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Kharita Challenges

Problems

Real geospatial problems, graded automatically. Choose a track, a level and what you want to hand in.

3 of 59 problems

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Track
Spatial Analysis2 problemsPostGIS / SQL0 problemsPython0 problemsRemote Sensing3 problemsCartography0 problemsWeb GIS0 problemsData Management0 problemsGIS Architecture0 problems
Hand in
SQL0 problemsPython0 problemsGeoJSON2 problemsAnswers1 problemSchema0 problemsDecisions0 problemsDataset file0 problems
  1. Not started, How green was London on 11 July 2025?Raster analysisAnswers

    Compute NDVI from a two-band Sentinel-2 clip, handle nodata and integer types properly, and report the distribution a monitoring programme quotes.

    Remote SensingintermediateDifficulty: intermediate220 XP~35 min4 checks

    You hand in your answers as values.

    Dataset

    • Greater London, Sentinel-2 red and NIR, 11 July 2025 · Raster · EPSG:32630

    What you’ll do

    • Compute a band ratio index with correct types
    • Exclude nodata from every statistic
    • Summarise the index as the programme's three figures
    NDVISentinel-2band mathnodataLondon
    Open problem
  2. Not started, How much of each borough lies below ten metres?Raster analysisGeoJSON

    Threshold a DEM, count inside polygons, and turn pixels into square kilometres on a geographic grid — a flood-screening figure per borough.

    Spatial AnalysisintermediateDifficulty: intermediate240 XP~40 min6 checks

    You hand in a GeoJSON result.

    Datasets

    • Greater London elevation (Copernicus DEM GLO-30) · Raster · EPSG:4326
    • London boroughs · Polygon · 33 features · EPSG:4326

    What you’ll do

    • Threshold a continuous raster
    • Count the thresholded pixels per polygon
    • Convert pixels to ground area on a geographic grid
    DEMthresholdzonalpixel areafloodLondonAlso trains Remote Sensing
    Open problem
  3. Not started, Which boroughs have the least tree cover?Raster analysisGeoJSON

    Zonal statistics on a categorical raster: the share of tree-cover pixels inside each borough polygon, for a tree-planting programme's targeting.

    Remote SensingintermediateDifficulty: intermediate230 XP~40 min7 checks

    You hand in a GeoJSON result.

    Datasets

    • Greater London land cover 2021 (ESA WorldCover 10 m) · Raster · EPSG:4326
    • London boroughs · Polygon · 33 features · EPSG:4326

    What you’ll do

    • Compute zonal statistics of a categorical raster over polygons
    • Express the class as a share per zone
    • Return the polygons ready for a choropleth
    zonal statisticsland coverraster–vectorWorldCoverLondonAlso trains Spatial Analysis
    Open problem