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    • Pour commencer
    • Beginner’s Guide
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    • Real World Examples
      • Burnt area mapping using Sentinel-2 data
      • Monitoring change through time using satellite imagery filmstrip plots
      • Monitoring chlorophyll-a in African waterbodies
      • Monitoring coastal erosion along Africa’s coastline
      • Measuring crop health
      • Exporting high quality satellite images
      • Forecasting cropland vegetation condition
      • Modelling intertidal elevation using tidal data
      • Identifying active irrigated cropping
      • Machine learning with the Open Data Cube
      • Monitoring Mangrove Extents
      • Vegetation Phenology
      • Radar vegetation phenology using Sentinel-1
      • Urban area mapping using Sentinel 1 data
      • Water detection with Sentinel-1
      • Rainfall anomalies from Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS)
      • Identifying ships with Sentinel-1
      • Timeseries analysis of temperature
      • Detecting change in urban extent
      • Urbanization Index Comparisons with Global Human Settlement (GHS)
      • Monthly vegetation condition anomalies
      • Vegetation Change Detection
      • Mapping longer-term changes in water extent with WOfS
      • Determining seasonal extent of waterbodies with Sentinel-2
      • Monitoring Water Quality
      • Turbidity in wetlands
      • Wetlands Insight Tool
      • Scalable Supervised Machine Learning
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Digital Earth Africa
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  • Analyse Sandbox »
  • Real World Examples

Real World Examples¶

More complex workflows demonstrating how DE Africa can be used to address real-world problems.

  • Burnt area mapping using Sentinel-2 data
  • Monitoring change through time using satellite imagery filmstrip plots
  • Monitoring chlorophyll-a in African waterbodies
  • Monitoring coastal erosion along Africa’s coastline
  • Measuring crop health
  • Exporting high quality satellite images
  • Forecasting cropland vegetation condition
  • Modelling intertidal elevation using tidal data
  • Identifying active irrigated cropping
  • Machine learning with the Open Data Cube
  • Monitoring Mangrove Extents
  • Vegetation Phenology
  • Radar vegetation phenology using Sentinel-1
  • Urban area mapping using Sentinel 1 data
  • Water detection with Sentinel-1
  • Rainfall anomalies from Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS)
  • Identifying ships with Sentinel-1
  • Timeseries analysis of temperature
  • Detecting change in urban extent
  • Urbanization Index Comparisons with Global Human Settlement (GHS)
  • Monthly vegetation condition anomalies
  • Vegetation Change Detection
  • Mapping longer-term changes in water extent with WOfS
  • Determining seasonal extent of waterbodies with Sentinel-2
  • Monitoring Water Quality
  • Turbidity in wetlands
  • Wetlands Insight Tool
  • Scalable Supervised Machine Learning

These notebooks can also be found in your home folder on the sandbox, or accessed from GitHub at:

https://github.com/digitalearthafrica/deafrica-sandbox-notebooks

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