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About This Course

Welcome to the Wetland Toolkit Course, where you’ll learn to harness Digital Earth Africa’s open-source EO tools and data to map, classify and monitor wetlands across Africa. Wetlands deliver vital ecosystem services—water purification, flood regulation, carbon storage and biodiversity support—yet are rapidly disappearing due to drainage, agriculture and climate change. By the end of this course you will be able to use DE Africa’s Water Observations from Space (WOfS), Wetlands Insight Tool (WIT), Open Data Cube machine-learning workflows, and spectral indices (NDWI, NDVI, NDTI) to delineate wetland extent, classify wetland types, monitor seasonal and long-term dynamics, and support SDG 6.6.1 reporting.

Course Objectives

• Delineate wetland extent and intrinsic potential using optical (Sentinel-2, Landsat) and radar data.
• Classify wetlands by vegetation cover (open water vs vegetated; non-vegetated, herbaceous, forested) and detect converted areas (urban, cropland) following FAO LCCS principles.
• Compute and visualise time-series indicators: water clarity (NDTI), vegetation health (NDVI & anomalies), inundation frequency (WOfS) and fractional cover (WIT).
• Support SDG 6.6.1 reporting by quantifying changes in wetland extent and condition over time.
• Explain key wetland ecosystem services and threats, interpret data gaps (e.g. cloud cover) and compile results into concise reports and visualisations.

Course Structure

1. Session 1: Wetland Delineation & Classification
   Part A: Supervised machine-learning on the ODC to map intrinsic wetland potential using Sentinel-2, radar and elevation data.
   Part B: Basic classification into vegetation vs converted classes (optical, radar, cropland/urban).
2. Session 2: EO Indicators & Wetland Types
   Compute NDTI for water clarity (Landsat & WOfS mask).
   Use WIT and WOfS to plot seasonal inundation and vegetation fractions.
   Analyse NDVI anomalies for wetland health and apply them to the DE Africa Waterbodies dataset.
3. Session 3: Vegetated Wetlands & Mangroves
   Map and monitor mangrove ecosystems using the Global Mangrove Watch baseline.
   Apply NDVI and NDWI to assess mangrove extent and health over time.

Key Monitoring Components

• Water Observations from Space (WOfS): Landsat-derived maps of historical surface water—seasonality, long-term trends and perennial vs seasonal wetlands.
• Wetlands Insight Tool (WIT): Interactive notebook combining fractional cover, WOfS detections and other datasets into stacked-area plots of wetland composition.
• Landsat Analysis Ready Data (ARD): Harmonised 30-year archive of surface-reflectance imagery underpinning DE Africa products and custom indices.
• Vegetation & Water Indices: NDVI for vegetation ‘greenness’; NDWI for open water—analysed to reveal flooding patterns and phenology.
• Global Mangrove Watch (GMW): Pan-Africa baseline of mangrove extent (1996–2016) for canopy classification, tidal adjustment and coastal wetland change detection.

All exercises run in DE Africa’s cloud-based Sandbox using Python in Jupyter notebooks, with example code you can adapt for your own study areas. Learners are encouraged to view DE Africa live sessions on YouTube and consult the DE Africa User Guide.

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