Torus 2 - Toward an Open Resource Using Services

Cloud Computing for Environmental Data
Herausgeber: Laffly, Dominique

• Gebundenes Buch

Produktbeschreibung

This book, presented in three volumes, examines �environmental� disciplines in relation to major players in contemporary science: Big Data, artificial intelligence and cloud computing. Today, there is a real sense of urgency regarding the evolution of computer technology, the ever-increasing volume of data, threats to our climate and the sustainable development of our planet. As such, we need to reduce technology just as much as we need to bridge the global socio-economic gap between the North and South; between universal free access to data (open data) and free software (open source). In this book, we pay particular attention to certain environmental subjects, in order to enrich our understanding of cloud computing. These subjects are: erosion; urban air pollution and atmospheric pollution in Southeast Asia; melting permafrost (causing the accelerated release of soil organic carbon in the atmosphere); alert systems of environmental hazards (such as forest fires, prospective modeling of socio-spatial practices and land use); and web fountains of geographical data. Finally, this book asks the question: in order to find a pattern in the data, how do we move from a traditional computing model-based world to pure mathematical research? After thorough examination of this topic, we conclude that this goal is both transdisciplinary and achievable.

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Produktdetails

• Verlag: Wiley
• Seitenzahl: 320
• Erscheinungstermin: 3. Juni 2020
• Englisch
• Abmessung: 239mm x 157mm x 23mm
• Gewicht: 617g
• ISBN-13: 9781786306005
• ISBN-10: 178630600X
• Artikelnr.: 58772873

Autorenporträt

Dominique Lafly is a Professor at the University of Toulouse, France. As a geographer, he is interested in the landscape, and the links between societies and their environment. Concerned with the issue of Big Data, he promotes multidisciplinary programs to bring IT closer to environmental applied disciplines.

