Welcome to Gis4Schools’s documentation!

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