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Kharita Challenges

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

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Spatial Analysis2 problemsPostGIS / SQL1 problemPython3 problemsRemote Sensing1 problemCartography1 problemWeb GIS0 problemsData Management7 problemsGIS Architecture0 problems
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SQL0 problemsPython1 problemGeoJSON0 problemsAnswers2 problemsSchema0 problemsDecisions0 problemsDataset file0 problems
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Data preparation2 problemsData quality3 problemsSpatial analysis6 problemsRaster analysis0 problemsCartography2 problemsDecision support3 problemsGeospatial systems0 problemsWeb delivery1 problem
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PythonData qualityClear all
  1. Not started, Which airport codes will break the schedule join?Data qualityAnswers

    Audit a registry's identifiers before they become a join key: missing, malformed and duplicated codes, and positions that are only approximate.

    Data ManagementbeginnerDifficulty: beginner130 XP~25 min5 checks

    You hand in your answers as values.

    Dataset

    • World airports · Point · 893 features · EPSG:4326

    What you’ll do

    • Find nulls, duplicates and malformed values in an identifier column
    • Distinguish a key defect from a position defect
    • Report counts the integration can be sized against
    data qualityidentifiersjoin keysaviationAlso trains Python
    Open problem
  2. Not started, When the attributes and the geometry disagreeData qualityAnswers

    A reference gazetteer carries a latitude and a longitude column beside its geometry. Audit how far apart they are, and what else does not add up.

    Data ManagementintermediateDifficulty: intermediate200 XP~35 min5 checks

    You hand in your answers as values.

    Dataset

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

    What you’ll do

    • Compare each feature's geometry to the coordinate attributes it carries
    • Count the disagreements at two thresholds and identify the worst
    • Find keys the downstream spreadsheet cannot distinguish
    data qualitygazetteerhaversineduplicatesglobalAlso trains Python
    Open problem
  3. Not started, Which places can the emissions change map actually compare?Data qualityPython

    Audit two-date indicator coverage and map the places excluded before showing a climate trend.

    Data ManagementintermediateDifficulty: intermediate290 XP~45 min6 checks

    You hand in a Python script.

    Datasets

    • Countries · MultiPolygon · 241 features · EPSG:4326
    • CO2 per capita by country, 2010 and 2022 · Point · 241 features · EPSG:4326

    What you’ll do

    • Audit missingness before a two-date map is interpreted
    • Prevent a many-to-many join on nonstandard ISO codes
    • Show complete and incomplete coverage on real country polygons
    World Bankdata qualitymissing datacategorical mapglobalAlso trains Python, Cartography
    Open problem