Practical Handbook of Remote Sensing

Description

A Beginner’s Guide to the World of Satellite Data Over a thousand active satellites are in orbit around the Earth with applications including navigation, the transmission of data and satellite remote sensing; a space-based technology providing data accessible to everyone. The Practical Handbook of Remote Sensing offers a complete understanding of the basic scientific principles needed to perform practical remote sensing at home or at work, using a personal computer. This book contains the information needed to effectively find, download, analyze, and view environmental data. Written by an expert with more than 15 years of experience along with the perspective of a non-expert navigating his way through remote sensing for the first time, it serves as a guidebook for anyone wanting to use remote sensing technology without becoming an expert on the subject. No Previous Knowledge Required The book explains the science behind remote sensing; describing what it is, how it works, and how it can be used in real life applications. Using just a standard personal computer, the authors help readers discover a wide variety of satellite imagery and how these images can be used to monitor environmental changes in real-world application areas: urban environments, natural landscape, terrestrial water cycle, and coastal environments. The book primarily concentrates on practically using optical data from the Landsat missions with further examples based on MODIS, TerraSAR-X and pre-processed datasets such as those provided by the Copernicus Services. It also provides a review of near-future developments in satellites, sensors, and the processing of data, along with a review of near-future applications and longer-term developments. In addition, this book: Includes a complementary website providing additional support, satellite images, videos, updates on satellite data and a FAQ/forum to answer readers’ questions Gives readers detailed hands-on practical exercises on how to find, download, process and visualize freely available satellite remote sensing data, coupled with result-comparisons Demonstrates how satellite data can be used to provide a range of environmental monitoring for both small local areas and across the globe Content: List of figures -- List of tables -- Preface -- Acknowledgments -- Authors -- List of symbols -- List of acronyms and abbreviations -- 1. What is remote sensing? 1.1. Definition of remote sensing 1.2. History of remote sensing 1.3. Principles of remote sensing 1.4. Usefulness of remote sensing 1.5. Challenges of remote sensing 1.6. Summary and scope of the book 1.7. Key terms References -- 2. How does remote sensing work? 2.1. Principles of satellite remote sensing 2.2. What the sensor measures in remote sensing 2.3. EM spectrum 2.4. How do sensors take measurements? 2.5. Spatial, spectral, and temporal resolutions 2.6. Summary 2.7. Key terms References -- 3. Data available from remote sensing: 3.1. Optical data 3.2. Microwave data 3.3. Distinction between freely available data and commercial data 3.4. Where to find data 3.5. Picking the right type of data for a particular application 3.6. Summary 3.7. Key terms -- 4. Basic remote sensing using Landsat data: 4.1. Notation used for practical exercises within the book 4.2. History of Landsat 4.3. Summary of the Landsat missions 4.4. Different levels of data available 4.5. Accessing the level 1 Landsat data 4.6. Selecting the level 1 Landsat data to download 4.7. Worldwide reference system 4.8. Downloading the level 1 Landsat data 4.9. Basic viewing and using the Landsat data 4.10. Landsat calibration and anomalies 4.11. Practical exercise: finding, downloading, and viewing Landsat data 4.12. Summary 4.13. Online resources 4.14. Key terms References 5. Introduction to image processing: 5.1. What is an image and how are they acquired? 5.2. Image properties 5.3. Why are remotely sensed images often large in size? 5.4. Image processing technique: contrast manipulation/histogram stretching 5.5. Image processing technique: filtering pixels 5.6. Image processing technique: applying algorithms and color palettes 5.7. Summary 5.8. Key terms -- 6. Practical image processing: 6.1. Image processing software 6.2. Installing the SNAP 6.3. Introduction to the SNAP 6.4. The geometry of Landsat level 1 data 6.5. Landsat level 1 GeoTIFF files 6.6. Downloading the level 1 GeoTIFF data 6.7. Importing Landsat level 1 data into SNAP 6.8. Practical image processing: creating simple color composites 6.9. Practical image processing: creating a subset 6.10. Practical image processing: contrast enhancement through histogram stretching 6.11. Practical image processing: color palettes 6.12. Practical image processing: applying a filter 6.13. Practical image processing: applying the NDVI algorithm 6.14. Summary 6.15. Online resources 6.16. Key terms 7. Geographic information system and an introduction to QGIS: 7.1. Introduction to GIS 7.2. GIS software packages 7.3. Installing QGIS 7.4. Introduction to QGIS 7.5. Importing remote sensing data into QGIS 7.6. GIS data handling technique: contrast enhancement/histogram stretch 7.7. GIS data handling technique: combining images 7.8. GIS data handling techniques: adding cartographic layers 7.9. CRS adjustments within QGIS 7.10. Saving images and projects in QGIS 7.11. Summary 7.12. Online resources 7.13. Key terms References -- 8. Urban environments and their signatures: 8.1. Introduction to application chapters of the book 8.2. Urban environments 8.3. Introduction to the optical signatures of urban surfaces 8.4. Introduction to the thermal signatures of urban surfaces 8.5. Urban applications 8.6. Practical exercise: spectral and thermal signatures 8.7. Summary 8.8. Online resources 8.9. Key terms References -- 9. Landscape evolution: 9.1. Principles of using time-series analysis for monitoring landscape evolution 9.2. Landscape evolution techniques 9.3. Optical vegetation indices for landscape evolution 9.4. Microwave data for landscape evolution 9.5. Landscape evolution applications 9.6. Practical exercise: supervised land cover classification 9.7. Summary 9.8. Online resources 9.9. Key terms References 10. Inland waters and the water cycle: 10.1. Optical and thermal data for inland waters 10.2. Microwave data for monitoring the water cycle 10.3. Inland water applications 10.4. Practical exercise: analysis of the Aswan Dam 10.5. Summary 10.6. Online resources 10.7. Key terms References -- 11. Coastal waters and coastline evolution: 11.1. Optical data 11.2. Passive microwave signatures from the ocean 11.3. Coastal applications 11.4. Practical exercise -- New York Bight 11.5. Summary 11.6. Online resources 11.7. Key terms References -- 12. Where to next? 12.1. Developments in satellite hardware 12.2. Developments in data processing 12.3. Developments in applications 12.4. Long-term developments for remote sensing 12.5. Developing your knowledge further 12.6. Summary 12.7. Online resources References -- Figures.