GIS4Schools
latest
Contents:
1. Fundamentals of multispectral Earth observation
1.1. Remote sensing, Earth observation and GIS
1.2. Satellites for Earth observation
1.2.1. Satellite orbits and revisit time
1.2.2. Digital images and the EM spectrum
1.2.3. Spectral characteristics
1.2.4. Spatial resolution and swath width
1.3. Copernicus and the Sentinels
1.3.1. The Copernicus programme
1.3.2. Multispectral Sentinel satellites
1.4. Beyond satellite images
1.4.1. Copernicus Atmosphere Monitoring Service
1.4.2. Copernicus Marine Environment Monitoring Service
1.4.3. Copernicus Land Monitoring Service
1.4.4. Copernicus Climate Change Service
1.4.5. Copernicus Security Service
1.4.6. Copernicus Emergency Management Service
2. Principles of image analysis
2.1. The spectral signature
2.1.1. What is a spectral signature
2.1.2. Land cover vs land use
2.1.3. Spectral signatures of the main macro land cover classes
2.1.4. How to measure spectral signatures with satellites
2.1.5. How to compare spectral signatures
2.2. Spectral indices for environmental monitoring
2.2.1. What is a spectral index
2.2.2. How spectral indices are designed
2.3. Automatic land cover mapping
2.3.1. Supervised image classification
2.3.2. Classification strategies
2.4. Map validation
2.4.1. Precision or accuracy?
2.4.2. How much is accurate a map?
3. Access to Copernicus satellite images for free
3.1. Sentinel Hub EO Browser
3.1.1. How to select the correct products with Sentinel Hub EO Browser
3.1.2. How to view the satellite images with Sentinel Hub EO Browser
3.1.3. How to download the data with Sentinel Hub EO Browser
3.2. Some alternative repositories
4. Hands-on exercises
4.1. Monitoring lake’s trophic state (difficulty: advanced)
4.1.1. Download the data
4.1.2. The environmental problem
4.1.3. Scope of the exercise
4.1.4. Study area
4.1.5. Satellite images
4.1.6. The modelling
4.1.7. Chlorophyll’s concentration and water level
4.1.8. QGIS set-up
4.1.9. Prepare the satellite images
4.1.10. Load the satellite images with the correct colours
4.1.11. Resize the image
4.1.12. Calculate the Ratio Vegetation Index
4.1.13. Sample the RVI in the calibration sites
4.1.14. Calibrate the spectral model
4.1.15. Create an automatic workflow
4.1.16. Create a batch processing to manipulate all the satellite images at once
4.1.17. Estimate the chlorophyll’s concentration in Lake Trasimeno
4.1.18. Simple analysis of results
4.2. Mapping crop types (difficulty: intermediate)
4.2.1. Download the data
4.2.2. The environmental problem
4.2.3. Scope of the exercise
4.2.4. Study area
4.2.5. Satellite images
4.2.6. Land cover information
4.2.7. Methods
4.2.8. QGIS set-up
4.2.9. Prepare multiband files for 10-meter satellite images
4.2.10. Prepare multiband files for 20-meter satellite images
4.2.11. Resize the image
4.2.12. Create the training samples for image classification
4.2.13. Automatic mapping of crop types
4.2.14. Simple analysis of results
4.3. Monitoring crops’ vegetative stage (difficulty: easy)
4.3.1. Download the data
4.3.2. The environmental problem
4.3.3. Scope of the exercise
4.3.4. Study area
4.3.5. Satellite images
4.3.6. Land cover information
4.3.7. Methods
4.3.8. QGIS set-up
4.3.9. Calculate NDVI
4.3.10. Select the NDVI information for Barley and Potato
4.3.11. Compare winter crops and summer crops
4.3.12. Simple analysis of results
4.4. Additional resources
5. Credits
GIS4Schools
»
Index
Edit on GitHub
Index