Practical Handbook of Remote Sensing

Cover
Half Title
Title Page
Copyright Page
Table of Contents
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 Does the Sensor Measure in Remote Sensing?
2.3 Electromagnetic Spectrum
2.4 How do Sensors Take Measurements?
2.5 Spatial, Spectral, and Temporal Resolutions
2.5.1 Spatial Resolution of Data
2.5.2 Spectral Resolution of Data
2.5.3 Temporal Resolution of Data
2.5.4 Resolution Compromises
2.6 Summary
2.7 Key Terms
References
3. Data Available From Remote Sensing
3.1 Optical Data
3.1.1 Passive: Visible and Infrared
3.1.2 Active: Lidar
3.2 Microwave Data
3.2.1 Passive: Radiometer
3.2.2 Active: Scatterometer
3.2.3 Active: Altimeter
3.2.4 Active: Synthetic Aperture Radar
3.3 Radio Data
3.4 Distinction Between Freely Available Data and Commercial Data
3.5 Where to Find Data?
3.6 Picking the Right Type of Data for a Particular Application
3.7 Summary
3.8 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 Scene ID
4.8 Worldwide Reference System
4.9 Downloading the Level 1 Landsat Data
4.10 Basic Viewing and Using the Landsat Data
4.11 Landsat Known Issues
4.11.1 Scan Line Corrector within Landsat-7 ETM+
4.11.2 Bright Pixels
4.12 Practical Exercise: Finding, Downloading, and Viewing Landsat Data
4.13 Summary
4.14 Online Resources
4.15 Key Terms
References
5. Introduction to Image Processing
5.1 What is an Image and How is it 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 Product Bundle
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 History of the Copernicus Program
6.14.1 Summary of Sentinel Missions
6.14.1.1 Sentinel-1A and 1B
6.14.1.2 Sentinel-2A and 2B
6.14.1.3 Sentinel-3A and 3B
6.14.1.4 Sentinel-5P
6.14.1.5 Sentinel-6
6.15 Practical Exercise: Finding, Downloading, Processing, and Visualizing Sentinel-2 Data
6.15.1 Downloading the Sentinel-2 Data
6.15.2 Importing Sentinel-2 Level-1 Data into SNAP
6.15.3 Practical Image Processing: Creating Simple Color Composites
6.15.4 Practical Image Processing: Applying the NDVI Algorithm
6.16 Summary
6.17 Online Resources
6.18 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
7.7.1 GIS Data Handling Technique: Combining Data From Different Satellites
7.8 GIS Data Handling Techniques: Adding Cartographic Layers
7.9 Coordinate Reference System 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
8.5.1 Green Spaces and Urban Creep
8.5.2 Temperature Dynamics
8.5.3 Nighttime Imagery
8.5.4 Subsidence
8.6 Practical Exercise: Spectral and Thermal Signatures
8.6.1 Step One: Downloading, Importing, and Processing Landsat Optical Data to Determine Green Spaces
8.6.2 Step Two: Downloading and Importing MODIS Data to QGIS
8.6.3 Step Three: Combining MODIS Thermal Data with Optical Data From Landsat
8.6.4 Step Four: Comparing Thermal Data From Landsat and MODIS
8.6.5 Step Five: Example of ASTER Data
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
9.5.1 Mapping Land Cover
9.5.2 Agriculture
9.5.3 Forestry and Carbon Storage
9.5.4 Fire Detection
9.6 Practical Exercise: Supervised Land Cover Classification
9.6.1 First Stage: Creating the Data Set Ready for Land Classification
9.6.1.1 Step One: Installing Semi-Automatic Classification Plugin Into QGIS
9.6.1.2 Step Two: Importing and Preprocessing the Data
9.6.1.3 Step Three: Creating a False-Color Composite
9.6.1.4 Step Four: Choosing Classification Wavebands
9.6.2 Second Stage: Performing a Supervised Land Classification Using Existing Training Sites
9.6.2.1 Step Five: Importing Spectral Signatures
9.6.2.2 Step Six: Classification Algorithm and Preview
9.6.2.3 Step Seven: Whole Scene Classification
9.6.3 Third Stage: Performing a Supervised Land Classification with Your Own Training Sites
9.6.3.1 Step Eight: Creating a Pseudo-True-Color Composite
