本書共有兩卷。此為第2卷，共有18章，主要內容為（1）提供了有關地球科學遙感數據的信息；（2）討論了MODIS探測器的校正和特點；（3）對當前數據處理方法進行分析和評價；（4）介紹了不同數據中心的數據查詢和定購；以及（5）探討了遙感和地理信息系統產品——網路GIS套用和工具等內容。該書作者均為相關領域具有權威性的專家與學者。圖書內容既包括現代遙感技術的基礎知識，又涉及衛星遙感的前沿領域，有廣泛的實用性，可作為遙感、地學、環境、空間信息等地球科學領域的專業參考書。
基本介紹
- 書名：地球衛星遙感:數據計算的過程和工具
- 出版社：清華大學出版社
- 頁數：335頁
- ISBN：7302128553, 9787302128557
- 作者：曲 (Qu.J.J.) 等
- 出版日期：2006年9月1日
- 開本：16開
- 品牌：清華大學出版社
基本介紹,內容簡介,作者簡介,圖書目錄,
基本介紹
內容簡介
本書共有兩卷。此為第2卷，共有18章，主要內容為（1）提供了有關地球科學遙感數據的信息；（2）討論了MODIS探測器的校正和特點；（3）對當前數據處理方法進行分析和評價；（4）介紹了不同數據中心的數據查詢和定購；以及（5）探討了遙感和地理信息系統產品——網路GIS套用和工具等內容。
該書作者均為相關領域具有權威性的專家與學者。圖書內容既包括現代遙感技術的基礎知識，又涉及衛星遙感的前沿領域，有廣泛的實用性，可作為遙感、地學、環境、空間信息等地球科學領域的專業參考書。
該書作者均為相關領域具有權威性的專家與學者。圖書內容既包括現代遙感技術的基礎知識，又涉及衛星遙感的前沿領域，有廣泛的實用性，可作為遙感、地學、環境、空間信息等地球科學領域的專業參考書。
作者簡介
Prof. John J. Qu is a faculty member of the ESGS department at the school of Computational Sciences and is Technical Director of EastFIRE Lab at George Mason University. He is also with NASA Goddard Space Flight Center to support the NPOESS Preparatory Project (NPP) mission. His major research areas are satellite remote sensing, Earth systems science, fire science and GIS applications.
圖書目錄
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
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
