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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 Analysis14 problemsPostGIS / SQL5 problemsPython6 problemsRemote Sensing4 problemsCartography5 problemsWeb GIS4 problemsData Management18 problemsGIS Architecture5 problems
Level
Beginner3 problemsIntermediate6 problemsAdvanced6 problemsExpert2 problems
Hand in
SQL2 problemsPython5 problemsGeoJSON0 problemsAnswers3 problemsSchema0 problemsDecisions0 problemsDataset file0 problems
Category
Data preparation1 problemData quality0 problemsSpatial analysis1 problemRaster analysis0 problemsCartography2 problemsDecision support1 problemGeospatial systems0 problemsWeb delivery1 problem
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PythonAdvancedClear all
  1. 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
  2. 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
  3. Not started, Deliver a compact sewer review mapProjectWeb delivery3 steps

    Extract a review cohort, make its browser payload inspectable, and measure the transfer budget.

    Web GISadvancedDifficulty: advanced580 XP~90 min9 checks

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

    1. Extract the review cohort · SQL
    2. Prepare the browser layer · Python
    3. Measure the transfer budget · Answers

    Dataset

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

    What you’ll do

    • Query the exact review cohort
    • Serve a compact, inspectable WGS 84 point layer
    • Measure raw and compressed payload size from the delivered layer
    NYC 311urban servicestemporal GISheat mapGeoPandasAlso trains PostGIS / SQL, Python
    Open project
  4. Not started, How much of each state is built up?Spatial analysisPython

    Overlay the urban footprints on the states in an equal-area projection and credit each side of a state line only what lies on it.

    PythonadvancedDifficulty: advanced320 XP~55 min5 checks

    You hand in a Python script.

    Datasets

    • United States states · Polygon · 51 features · EPSG:4326
    • Urban areas · Polygon · 2,143 features · EPSG:4326

    What you’ll do

    • Reproject both layers to an equal-area CRS
    • Clip the urban footprints to the states with an overlay
    • Sum clipped area per state and express it as a share of the state's area
    GeoPandasoverlayequal-areaAlbersland useAlso trains Spatial Analysis, Data Management
    Open problem
  5. Not started, Repair the park intake without losing its second partData preparationPython

    Repair an invalid park outline while preserving every valid polygon component.

    Data ManagementadvancedDifficulty: advanced370 XP~55 min6 checks

    You hand in a Python script.

    Dataset

    • Cape Town park polygons, geometry intake · Polygon · 11 features · EPSG:4326

    What you’ll do

    • Repair topology without discarding area.
    • Handle null geometry and source precedence before release.
    • Deliver a uniform polygon type.
    data-preparationcape townpythonAlso trains Python
    Open problem
  6. Not started, Show country CO2 change without losing the outlierCartographyPython

    Join two WDI observations to country polygons, preserve the true change, and cap only the display value.

    CartographyadvancedDifficulty: advanced500 XP~85 min7 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 and join two independently sourced global datasets on a stable country key
    • Calculate signed per-capita change while excluding missing year pairs
    • Publish a diverging polygon map with a disclosed display cap and the true values retained
    projectWorld BankNatural Earthdata joindiverging mapglobalAlso trains Python, Data Management
    Open problem