Inhaltsangabe

Preface xi
Part 1. Earth Science Remote Sensing xvii
Introduction to Part 1 xix
Dominique LAFFLY
Chapter 1. A Brief History of Remote Sensing 1
Dominique LAFFLY
1.1. History 1
1.2. Fields of application 8
1.3. Orbits, launchers and platforms 10
1.4. The acquired data are digital images 12
1.5. So what is remote sensing? Some definitions 14
1.6. Notes 19
1.7. References 21
Chapter 2. Physics of RS 23
Luca TOMASSETTI
2.1. Introduction 23
2.2. Remote sensing 23
2.3. Fundamental properties of electromagnetic waves 29
2.3.1. Wave equation and solution 29
2.3.2. Quantum properties of electromagnetic radiation 30
2.3.3. Polarization, coherence, group and phase velocity, the Doppler
effect 31
2.4. Radiation quantities 31
2.4.1. Spectral quantities 33
2.4.2. Luminous quantities 34
2.5. Generation of electromagnetic waves 34
2.6. Detection of electromagnetic waves 37
2.7. Interaction of electromagnetic waves with matter 38
2.7.1. Overview 38
2.7.2. Interaction mechanisms 39
2.8. Solid surfaces sensing in the visible and near infrared 41
2.8.1. Wave-surface interaction mechanisms 43
2.9. Radiometric and geometric resolutions 45
2.10. References 46
Chapter 3. Image Quality 47
Dominique LAFFLY
3.1. Introduction 47
3.2. Image quality - geometry 54
3.2.1. Whiskbroom concept 57
3.2.2. Pushbroom concept 60
3.2.3. Full frame concept 62
3.2.4. Optical geometric distortions 64
3.2.5. Relief distortions 66
3.2.6. Inverse location model 67
3.2.7. Direct location model 69
3.2.8. Root Mean Square (RMS) validation 72
3.2.9. Resampling methods 73
3.2.10. Image geometric quality to assume geographical space continuity 75
3.3. Image quality - radiometry 76
3.3.1. Radiometric model of the instrument 78
3.3.2. Radiometric equalization and calibration 79
3.3.3. Radiometric signal noise reduction (SNR) 81
3.3.4. Radiometric physical value 82
3.3.5. Image quality - resolution 84
3.4. Conclusion 91
3.5. Notes 91
3.6. References 91
Chapter 4. Remote Sensing Products 95
Van Ha PHAM, Viet Hung LUU, Anh PHAN, Dominique LAFFLY, Quang Hung BUI and
Thi Nhat Thanh NGUYEN
4.1. Atmospheric observation 95
4.1.1. Introduction to common atmospheric gases and particles 95
4.1.2. Introduction to meteorological parameters 103
4.1.3. Atmospheric observation from satellite 107
4.2. Land observation 128
4.2.1. Introduction 128
4.2.2. Land cover/land use classification system 129
4.2.3. Legend 134
4.2.4. Data 134
4.2.5. Methodology 137
4.2.6. Global land cover datasets 154
4.3. Conclusion 158
4.4. References 158
Chapter 5. Image Processing in Spark 163
Yannick LE NIR, Florent DEVIN, Thomas BALDAQUIN, Pierre MESLER LAZENNEC, Ji
Young JUNG, Se-Eun KIM, Hyeyoung KWOON, Lennart NILSEN, Yoo Kyung LEE and
Dominique LAFFLY
5.1. Introduction 163
5.2. Prediction map generation 164
5.2.1. Spark 164
5.2.2. Implementation 165
5.2.3. Naive method 167
5.2.4. Advanced method 168
5.3. Conclusion 171
Chapter 6. Satellite Image Processing using Spark on the HUPI Platform 173
Vincent MORENO and Minh Tu NGUYEN
6.1. Introduction 173
6.2. Presentation of GeoTrellis 174
6.3. Using GeoTrellis in Hupi-Notebook 174
6.3.1. Some core concepts of GeoTrellis 177
6.3.2. Computation of NDVI 177
6.3.3. Compare two NDVI 178
6.3.4. Descriptive statistics of NDVI per Tile 178
6.3.5. K-means 179
6.4. Workflows in HDFS: automatize image processing 181
6.4.1. Create a jar 181
6.4.2. Monitor the Spark jobs 182
6.4.3. Tune performance of the Spark job 183
6.4.4. Create a workflow in Hupi-Studio 184
6.5. Visualizations in Hupi-Front 186
6.6. Cloud service 188
6.7. Development 189
Chapter 7. Remote Sensing Case Studies 191
Van Ha PHAM, Thi Nhat Thanh NGUYEN and Dominique LAFFLY
7.1. Satellite AOD validation using R 191
7.1.1. Introduction 191
7.1.2. Datasets 192
7.1.3. Validation methodology 195
7.1.4. Experiments and results 198
7.1.5. Conclusion 204
7.2. Georeferencing satellite images 204
7.2.1. Introduction 204
7.2.2. Georeferencing methods 205
7.2.3. Datasets and methodology 207
7.2.4. Results and discussion 210
7.3. Conclusion 216
7.4. Appendix: R source code of validation process 217
7.5. References 222
Conclusion to Part 1 225
Dominique LAFFLY
Part 2. GIS Application and Geospatial Data Infrastructure 227
Chapter 8. Overview of GIS Application 229
Quang Huy MAN
8.1. Introduction 229
8.2. Enterprise GIS for environmental management 230
8.3. GIS and decision-making in planning and management 232
8.3.1. Data quality and control 233
8.3.2. Decision support systems (DSS) 233
8.3.3. Integrating GIS with the DSS 234
8.4. GIS for water-quality management 235
8.5. GIS for land-use planning 236
8.6. Application of the technology in LUP and management 240
8.6.1. Computers and software programs applied to LUP and management 241
8.6.2. Application of GIS analysis and MCE in land-use planning and
management 242
8.7. References 243
Chapter 9. Spatial Data Infrastructure 247
Quang Hung BUI, Quang Thang LUU, Duc Van HA, Tuan Dung PHAM, Sanya PRASEUTH
and Dominique LAFFLY
9.1. Introduction 247
9.2. Spatial data infrastructure 247
9.3. Components of spatial data infrastructure 249
9.4. Open standards for spatial data infrastructure 251
9.4.1. Open geospatial consortium (OGC) 251
9.4.2. OGC's open standards 252
9.4.3. Usage of OGC's open standards in SDI 255
9.5. Server architecture models for the National Spatial Data
Infrastructure and Geospatial One-Stop (GOS) portal 256
9.5.1. GOS portal architecture 256
9.5.2. Standards for GOS portal architecture 257
9.5.3. Taxonomy of geospatial server architecture 257
9.5.4. Three reference architectures for server architecture model 258
9.6. References 260
List of Authors 263
Index 265
Summaries of other volumes 267