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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 Analysis4 problemsPostGIS / SQL0 problemsPython0 problemsRemote Sensing2 problemsCartography1 problemWeb GIS0 problemsData Management4 problemsGIS Architecture0 problems
Level
Beginner1 problemIntermediate0 problemsAdvanced4 problemsExpert0 problems
Hand in
SQL4 problemsPython4 problemsGeoJSON8 problemsAnswers5 problemsSchema1 problemDecisions2 problemsDataset file4 problems
Category
Data preparation2 problemsData quality0 problemsSpatial analysis0 problemsRaster analysis1 problemCartography0 problemsDecision support1 problemGeospatial systems0 problemsWeb delivery0 problems
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Data ManagementAdvancedDataset fileClear 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, Deliver a field-ready public asset registerProjectData preparation4 steps

    Merge two open asset extracts into a quality-controlled GeoPackage for field inspection.

    Data ManagementadvancedDifficulty: advanced600 XP~105 min17 checks

    Worked in 4 steps, each checked before the next one opens.

    1. Audit both incoming sources · Answers
    2. Build the common asset model · Dataset file
    3. Verify and round coordinates · GeoJSON
    4. Package and verify the handover · Dataset file

    Datasets

    • Melbourne toilet source · Point · 7 features · EPSG:4326
    • Melbourne drinking-water source · Point · 21 features · EPSG:4326

    What you’ll do

    • Profile and reconcile two source layers without multiplying assets.
    • Normalise access without representing unknown status as public.
    • Deliver a reproducible, typed WGS 84 GeoPackage handover.
    data-preparationprojectgeopackagemelbournehandoverAlso trains Spatial Analysis, Cartography
    Open project
  3. Not started, Deliver an access-safe public toilet layerData preparationDataset file

    Classify access honestly and deliver a typed projected GeoPackage without null locations.

    Data ManagementadvancedDifficulty: advanced365 XP~55 min6 checks

    You hand in a prepared dataset file.

    Dataset

    • Amsterdam toilet access staging · Point · 14 features · EPSG:4326

    What you’ll do

    • Distinguish missing access from public access.
    • Preserve first-source precedence and drop null geometry.
    • Deliver a named GeoPackage in the receiving CRS.
    data-preparationamsterdamfileAlso trains Spatial Analysis
    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