Skip to content
Kharita Challenges

Problems

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

10 of 59 problems

Pick one for me
  1. Not started, At which zoom does the dock layer fit in a tile?Web deliveryAnswers

    Count features per XYZ tile across zoom levels to set a vector-tile pipeline's minimum zoom and its per-tile limit honestly.

    Web GISintermediateDifficulty: intermediate190 XP~30 min4 checks

    You hand in your answers as values.

    Dataset

    • Santander Cycles docking stations (live snapshot) · Point · 799 features · EPSG:4326

    What you’ll do

    • Convert coordinates to tile indices at several zooms
    • Count features per tile and find the maximum
    • Choose a minimum zoom from the data rather than a default
    vector tilesXYZtippecanoezoom levelsLondonAlso trains Spatial Analysis
    Open problem
  2. Not started, How big does Web Mercator make Greenland?CartographyAnswers

    Put a number on the most famous distortion in cartography: the same countries measured on the ellipsoid and on the projection every web map uses.

    CartographyintermediateDifficulty: intermediate210 XP~30 min4 checks

    You hand in your answers as values.

    Dataset

    • Countries · MultiPolygon · 241 features · EPSG:4326

    What you’ll do

    • Measure area geodesically or in an equal-area projection
    • Project the same polygons to Web Mercator and take their planar area
    • Express the distortion as ratios a reader can repeat
    Web Mercatorprojectionarea distortionEqual EarthglobalAlso trains Spatial Analysis
    Open problem
  3. Not started, The buffer that shrank on the way to the mapCartographyAnswers

    Quantify what a 400 m buffer drawn in EPSG:3857 actually covers on the ground in London, and how much of the coverage report it loses.

    CartographyintermediateDifficulty: intermediate200 XP~30 min4 checks

    You hand in your answers as values.

    Datasets

    • Santander Cycles docking stations (live snapshot) · Point · 799 features · EPSG:4326
    • London boroughs · Polygon · 33 features · EPSG:4326

    What you’ll do

    • Derive the Web Mercator scale factor at London's latitude
    • Translate a projected buffer distance into its ground equivalent
    • Re-run the coverage analysis with the shrunken buffer and measure the shortfall
    Web Mercatorscale factorprojectionbufferLondonAlso trains Spatial Analysis
    Open problem
  4. Not started, Which ports in the registry are the same port?Data qualityAnswers

    Find probable duplicates in a facility registry by combining a name match with a distance rule — and separate them from the honest homonyms.

    Data ManagementintermediateDifficulty: intermediate190 XP~30 min4 checks

    You hand in your answers as values.

    Dataset

    • Ports · Point · 1,081 features · EPSG:4326

    What you’ll do

    • Find repeated identifiers in a registry
    • Combine an attribute match with a spatial rule to separate duplicates from homonyms
    • Size the missing attribute that would resolve the rest
    data qualitydeduplicationhaversineregistryglobalAlso trains Spatial Analysis
    Open problem
  5. Not started, Build an earthquake contact reconnaissance queueProjectDecision support3 steps

    Screen strong shallow events, quantify airfield and settlement proximity, and hand over a traceable contact map.

    Spatial AnalysisadvancedDifficulty: advanced550 XP~95 min12 checks

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

    1. Select the event queue · SQL
    2. Measure contact gaps · Answers
    3. Hand over the access map · Python

    Datasets

    • Global M5.5+ earthquakes, Jan–Mar 2025 · Point · 86 features · EPSG:4326
    • World airports · Point · 893 features · EPSG:4326
    • Populated places · Point · 1,251 features · EPSG:4326

    What you’ll do

    • Select a reproducible event queue in SQL
    • Measure two independent global proximity indicators
    • Deliver an auditable access map with an explicit contact-gap distinction
    projectUSGSnearest neighbourlogisticsglobalAlso trains Python, Data Management, Cartography
    Open project
  6. Not started, Classify a map where most of the values are zeroCartographyAnswers

    Quantile breaks collapse on a distribution dominated by zeros. Measure how, on the river-kilometres-per-country table, and say what a map maker should do instead.

    CartographyadvancedDifficulty: advanced290 XP~45 min6 checks

    You hand in your answers as values.

    Datasets

    • Countries · MultiPolygon · 241 features · EPSG:4326
    • Rivers and lake centrelines · LineString · 461 features · EPSG:4326

    What you’ll do

    • Reproduce a derived per-country measure
    • Compute quantile and equal-interval breaks on a zero-heavy distribution
    • Quantify how each scheme distributes the countries
    choroplethclassificationquantileszero-inflatedhydrologyAlso trains Python, Spatial Analysis
    Open problem
  7. 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
  8. 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
  9. Not started, Plan a cycle redistribution shiftProjectDecision support3 steps

    Classify the dock snapshot, propose bounded bike moves, and size the resulting shift with its unserved stations visible.

    Spatial AnalysisadvancedDifficulty: advanced600 XP~100 min11 checks

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

    1. Classify the snapshot · SQL
    2. Map feasible transfers · GeoJSON
    3. Size the preliminary shift · Answers

    Dataset

    • Santander Cycles docking stations (live snapshot) · Point · 799 features · EPSG:4326

    What you’ll do

    • Classify full and empty active stations in SQL
    • Build a bounded nearest-source transfer map
    • Size a shift and report unserved empties from the same rules
    nearest neighbouroperationscapacityCRStransportLondonAlso trains Data Management, GIS Architecture
    Open project
  10. 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