Practical Handbook of Remote Sensing, 2nd Edition

Practical Handbook of Remote Sensing, 2nd Edition

by Samantha Lavender, Andrew Lavender
Released April 2023
Publisher(s): CRC Press
ISBN: 9781000862225

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Book description

The second edition of Practical Handbook of Remote Sensing is updated with new explanations and practical examples using the Copernicus satellite data and new versions of the open-source software, along with a new chapter and new applications. Thoroughly revised, the handbook continues to be a practical “how-to” remote sensing guide.

Table of contents

  1. Cover
  2. Half Title
  3. Title Page
  4. Copyright Page
  5. Table of Contents
  6. List of Figures
  7. List of Tables
  8. Preface
  9. Acknowledgments
  10. Authors
  11. List of Symbols
  12. List of Acronyms and Abbreviations
  13. 1. What Is Remote Sensing?
    1. 1.1 Definition of Remote Sensing
    2. 1.2 History of Remote Sensing
    3. 1.3 Principles of Remote Sensing
    4. 1.4 Usefulness of Remote Sensing
    5. 1.5 Challenges of Remote Sensing
    6. 1.6 Summary and Scope of the Book
    7. 1.7 Key Terms
    8. References
  14. 2. How Does Remote Sensing Work?
    1. 2.1 Principles of Satellite Remote Sensing
    2. 2.2 What Does the Sensor Measure in Remote Sensing?
    3. 2.3 Electromagnetic Spectrum
    4. 2.4 How Do Sensors Take Measurements?
    5. 2.5 Spatial, Spectral, and Temporal Resolutions
      1. 2.5.1 Spatial Resolution of Data
      2. 2.5.2 Spectral Resolution of Data
      3. 2.5.3 Temporal Resolution of Data
      4. 2.5.4 Resolution Compromises
    6. 2.6 Summary
    7. 2.7 Key Terms
    8. References
  15. 3. Data Available from Remote Sensing
    1. 3.1 Optical Data
      1. 3.1.1 Passive: Visible and Infrared
      2. 3.1.2 Active: Lidar
    2. 3.2 Microwave Data
      1. 3.2.1 Passive: Radiometer
      2. 3.2.2 Active: Scatterometer
      3. 3.2.3 Active: Altimeter
      4. 3.2.4 Active: Synthetic Aperture Radar
    3. 3.3 Radio Data
    4. 3.4 Distinction between Freely Available Data and Commercial Data
    5. 3.5 Where to Find Data?
    6. 3.6 Picking the Right Type of Data for a Particular Application
    7. 3.7 Summary
    8. 3.8 Key Terms
  16. 4. Basic Remote Sensing Using Landsat Data
    1. 4.1 Notation Used for Practical Exercises within the Book
    2. 4.2 History of Landsat
    3. 4.3 Summary of the Landsat Missions
    4. 4.4 Different Levels of Data Available
    5. 4.5 Accessing the Level 1 Landsat Data
    6. 4.6 Selecting the Level 1 Landsat Data to Download
    7. 4.7 Scene ID
    8. 4.8 Worldwide Reference System
    9. 4.9 Downloading the Level 1 Landsat Data
    10. 4.10 Basic Viewing and Using the Landsat Data
    11. 4.11 Landsat Known Issues
      1. 4.11.1 Scan Line Corrector within Landsat-7 ETM+
      2. 4.11.2 Bright Pixels
    12. 4.12 Practical Exercise: Finding, Downloading, and Viewing Landsat Data
    13. 4.13 Summary
    14. 4.14 Online Resources
    15. 4.15 Key Terms
    16. References
  17. 5. Introduction to Image Processing
    1. 5.1 What Is an Image and How Is It Acquired?
    2. 5.2 Image Properties
    3. 5.3 Why Are Remotely Sensed Images Often Large in Size?
