS5 Programming Model 137

7.6 NITF 137

7.6.1 The Physical Layout of NITF 138

7.6.2 The NITF Header 138

7.6.3 The NITF Image Data Segment 139

7.6.4 The NITF Related So,are 139

7.7 TIFF and GeoTIFF 140

7.7.1 The Physical Layout of TIFF 140

7.7.2 The TIFF Data Model 141

7.7.3 GeoTIFF 142

7.8 Summary 144

Acknowledgements 144

References 145

8 A Simple, Scalable, Script-Based Science Processor 146

8.1 Genesis of the Simple, Scalable, Script-Based Science Processor 146

8.2 Architecture and Design 147

8.2.1 The S4P Kernel 147

8.2.2 Lessons Learned from Other Systems 148

8.3 Design Principles 149

8.3.1 Design for Trouble 149

8.3.2 Keep It Simple 151

8.4 How S4P Works 152

8.4.1 Stations and the Stationmaster Daemon 152

8.4.2 Monitoring Stations and Jobs 153

8.4.3 Station Configurability 154

8.5 S4P Reuse 154

8.5.1 On-Demand Subsetting 155

8.5.2 Near-Archive Data Mining 155

8.5.3 Direct Broadcast Processing at IMaRS 156

8.5.4 S4P for Missions 156

8.6 S4P for Missions Implementation 156

8.6.1 Data Flow Initiation 157

8.6.2 Algorithm Preparation 158

8.6.3 Algorithm Execution 159

8.6.4 Data Archive Interface 159

8.6.5 Data Management 159

8.7 Future Development 160

8.7.1 Case-Based Reasoning 160

8.7.2 Open-Source S4PM 160

8.8 Conclusions 160

References 161

9 The MODIS Reprojection Tool 162

9.1 Introduction 162

9.2 MRT Functional Capabilities 163

9.2.1 The MRT GUI 163

9.2.2 Parameter Files 166

9.2.3 Log File 166

9.2.4 Mosaicking 166

9.2.5 Map Projections 167

9.2.6 Resampling Process 169

9.2.7 SDS Subsets 171

9.2.8 Spatial Subsets 171

9.2.9 Format Conversion 172

9.2.10 Metadata 173

9.3 Special Considerations :. 176

9.3.1 Bounding Tiles 176

9.3.2 Crossing the International Dateline 176

9.4 Summary 177

Acknowledgements 177

References 177

10 A Tool for Conversion of Earth Observing System Data Products to GIS Compatible Formats and for the Provision of

Post-Processing

Functionality 178

10.1 Introduction 178

10.2 Functionality 180

10.3 GUI Overview 181

10.4 Access 183

10.5 Data Sets Tested and Examples of Usage 184

10.6 Conclusions 189

References 189

11 HDFLook--Multifunctional HDF-EOS Tool for MODIS and AIRS Data Processing at GES DISC DAAC 190

11.1 Introduction 190

11.2 HDFLook Main Features 190

11.2.1 CommonHDFLookHDF-EOS Features 191

11.2.2 HDFLook MODIS Functions 192

11.2.3 HDFLook AIRS Functions 194

11.2.4 High-Level Script Features 195

11.3 GES DISC DAAC HDFLook Applications 197

11.3.1 MODIS/Terra and MODIS/Aqua Browse Imagery 197

11.3.2 On-the-Fly Spatial Subsetting of Data from the GES DISC DAAC Data Pool 198

11.3.3 MODIS L3 Atmospheric Products Online Visualization and Analysis System 198

11.4 Global MODIS Browse Imagery 198

11.5 HDFLook Releases and Distribution 200

11.6 Conclusions 200

Acknowledgements 200

References 200

12 Tropical Rainfall Measuring Mission Data and Access Tools 202

12.1 Introduction 202

12.1.1 TRMM Science 202

12.1.2 TRMM Orbit and Instruments 203

12.1.3 TRMM Ground Validation Sites and Field Experiments 204

12.2 TRMM Products 206

12.2.1 TRMM Standard Products 206

12.2.2 TRMM Subsets 206

12.3 TRMM Field Experiment Data Sets 212

12.3.1 Field Experiment Data 212

12.3.2 Ancillary Data 212

12.4 Tools for Data Visualization and Analysis 213

12.4.1 TSDIS Orbit Viewer 213

12.4.2 TOVAS 215

12.5 TRMM Data Access and Usage 215

12.6 TRMM Applications 217

Acknowledgements 218

References 218

13 The Open GIS Web Service Specifications for Interoperable Access and Services of NASA EOS Data 220

13.1 Introduction 220

13.2 NASA EOSDIS Data Environment 221

13.3 The OGC Web-Based Interoperable Data Access Technology 223

