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