Skip to main content
Ctrl+K
Digital Earth Africa 2026 documentation - Home Digital Earth Africa 2026 documentation - Home
  • Home
  • Data
  • Platforms
  • Direct Access
  • Tech Alert
  • About
  • GitHub
  • Home
  • Data
  • Platforms
  • Direct Access
  • Tech Alert
  • About
  • GitHub

Section Navigation

MAPS AND VISUALISATION

  • DE Africa Map
  • Africa GeoPortal

ANALYSIS AND DATA DISCOVERY

  • Digital Earth Africa Sandbox
    • Getting Started
    • Beginner’s Guide
      • Introduction to Jupyter notebooks
      • Introduction to products and measurements
      • Loading data from Digital Earth Africa
      • Introduction to plotting
      • Performing a basic analysis
      • Introduction to Numpy
      • Introduction to xarray
      • Parallel processing with Dask
      • Beginner’s Guide
    • Datasets
      • ALOS/ALOS-2 PALSAR/PALSAR-2 Annual Mosaics
      • OECD/SWAC Africapolis with urban green space indicators
      • Copernicus Global Land Service Lake Water Quality
      • ERA5 Climate Gridded Data
      • Coastlines
      • Cropland extent maps for Africa
      • Digital Elevation Models
      • Fractional Cover
      • GeoMAD
      • Global Mangrove Watch
      • High Resolution Population Density Maps
      • Land Use Land Cover Maps
      • Landsat Surface Reflectance
      • Landsat Surface Temperature
      • Monthly NDVI Anomaly
      • NDVI Climatology
      • OpenStreetMap
      • Datasets
      • Rainfall - Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS)
      • Rolling GeoMAD
      • Sentinel-1
      • Sentinel-1 Monthly Mosaic
      • Sentinel-2 Collection 1
      • Sentinel-3 OLCI Land
      • Sentinel-3 SLSTR Land Surface Temperature
      • Sentinel-3 Synergy Vegetation Product.
      • Sentinel-3 OLCI Water
      • Sentinel-5P Tropomi Level-2
      • Global Root-zone moisture Analysis & Forecasting System (GRAFS)
      • WaPOR Data Loading
      • Water Observations from Space (WOfS)
      • Digital Earth Africa Water Quality Monitoring Service (WQMS)
      • Waterbodies
      • ESA WorldCereal
      • The World Settlement Footprint (WSF)
      • World Settlement Footprint - Evolution
      • The World Settlement Footprint (WSF)
      • iSDA soil data
    • Frequently Used Code
      • Run analyses on multiple polygons
      • Generating animated time series using xr_animation
      • Applying WOfS Bitmasking
      • Calculating band indices
      • Calculating band indices with Spyndex package
      • Cloud and pixel quality masking for Landsat
      • Extracting contour lines
      • Downloading and streaming data using STAC metadata
      • Exporting Cloud-Optimised GeoTIFFs
      • Generating continental animated time series using xr_animation
      • Generating composite images
      • Generating GeoMAD composites
      • Image segmentation
      • Displaying satellite imagery on a web map
      • Integrating external data from a CSV
      • Exporting to Google Drive from the Sandbox
      • Principal component analysis for multi-spectral data
      • Frequently used code
      • Rasterising vectors & vectorising rasters
      • Reprojecting datacube and raster data
      • Combining satellite data with tidal modelling using OTPS
      • Using load_ard to load and cloud mask multiple satellite sensors
      • Working with time in xarray
    • Real World Examples
      • True colour animations with rainfall
      • Burnt area mapping using Sentinel-2 data
      • Near real-time burnt area mapping using the Digital Earth Africa datacube
      • 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
      • Monitoring Crop Health using Enhanced Vegetation Index
      • Exporting high quality satellite images
      • Detection of Floating Marine Debris
      • Forecasting cropland vegetation condition
      • Monitoring changes in forest extent
      • Exporting satellite imagery animations
      • Inspecting WaPOR through time
      • Modelling intertidal elevation using tidal data
      • Modelling intertidal elevation using tidal data and Sentinel-2
      • Identifying active irrigated cropping
      • Irrigated crop water requirements
      • Machine learning with the Open Data Cube
      • Monitoring Mangrove Extents
      • Generating NDVI animations
      • Vegetation Phenology
      • Radar vegetation phenology using Sentinel-1
      • Real_world_examples
      • 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
      • OECD/SWAC urban green space and tree cover estimation approach
      • Urbanization Index Comparisons with Global Human Settlement (GHS)
      • Mapping urban tree extent
      • Monthly vegetation condition anomalies
      • Vegetation Change Detection
      • Mapping longer-term changes in water extent with WOfS
      • Determining seasonal extent of waterbodies with Sentinel-2
      • Time Series Monitoring of Aquatic Weeds and Floating Algae
      • Time Series Monitoring of Turbidity
      • Monitoring Water Quality
      • Waterbodies Long-Term Animations
      • Waterbodies Seasonal Animations
      • Turbidity in wetlands
      • Wetlands Insight Tool
      • Scalable Supervised Machine Learning
        • Scalable Supervised Machine Learning on the Open Data Cube
        • Extracting training data from the ODC
        • Inspecting training data
        • Evaluate, optimize, and fit a classifier
        • Classifying satellite data
        • Object-based filtering of pixel classifications
    • Use Cases
    • DE Africa Tools Package
      • deafrica_tools.areaofinterest
      • deafrica_tools.bandindices
      • deafrica_tools.coastal
      • deafrica_tools.dask
      • deafrica_tools.load_era5
      • deafrica_tools.load_soil_moisture
      • deafrica_tools.plotting
      • deafrica_tools.spatial
      • deafrica_tools.temporal
        • deafrica_tools.temporal.xr_phenology
        • deafrica_tools.temporal.temporal_statistics
      • deafrica_tools.waterbodies
      • deafrica_tools.app.deacoastlines
      • deafrica_tools.app.forestmonitoring
      • deafrica_tools.app.geomedian
      • deafrica_tools.app.imageexport
      • deafrica_tools.app.widgetconstructors
    • Getting Help with the Sandbox
    • Version Control with Git
      • What is Git?
      • Connect to Git
      • Git with the Git menu
      • Git with Terminal
      • Make a pull request (PR)
    • Understanding Dask
      • Lazy-loading Data
      • Lazy Operations
      • Dask Client for Larger Datasets
    • Google Drive Access
    • DE Africa Sandbox Terms and Conditions

LOCAL DEPLOYMENT

  • Cube in a Box
  • Digital Earth Africa Platforms
  • Analysis Sandbox
  • Real World Examples
  • Scalable Supervised Machine Learning

Scalable Supervised Machine Learning#

This workflow covers training a machine learning model to classify satellite data.

  • Scalable Supervised Machine Learning on the Open Data Cube
  • Extracting training data from the ODC
  • Inspecting training data
  • Feature Importance
  • Evaluate, optimize, and fit a classifier
  • Classifying satellite data
  • Object-based filtering of pixel classifications
Digital Earth Africa is a programme of icipe – International Centre of Insect Physiology and Ecology
© 2026 Digital Earth Africa. All Rights Reserved. Privacy