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Kharita Challenges

Problems

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

3 of 59 problems

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Track
Spatial Analysis3 problemsPostGIS / SQL0 problemsPython0 problemsRemote Sensing0 problemsCartography1 problemWeb GIS0 problemsData Management2 problemsGIS Architecture0 problems
Level
Beginner3 problemsIntermediate4 problemsAdvanced8 problemsExpert0 problems
Hand in
SQL3 problemsPython2 problemsGeoJSON3 problemsAnswers3 problemsSchema0 problemsDecisions0 problemsDataset file1 problem
Category
Data preparation0 problemsData quality0 problemsSpatial analysis2 problemsRaster analysis0 problemsCartography1 problemDecision support0 problemsGeospatial systems0 problemsWeb delivery0 problems
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BeginnerGeoJSONClear all
  1. Not started, Normalise the map before you shade itCartographyGeoJSON

    Turn a count into a rate: population per square kilometre for every country, with the area measured rather than looked up.

    CartographybeginnerDifficulty: beginner140 XP~25 min6 checks

    You hand in a GeoJSON result.

    Dataset

    • Countries · MultiPolygon · 241 features · EPSG:4326

    What you’ll do

    • Measure every polygon's area in an equal-area projection
    • Compute a rate by dividing the count by the area
    • Return every country, ready to shade
    choroplethnormalisationEqual EarthdensityglobalAlso trains Spatial Analysis
    Open problem
  2. Not started, Which airports sit inside a city?Spatial analysisGeoJSON

    Point-in-polygon screening: the airports whose point falls inside a built-up footprint, for a noise-exposure programme.

    Spatial AnalysisbeginnerDifficulty: beginner130 XP~20 min5 checks

    You hand in a GeoJSON result.

    Datasets

    • World airports · Point · 893 features · EPSG:4326
    • Urban areas · Polygon · 2,143 features · EPSG:4326

    What you’ll do

    • Test each point for containment in any polygon of a second layer
    • Return the qualifying points once each, with their attributes
    point-in-polygonspatial joinscreeningaviationglobalAlso trains Data Management
    Open problem
  3. Not started, Which boroughs is the cycle-hire scheme actually in?Spatial analysisGeoJSON

    Join 799 docking stations to 33 boroughs and rank them by docks per square kilometre.

    Spatial AnalysisbeginnerDifficulty: beginner130 XP~25 min6 checks

    You hand in a GeoJSON result.

    Datasets

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

    What you’ll do

    • Spatially join docking stations to the borough that contains them
    • Sum docking points per borough without dropping the boroughs that have none
    • Measure borough area in a metric CRS and compute docks per km²
    spatial joinaggregationCRStransportLondonAlso trains Data Management
    Open problem