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Kharita Challenges

Problems

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

6 of 59 problems

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Track
Spatial Analysis5 problemsPostGIS / SQL3 problemsPython2 problemsRemote Sensing0 problemsCartography4 problemsWeb GIS0 problemsData Management4 problemsGIS Architecture0 problems
Level
Beginner0 problemsIntermediate6 problemsAdvanced5 problemsExpert0 problems
Hand in
SQL3 problemsPython2 problemsGeoJSON1 problemAnswers0 problemsSchema0 problemsDecisions0 problemsDataset file0 problems
Category
Data preparation1 problemData quality4 problemsSpatial analysis4 problemsRaster analysis3 problemsCartography2 problemsDecision support6 problemsGeospatial systems0 problemsWeb delivery3 problems
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IntermediateDecision supportClear all
  1. Not started, Build the global seismic reconnaissance watchlistDecision supportPython

    Turn a fixed USGS event feed into a mapped, reproducible shallow strong-event watchlist for requesting impact products.

    Spatial AnalysisintermediateDifficulty: intermediate240 XP~40 min5 checks

    You hand in a Python script.

    Dataset

    • Global M5.5+ earthquakes, Jan–Mar 2025 · Point · 86 features · EPSG:4326

    What you’ll do

    • Apply two inclusive, unit-aware filters to the frozen event snapshot
    • Carry stable event identifiers and response metadata into a point GeoDataFrame
    • Map event magnitude as a proportional point result without claiming it is impact
    USGSearthquakesGeoPandasemergency screeningglobalAlso trains Python, Data Management, Cartography
    Open problem
  2. Not started, Redirect the rider at an empty dockDecision supportSQL

    For every station with no bikes, the nearest station that has one, and the walk in metres — with the KNN operator so it stays fast at 799 stations or 79,000.

    PostGIS / SQLintermediateDifficulty: intermediate250 XP~40 min5 checks

    You hand in a spatial SQL query.

    Dataset

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

    What you’ll do

    • Filter to stations with no bikes
    • Find each one's nearest stocked station with an index-assisted nearest-neighbour search
    • Report the distance in metres
    KNNLATERALGiSTgeographyperformancetransport
    Open problem
  3. Not started, Where should a waterway survey start?Decision supportSQL

    Screen large global urban footprints for mapped river contact while keeping scale limitations explicit.

    Spatial AnalysisintermediateDifficulty: intermediate320 XP~50 min9 checks

    You hand in a spatial SQL query.

    Datasets

    • Urban areas · Polygon · 2,143 features · EPSG:4326
    • Rivers and lake centrelines · LineString · 461 features · EPSG:4326

    What you’ll do

    • Apply a spatial join to real river and urban geometry
    • Keep zero-contact footprints in the inventory
    • Distinguish map-scale contact classes for survey planning
    Natural Earthurban waterPostGISspatial screeningcategorical mapglobalAlso trains PostGIS / SQL, Cartography, Data Management
    Open problem
  4. Not started, Where should the sewer service desk review closure lag?Decision supportPython

    Turn a fixed 311 complaint cohort into a map of requests open longer than an analyst-defined day.

    Spatial AnalysisintermediateDifficulty: intermediate320 XP~50 min5 checks

    You hand in a Python script.

    Dataset

    • NYC 311 sewer requests, 1–7 June 2025 · Point · 408 features · EPSG:4326

    What you’ll do

    • Calculate closure lag from timestamp fields without inventing values for open requests
    • Select the service manager's review queue
    • Map the concentration of selected requests while retaining per-request details
    NYC 311urban servicestemporal GISheat mapGeoPandasAlso trains Python, Cartography, Data Management
    Open problem
  5. Not started, Which airfields should the response desk check?Decision supportSQL

    Use a metre-based spatial join to identify civil airfields near strong, shallow earthquake epicentres, with the facilities drawn on the map.

    PostGIS / SQLintermediateDifficulty: intermediate260 XP~45 min6 checks

    You hand in a spatial SQL query.

    Datasets

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

    What you’ll do

    • Filter events by magnitude and depth
    • Join the selected events to civil airfields within 250 km in metres
    • Return traceable, mapped airport points and measured distances
    PostGISearthquake responseairportsgeographyglobalAlso trains Spatial Analysis, Cartography
    Open problem
  6. Not started, Which capitals are more than an hour from a scheduled airport?Decision supportGeoJSON

    Nearest-neighbour from 200 national capitals to 872 civil airports, geodesically, with a threshold that has to be applied honestly.

    Spatial AnalysisintermediateDifficulty: intermediate230 XP~40 min5 checks

    You hand in a GeoJSON result.

    Datasets

    • Populated places · Point · 1,251 features · EPSG:4326
    • World airports · Point · 893 features · EPSG:4326

    What you’ll do

    • Filter the places to national capitals and the airports to civil scheduled-traffic fields
    • Find each capital's nearest qualifying airport with a geodesic distance
    • Keep the capitals beyond 75 km and report the airport and the distance
    nearest neighbourgeodesichaversinelogisticsglobalAlso trains Data Management
    Open problem