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Kharita Challenges

Problems

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

4 of 59 problems

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Track
Spatial Analysis14 problemsPostGIS / SQL5 problemsPython6 problemsRemote Sensing4 problemsCartography9 problemsWeb GIS3 problemsData Management9 problemsGIS Architecture1 problem
Level
Beginner1 problemIntermediate4 problemsAdvanced4 problemsExpert0 problems
Hand in
SQL0 problemsPython0 problemsGeoJSON2 problemsAnswers2 problemsSchema0 problemsDecisions0 problemsDataset file0 problems
Category
Data preparation0 problemsData quality1 problemSpatial analysis0 problemsRaster analysis3 problemsCartography0 problemsDecision support0 problemsGeospatial systems0 problemsWeb delivery0 problems
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Remote SensingIntermediateClear all
  1. Not started, Accept the rasters, or send them backData qualityAnswers

    The checks a data manager runs on delivered rasters before anyone analyses them: extent, nodata, value range, and whether the figures are plausible for the place.

    Data ManagementintermediateDifficulty: intermediate200 XP~35 min6 checks

    You hand in your answers as values.

    Datasets

    • Greater London elevation (Copernicus DEM GLO-30) · Raster · EPSG:4326
    • Greater London land cover 2021 (ESA WorldCover 10 m) · Raster · EPSG:4326
    • Greater London, Sentinel-2 red and NIR, 11 July 2025 · Raster · EPSG:32630

    What you’ll do

    • Read raster metadata and full-resolution statistics
    • Distinguish nodata from valid extremes
    • Record facts a later dispute can start from
    raster QAnodatametadataacceptanceLondonAlso trains Remote Sensing
    Open problem
  2. 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
  3. 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
  4. 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