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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 problemsCartography5 problemsWeb GIS4 problemsData Management18 problemsGIS Architecture5 problems
Level
Beginner1 problemIntermediate4 problemsAdvanced4 problemsExpert0 problems
Hand in
SQL0 problemsPython0 problemsGeoJSON3 problemsAnswers2 problemsSchema0 problemsDecisions1 problemDataset file2 problems
Category
Data preparation0 problemsData quality0 problemsSpatial analysis0 problemsRaster analysis2 problemsCartography0 problemsDecision support1 problemGeospatial systems1 problemWeb delivery0 problems
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Remote SensingAdvancedClear all
  1. Not started, Defend a borough greening shortlistProjectDecision support3 steps

    Measure canopy and summer vegetation on their own grids, then add low-ground context and apply one transparent shortlist rule.

    Remote SensingadvancedDifficulty: advanced620 XP~110 min13 checks

    Worked in 3 steps, each checked before the next one opens.

    1. Audit the vegetation rasters · Answers
    2. Deliver the borough evidence table · Dataset file
    3. Add low-ground context and shortlist · GeoJSON

    Datasets

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

    What you’ll do

    • Audit the two vegetation measures from observed raster pixels
    • Hand over a per-borough canopy and NDVI table as a GIS file
    • Add area-weighted low ground and an explicit shortlist flag
    zonal statisticsNDVIland coverDEMmulti-criteriaLondonAlso trains Spatial Analysis, Data Management
    Open project
  2. Not started, Design the searchable imagery archiveGeospatial systemsDecisions

    Choose a search, storage, preview and revision pattern for an imagery service with reproducible results.

    GIS ArchitectureadvancedDifficulty: advanced460 XP~70 min5 checks

    You hand in a set of design decisions.

    Dataset

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

    What you’ll do

    • Separate scene discovery from pixel storage and map rendering
    • Select an access pattern suited to small viewport reads and flexible band expressions
    • Preserve exact-version provenance through corrections
    system designSTACcloud optimized GeoTIFFraster tilesprovenanceAlso trains Remote Sensing, Data Management, Web GIS
    Open problem
  3. Not started, Mean NDVI per borough, across a projection boundaryRaster analysisGeoJSON

    Zonal statistics where the raster is in UTM and the polygons are in WGS 84: reproject the right layer, compute the index per borough, and hand back a map.

    Remote SensingadvancedDifficulty: advanced300 XP~50 min7 checks

    You hand in a GeoJSON result.

    Datasets

    • Greater London, Sentinel-2 red and NIR, 11 July 2025 · Raster · EPSG:32630
    • London boroughs · Polygon · 33 features · EPSG:4326

    What you’ll do

    • Recognise a CRS mismatch between a raster and a vector layer
    • Reproject the vector layer rather than resample the raster
    • Compute a per-zone mean of a derived index
    NDVIzonal statisticsCRSUTMSentinel-2LondonAlso trains Spatial Analysis, Data Management
    Open problem
  4. Not started, Screen Newham’s greening gridProjectRaster analysis3 steps

    Audit a real land-cover chip, deliver a measured grid file, and identify cells for field verification.

    Remote SensingadvancedDifficulty: advanced600 XP~100 min10 checks

    Worked in 3 steps, each checked before the next one opens.

    1. Audit the class chip · Answers
    2. Hand over the measured grid · Dataset file
    3. Map field-verification cells · GeoJSON

    Datasets

    • Newham WorldCover 2021 class chip · Raster · EPSG:4326
    • London boroughs · Polygon · 33 features · EPSG:4326

    What you’ll do

    • Audit class counts in the clipped raster
    • Prepare a traceable borough grid as an uploaded GIS file
    • Return only cells that meet a stated greening screen
    NewhamWorldCoverurban greeningoffline rasterAlso trains Data Management, Spatial Analysis
    Open project