9.6.3.2 Step Nine: Identifying and Selecting Your Own Training Sites
9.6.3.3 Step Eleven: Classification Algorithm and Preview
9.6.3.4 Step Ten: Whole Scene 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
10.2.1 Altimetry
10.2.2 Passive Radiometry
10.3 Inland Water Applications
10.3.1 Water Cycle and Wetlands
10.3.2 Soil Moisture Monitoring
10.3.3 Lakes, Rivers, and Reservoirs
10.3.4 Flood Mapping
10.3.5 Groundwater Measurement
10.4 Practical Exercise: Analysis of the Aswan Dam
10.4.1 Step One: Obtaining the TerraSAR-X SAR Data
10.4.2 Step Two: Loading the SAR Data Into QGIS
10.4.3 Step Three: Downloading the Landsat Data From EarthExplorer
10.4.4 Step Four: Importing Landsat Data Into QGIS
10.4.5 Step Five: Creating an NDWI Using a Mathematical Function
10.4.6 Step Six: Creating a Pseudo-True-Color Composite
10.4.7 Step Seven: Downloading the SRTM DEM Data
10.4.8 Step Eight: Loading the SRTM DEM Data Into QGIS
10.4.9 Step Nine: Merging the Four SRTM DEM Tiles Into a Single Layer
10.4.10 Step Ten: Adding Contour Lines
10.5 Summary
10.6 Online Resources
10.7 Key Terms
References
11. Coastal Waters and Coastline Evolution
11.1 Optical Data
11.1.1 The Color of the Water
11.1.2 Bathymetric Data
11.2 Passive Microwave Signatures From the Ocean
11.3 Coastal Applications
11.3.1 Physical Oceanography that Includes Temperature, Salinity, and Sea Ice
11.3.2 Water Quality, Including Algal Blooms
11.3.3 Mangroves and Coastal Protection
11.3.4 Coastal Evolution, Including Sediment Transport
11.4 Practical Exercise – New York Bight
11.4.1 Stage One: Importing and Processing MODIS L2 Data
11.4.1.1 Step One: Downloading MODIS L2 Data
11.4.1.2 Step Two: Importing the MODIS SST Data Into SNAP
11.4.1.3 Step Three: Processing the MODIS-Aqua SST Data
11.4.1.4 Step Four: Importing and Processing the MODIS OC Data in SNAP
11.4.1.5 Step Five: Download and Import the OLCI L2 Product
11.4.1.6 Step Six: Save the Products
11.4.2 Stage Two: Comparison of MODIS L2, OLCI L2, and Landsat Data
11.4.2.1 Step Seven: Restarting SNAP and Importing Landsat Data
11.4.2.2 Step Eight: Importing the Previous OC Product
11.4.2.3 Step Nine: Reprojection of the OC Image
11.4.3 Stage Three: OLCI L3 Data
11.4.3.1 Step Ten: Downloading OLCI L3 Data
11.5 Summary
11.6 Online Resources
11.7 Key Terms
References
12. Atmospheric Gases and Pollutants
12.1 An Understanding of the Atmosphere
12.2 Detecting What is in the Atmosphere
12.3 Air Quality
12.3.1 Real-Time and Forecasted Alerts
12.3.2 The Impact of COVID-19
12.4 Greenhouse Gas Emissions
12.4.1 Observing Methane
12.5 Practical – An Assessment of Air Quality and Temperature
12.5.1 Stage One: Adding Cartographic Layers
12.5.2 Stage Two: Adding CORINE Land Cover Data
12.5.3 Stage Three: Downloading the CAMS Data Set
12.5.4 Stage Four: Visualizing the CAMS Time Series
12.6 Summary
12.7 Online Resources
12.8 Key Terms
References
13. Where to Next?
13.1 Developments in Satellite Hardware
13.1.1 Instruments
13.1.2 Satellite Developments
13.1.2.1 Smaller and Smaller Satellites
13.1.2.2 Constellations
13.1.2.3 China
13.1.2.4 Democratization of Space
13.1.2.5 High-Altitude Pseudo-Satellite/High-Altitude Platform Station
13.1.2.6 Uncrewed Aerial Vehicles
13.1.2.7 Sustainability: Space Debris and Carbon Footprint
13.2 Developments in Data Processing
13.2.1 Accessing Online Data Sets
13.2.2 Onboard Satellite Data Processing
13.2.3 Integration
13.2.4 Machine Learning and Artificial Intelligence
13.2.5 Open Source and Open Science
13.2.6 Data Standards
13.3 Developments in Applications
13.3.1 Citizen Science
13.3.2 Climate Quality Data Sets
13.3.3 Repurposing
13.4 Developing Your Knowledge Further
13.4.1 Examples of Further Reading
13.5 Summary
13.6 Online Resources
References
Index