13.3.1 Web Coverage Service Implementation Specification 224

13.3.2 Web Feature Service Specification 225

13.3.3 Web Map Service Specification 226

13.3.4 Web Registry Service Specification 227

13.3.5 Results 228

13.4 Applying OGC Technology to the NASA EOS Data Environment 228

13.5 The Current Implementation Status of the OGC Technology 229

13.6 The Anticipated Impacts on End Users 230

References 231

14 Global MODIS Remote Sensing Data for Local Usage:Vaccess/MAGIC 233

14.1 Introduction 233

14.2 MODIS Data Processing for Regional Use 235

14.2.1 MODIS Vegetation Index and LAI Data Processing 236

14.2.2 MODIS Cloud Mask Data Processing 239

14.3 MODIS Real-Time Data Processing 240

14.4 Summary and Discussions 243

References 243

15 The NASA HDF-EOS Web GIS Software Suite 245

15.1 Introduction 245

15.2 The Current NWGISS Components and Their Functionalities 246

15.3 The Integration of NWGISS with Grid Technology 248

15.4 The Development of Geospatial Web Services in NWGISS 249

15.4.1 The Interoperable Data Provider Tier 250

15.4.2 The Middleware Geospatial Service and Knowledge

Management Tier 251

15.4.3 The Integrated Multiple-Protocol Geoinformation Client Tier 252

15.5 Conclusions 252

Acknowledgements 252

References 253

16 Network Geographic Information System 254

16.1 Introduction 254

16.2 Network Infrastructure 255

16.3 Distributing GIS Functions 259

16.4 Distributed GIS 262

16.5 Network GIS Taxonomy 263

16.6 Examples of Network GIS 264

16.7 Research Topics in Network GIS 267

Acknowledgements 268

References 269

17 A Content-Based Search Method and Its Application for EOS 272

17.1 Introduction 272

17.2 Method 273

17.2.1 Pyramid Model 274

17.2.2 Histograms 274

17.2.3 Clustering and Type I Query 275

17.2.4 Type n Query Algorithms 276

17.3 Prototype System 279

17.4 Results 281

17.4.1 Data and Pyramid Structure 281

17.4.2 Clustering Criteria 282

17.4.3 Type I Query Processing Procedure 284

17.4.4 Results from the Prototype System 286

17.5 Conclusions and Future Work 287

Acknowledgements 289

References 289

18 The Impact of Precipitation and Temperature on Net Primary Productivity in Xinjiang, China from 1981 to 2000 292

18.1 Introduction 292

18.2 Material and Methods 293

18.2.1 Study Area 293

18.2.2 The NPP Estimation with GLO-PEM Model 294

18.2.3 The NPP Estimation with CEVSA Model 296

18.3 Results and Discussion 297

18.3.1 A Comparison Between Estimated NPP with the GLOPEM and CEVSA 297

18.3.2 Precipitation and Temperature Impact on NPP 298

18.4 Conclusions 303

Acknowledgements 304

References 304

Appendix A Earth Science Remote Sensing Data and Services and Information Technology at the NASA/GES DISC DAAC 306

A.1 Introduction 306

A.I.1 What is the DISC--Mission Statement 306

A. 1.2 What else is the DISC 306

A. 1.3 Disciplines, Measurements, Missions, and Applications 307

A.2 An Integrated Organization 309

A.2.1 Engineering 309

A.2.2 Systems Execution 310

A.2.3 Data Support 310

A.2.4 Mission Support 310

A.2.5 An Integrated GES DAAC 310

A.3 Utilizing Information Technology: Data, Information, Services 311

A.3.1 Data Access, Visualization and Analysis Tools 311

A.3.2 Examining Advanced Technologies 313

A.4 Evolving the GES DISC 314

A.4.1 Why Evolve Earth Science Data Systems 314

A.4.2 GES DISC Evolution 315

A.4.3 The Evolved GES DISC 316

A.5 Summary 317

Appendix B 318

B.1 A C Code Example for the HDF SD APl 318

B.2 A C Code Example for the HDF-EOS SW API 320

B.3 A C Code Segment for the HDF-EOS GD APl 322

B.4 A C Code Example for the HDF5 API 323

B.5 A C Code Example for the HDF-EOS5 SW API 326

Appendix C Internet Links for Data Access (Search and Order) 329

Index 330