    4. 5.4 Image Processing Technique: Contrast Manipulation/Histogram Stretching
    5. 5.5 Image Processing Technique: Filtering Pixels
    6. 5.6 Image Processing Technique: Applying Algorithms and Color Palettes
    7. 5.7 Summary
    8. 5.8 Key Terms
  18. 6. Practical Image Processing
    1. 6.1 Image Processing Software
    2. 6.2 Installing the SNAP
    3. 6.3 Introduction to the SNAP
    4. 6.4 The Geometry of Landsat Level-1 Data
    5. 6.5 Landsat Level-1 GeoTIFF Files
    6. 6.6 Downloading the Level-1 Product Bundle
    7. 6.7 Importing Landsat Level-1 Data into SNAP
    8. 6.8 Practical Image Processing: Creating Simple Color Composites
    9. 6.9 Practical Image Processing: Creating a Subset
    10. 6.10 Practical Image Processing: Contrast Enhancement through Histogram Stretching
    11. 6.11 Practical Image Processing: Color Palettes
    12. 6.12 Practical Image Processing: Applying a Filter
    13. 6.13 Practical Image Processing: Applying the NDVI Algorithm
    14. 6.14 History of the Copernicus Program
      1. 6.14.1 Summary of Sentinel Missions
        1. 6.14.1.1 Sentinel-1A and 1B
        2. 6.14.1.2 Sentinel-2A and 2B
        3. 6.14.1.3 Sentinel-3A and 3B
        4. 6.14.1.4 Sentinel-5P
        5. 6.14.1.5 Sentinel-6
    15. 6.15 Practical Exercise: Finding, Downloading, Processing, and Visualizing Sentinel-2 Data
      1. 6.15.1 Downloading the Sentinel-2 Data
      2. 6.15.2 Importing Sentinel-2 Level-1 Data into SNAP
      3. 6.15.3 Practical Image Processing: Creating Simple Color Composites
      4. 6.15.4 Practical Image Processing: Applying the NDVI Algorithm
    16. 6.16 Summary
    17. 6.17 Online Resources
    18. 6.18 Key Terms
  19. 7. Geographic Information System and an Introduction to QGIS
    1. 7.1 Introduction to GIS
    2. 7.2 GIS Software Packages
    3. 7.3 Installing QGIS
    4. 7.4 Introduction to QGIS
    5. 7.5 Importing Remote Sensing Data into QGIS
    6. 7.6 GIS Data Handling Technique: Contrast Enhancement/Histogram Stretch
    7. 7.7 GIS Data Handling Technique: Combining Images
      1. 7.7.1 GIS Data Handling Technique: Combining Data from Different Satellites
    8. 7.8 GIS Data Handling Techniques: Adding Cartographic Layers
    9. 7.9 Coordinate Reference System Adjustments within QGIS
    10. 7.10 Saving Images and Projects in QGIS
    11. 7.11 Summary
    12. 7.12 Online Resources
    13. 7.13 Key Terms
    14. References
  20. 8. Urban Environments and Their Signatures
    1. 8.1 Introduction to Application Chapters of the Book
    2. 8.2 Urban Environments
    3. 8.3 Introduction to the Optical Signatures of Urban Surfaces
    4. 8.4 Introduction to the Thermal Signatures of Urban Surfaces
    5. 8.5 Urban Applications
      1. 8.5.1 Green Spaces and Urban Creep
      2. 8.5.2 Temperature Dynamics
      3. 8.5.3 Nighttime Imagery
      4. 8.5.4 Subsidence
    6. 8.6 Practical Exercise: Spectral and Thermal Signatures
      1. 8.6.1 Step One: Downloading, Importing, and Processing Landsat Optical Data to Determine Green Spaces
      2. 8.6.2 Step Two: Downloading and Importing MODIS Data to QGIS
      3. 8.6.3 Step Three: Combining MODIS Thermal Data with Optical Data from Landsat
      4. 8.6.4 Step Four: Comparing Thermal Data from Landsat and MODIS
