Exploring the Earth with QGIS: A Guide to Using Satellite Imagery at Its Full Potential (Springer Remote Sensing/Photogrammetry)

Preface
Contents
List of Figures
List of Tables
Chapter 1: Introduction to QGIS
	1.1 Download and Install QGIS
	1.2 The Differences Between QGIS and Other GIS Software
	1.3 QGIS Appearance
Chapter 2: QGIS Plugins for Remote Sensing
	2.1 QGIS Plugin for Remote Sensing Analysis
	2.2 Advantages and Disadvantages of Plugins
Chapter 3: Data Acquiring
	3.1 ALOS
	3.2 Landsat
	3.3 Sentinel
	3.4 MODIS
	3.5 ASTER
	3.6 Planet
	3.7 Tellus Traveler
	3.8 Copernicus Data Space Ecosystem
Chapter 4: Data Preprocessing
	4.1 Download the Raster DEM Data
	4.2 Check Data Quality
	4.3 Resample the Raster Data
	4.4 Clip the Raster Data
	4.5 Perform Data Cleaning
	4.6 Apply Color and Styling
Chapter 5: Data Management
	5.1 Importing Data
	5.2 Classification
	5.3 Analysis
		5.3.1 Satellite Image Analysis
		5.3.2 DEM Analysis
	5.4 Visualization
		5.4.1 Layout Manager
Chapter 6: Data Visualization
	6.1 Adding Data
	6.2 Styling
	6.3 Creating 3D Maps
Chapter 7: Data Analysis
	7.1 Elevation Profile Extraction
	7.2 Point Sampling Analysis
	7.3 Viewshed Analysis
	7.4 Watershed Analysis
		7.4.1 Stream Delineation Using DEM
		7.4.2 Watershed Delineation Using DEM
	7.5 Statistical Analysis
		7.5.1 Zonal Statistics
		7.5.2 Exploratory Analysis
		7.5.3 Explanatory Analysis
		7.5.4 Create or Modify the R Script
	7.6 Land Use Land Cover Analysis
		7.6.1 Clustering
			7.6.1.1 Download and Open Pleiades Imagery
			7.6.1.2 Create Box and Clip the Image
			7.6.1.3 Clustering Using K-Means
			7.6.1.4 Classification Report
		7.6.2 Pixel-Based
			7.6.2.1 Creating Training Data
			7.6.2.2 Install Dzetsaka Plugin
			7.6.2.3 Select Classifier and Perform Classification
			7.6.2.4 Advantages and Disadvantages of Pixel-Based
		7.6.3 Object-Based
			7.6.3.1 Download and Install Orfeo Toolbox
			7.6.3.2 Creating Training Polygon
			7.6.3.3 Object-Based Image Analysis (OBIA)
Chapter 8: Integration of Remote Sensing Data with Other Spatial Datasets
	8.1 Download and Import the Remote Sensing and Other Spatial Datasets into QGIS
	8.2 Integrating with LiDAR
Chapter 9: Integration of QGIS with Google Earth Engine (GEE)
	9.1 Advantages and Disadvantages
	9.2 Install and Authentication Process
	9.3 Visualizing Satellite Images
		9.3.1 Sentinel-2
		9.3.2 Landsat-8
		9.3.3 Precipitation
		9.3.4 Night-Time
		9.3.5 Copernicus Land Cover
		9.3.6 ALOS DEM Elevation
		9.3.7 Sentinel-1 (SAR Seasonality)
		9.3.8 Sentinel-5 (NO2)
		9.3.9 Land Surface Temperature
		9.3.10 Sea Surface Temperature
	9.4 Map Algebra (Expression)
		9.4.1 SAVI and NDVI
		9.4.2 Normalized Burn Ratio
Chapter 10: Case Studies and Examples of Earth Remote Sensing Applications Using QGIS
	10.1 Vegetation Cover Change in New Delhi
		10.1.1 Working with Model Designer
	10.2 Land Use Land Cover Classification Using Machine Learning Algorithm
		10.2.1 Unsupervised Classification
		10.2.2 Supervised Classification
		10.2.3 Refining Classification Result
		10.2.4 Accuracy Assessment
	10.3 Floods Mapping Using SAR
Glossary and Abbreviations
Bibliography
Index