Skip to content
Kharita Challenges

Problems

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

3 of 59 problems

Pick one for me
Track
Spatial Analysis0 problemsPostGIS / SQL0 problemsPython1 problemRemote Sensing1 problemCartography1 problemWeb GIS1 problemData Management2 problemsGIS Architecture0 problems
Category
Data preparation0 problemsData quality1 problemSpatial analysis0 problemsRaster analysis1 problemCartography0 problemsDecision support0 problemsGeospatial systems0 problemsWeb delivery1 problem
  1. Not started, How many tiles does an offline London need?Web deliveryAnswers

    From a bounding box to a tile count: size the offline basemap for a field app across zoom 10–15.

    Web GISbeginnerDifficulty: beginner140 XP~25 min3 checks

    You hand in your answers as values.

    Dataset

    • London boroughs · Polygon · 33 features · EPSG:4326

    What you’ll do

    • Take the bounding box of the borough layer
    • Convert box corners to tile coordinates at each zoom
    • Count tiles per zoom and total them into a storage estimate
    XYZ tilesWeb Mercatorofflinecapacity planningLondonAlso trains Cartography
    Open problem
  2. Not started, What is Greater London made of?Raster analysisAnswers

    A class histogram on a 10 m land-cover raster: the shares a planning document quotes, and the reason a pixel count is not quite an area.

    Remote SensingbeginnerDifficulty: beginner140 XP~25 min5 checks

    You hand in your answers as values.

    Dataset

    • Greater London land cover 2021 (ESA WorldCover 10 m) · Raster · EPSG:4326

    What you’ll do

    • Read a categorical raster and count pixels per class
    • Express classes as shares of the valid pixels
    • State what the number is and is not
    land coverWorldCoverhistogramrasterLondonAlso trains Data Management
    Open problem
  3. 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