      5. 8.6.5 Step Five: Example of ASTER Data
    7. 8.7 Summary
    8. 8.8 Online Resources
    9. 8.9 Key Terms
    10. References
  21. 9. Landscape Evolution
    1. 9.1 Principles of Using Time-Series Analysis for Monitoring Landscape Evolution
    2. 9.2 Landscape Evolution Techniques
    3. 9.3 Optical Vegetation Indices for Landscape Evolution
    4. 9.4 Microwave Data for Landscape Evolution
    5. 9.5 Landscape Evolution Applications
      1. 9.5.1 Mapping Land Cover
      2. 9.5.2 Agriculture
      3. 9.5.3 Forestry and Carbon Storage
      4. 9.5.4 Fire Detection
    6. 9.6 Practical Exercise: Supervised Land Cover Classification
      1. 9.6.1 First Stage: Creating the Data Set Ready for Land Classification
        1. 9.6.1.1 Step One: Installing Semi-Automatic Classification Plugin into QGIS
        2. 9.6.1.2 Step Two: Importing and Preprocessing the Data
        3. 9.6.1.3 Step Three: Creating a False-Color Composite
        4. 9.6.1.4 Step Four: Choosing Classification Wavebands
      2. 9.6.2 Second Stage: Performing a Supervised Land Classification Using Existing Training Sites
        1. 9.6.2.1 Step Five: Importing Spectral Signatures
        2. 9.6.2.2 Step Six: Classification Algorithm and Preview
        3. 9.6.2.3 Step Seven: Whole Scene Classification
      3. 9.6.3 Third Stage: Performing a Supervised Land Classification with Your Own Training Sites
        1. 9.6.3.1 Step Eight: Creating a Pseudo-True-Color Composite
        2. 9.6.3.2 Step Nine: Identifying and Selecting Your Own Training Sites
        3. 9.6.3.3 Step Eleven: Classification Algorithm and Preview
        4. 9.6.3.4 Step Ten: Whole Scene Classification
    7. 9.7 Summary
    8. 9.8 Online Resources
    9. 9.9 Key Terms
    10. References
  22. 10. Inland Waters and the Water Cycle
    1. 10.1 Optical and Thermal Data for Inland Waters
    2. 10.2 Microwave Data for Monitoring the Water Cycle
      1. 10.2.1 Altimetry
      2. 10.2.2 Passive Radiometry
    3. 10.3 Inland Water Applications
      1. 10.3.1 Water Cycle and Wetlands
      2. 10.3.2 Soil Moisture Monitoring
      3. 10.3.3 Lakes, Rivers, and Reservoirs
      4. 10.3.4 Flood Mapping
      5. 10.3.5 Groundwater Measurement
    4. 10.4 Practical Exercise: Analysis of the Aswan Dam
      1. 10.4.1 Step One: Obtaining the TerraSAR-X SAR Data
      2. 10.4.2 Step Two: Loading the SAR Data into QGIS
      3. 10.4.3 Step Three: Downloading the Landsat Data from EarthExplorer
      4. 10.4.4 Step Four: Importing Landsat Data into QGIS
      5. 10.4.5 Step Five: Creating an NDWI Using a Mathematical Function
      6. 10.4.6 Step Six: Creating a Pseudo-True-Color Composite
      7. 10.4.7 Step Seven: Downloading the SRTM DEM Data
      8. 10.4.8 Step Eight: Loading the SRTM DEM Data into QGIS
      9. 10.4.9 Step Nine: Merging the Four SRTM DEM Tiles into a Single Layer
      10. 10.4.10 Step Ten: Adding Contour Lines
    5. 10.5 Summary
    6. 10.6 Online Resources
    7. 10.7 Key Terms
    8. References
  23. 11. Coastal Waters and Coastline Evolution
    1. 11.1 Optical Data
      1. 11.1.1 The Color of the Water
      2. 11.1.2 Bathymetric Data
    2. 11.2 Passive Microwave Signatures from the Ocean
    3. 11.3 Coastal Applications
