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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 Analysis1 problemPostGIS / SQL0 problemsPython2 problemsRemote Sensing1 problemCartography1 problemWeb GIS0 problemsData Management4 problemsGIS Architecture0 problems
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Beginner1 problemIntermediate2 problemsAdvanced0 problemsExpert0 problems
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SQL0 problemsPython1 problemGeoJSON0 problemsAnswers1 problemSchema0 problemsDecisions0 problemsDataset file0 problems
Category
Data preparation0 problemsData quality2 problemsSpatial analysis2 problemsRaster analysis0 problemsCartography0 problemsDecision support2 problemsGeospatial systems0 problemsWeb delivery0 problems
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PythonIntermediateData qualityClear all
  1. 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
  2. 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