      1. 11.3.1 Physical Oceanography that Includes Temperature, Salinity, and Sea Ice
      2. 11.3.2 Water Quality, Including Algal Blooms
      3. 11.3.3 Mangroves and Coastal Protection
      4. 11.3.4 Coastal Evolution, Including Sediment Transport
    4. 11.4 Practical Exercise – New York Bight
      1. 11.4.1 Stage One: Importing and Processing MODIS L2 Data
        1. 11.4.1.1 Step One: Downloading MODIS L2 Data
        2. 11.4.1.2 Step Two: Importing the MODIS SST Data into SNAP
        3. 11.4.1.3 Step Three: Processing the MODIS-Aqua SST Data
        4. 11.4.1.4 Step Four: Importing and Processing the MODIS OC Data in SNAP
        5. 11.4.1.5 Step Five: Download and Import the OLCI L2 Product
        6. 11.4.1.6 Step Six: Save the Products
      2. 11.4.2 Stage Two: Comparison of MODIS L2, OLCI L2, and Landsat Data
        1. 11.4.2.1 Step Seven: Restarting SNAP and Importing Landsat Data
        2. 11.4.2.2 Step Eight: Importing the Previous OC Product
        3. 11.4.2.3 Step Nine: Reprojection of the OC Image
      3. 11.4.3 Stage Three: OLCI L3 Data
        1. 11.4.3.1 Step Ten: Downloading OLCI L3 Data
    5. 11.5 Summary
    6. 11.6 Online Resources
    7. 11.7 Key Terms
    8. References
  24. 12. Atmospheric Gases and Pollutants
    1. 12.1 An Understanding of the Atmosphere
    2. 12.2 Detecting What Is in the Atmosphere
    3. 12.3 Air Quality
      1. 12.3.1 Real-Time and Forecasted Alerts
      2. 12.3.2 The Impact of COVID-19
    4. 12.4 Greenhouse Gas Emissions
      1. 12.4.1 Observing Methane
    5. 12.5 Practical – An Assessment of Air Quality and Temperature
      1. 12.5.1 Stage One: Adding Cartographic Layers
      2. 12.5.2 Stage Two: Adding CORINE Land Cover Data
      3. 12.5.3 Stage Three: Downloading the CAMS Data set
      4. 12.5.4 Stage Four: Visualizing the CAMS Time Series
    6. 12.6 Summary
    7. 12.7 Online Resources
    8. 12.8 Key Terms
    9. References
  25. 13. Where to Next?
    1. 13.1 Developments in Satellite Hardware
      1. 13.1.1 Instruments
      2. 13.1.2 Satellite Developments
        1. 13.1.2.1 Smaller and Smaller Satellites
        2. 13.1.2.2 Constellations
        3. 13.1.2.3 China
        4. 13.1.2.4 Democratization of Space
        5. 13.1.2.5 High-Altitude Pseudo-Satellite/High-Altitude Platform Station
        6. 13.1.2.6 Uncrewed Aerial Vehicles
        7. 13.1.2.7 Sustainability: Space Debris and Carbon Footprint
    2. 13.2 Developments in Data Processing
      1. 13.2.1 Accessing Online Data Sets
      2. 13.2.2 Onboard Satellite Data Processing
      3. 13.2.3 Integration
      4. 13.2.4 Machine Learning and Artificial Intelligence
      5. 13.2.5 Open Source and Open Science
      6. 13.2.6 Data Standards
    3. 13.3 Developments in Applications
      1. 13.3.1 Citizen Science
      2. 13.3.2 Climate Quality Data Sets
      3. 13.3.3 Repurposing
    4. 13.4 Developing Your Knowledge Further
      1. 13.4.1 Examples of Further Reading
    5. 13.5 Summary
    6. 13.6 Online Resources
    7. References
  26. Index

Product information

  • Title: Practical Handbook of Remote Sensing, 2nd Edition
  • Author(s): Samantha Lavender, Andrew Lavender
  • Release date: April 2023
  • Publisher(s): CRC Press
  • ISBN: 9781000862225