Problems
Real geospatial problems, graded automatically. Choose a track, a level and what you want to hand in.
- Not started, Accept the rasters, or send them backData qualityAnswersData ManagementintermediateDifficulty: intermediate200 XP~35 min6 checksData ManagementintermediateDifficulty: intermediate
The checks a data manager runs on delivered rasters before anyone analyses them: extent, nodata, value range, and whether the figures are plausible for the place.
You hand in your answers as values.
Datasets
- Greater London elevation (Copernicus DEM GLO-30) · Raster · EPSG:4326
- Greater London land cover 2021 (ESA WorldCover 10 m) · Raster · EPSG:4326
- Greater London, Sentinel-2 red and NIR, 11 July 2025 · Raster · EPSG:32630
What you’ll do
- Read raster metadata and full-resolution statistics
- Distinguish nodata from valid extremes
- Record facts a later dispute can start from
raster QAnodatametadataacceptanceLondonAlso trains Remote SensingOpen problem - Not started, At which zoom does every capital get its own tile?Web deliveryAnswersWeb GISintermediateDifficulty: intermediate180 XP~25 min4 checksWeb GISintermediateDifficulty: intermediate
Count capitals per XYZ tile across zooms to decide where a label layer switches from clustering to one label per city.
You hand in your answers as values.
Dataset
- Populated places · Point · 1,251 features · EPSG:4326
What you’ll do
- Convert points to tile indices at several zooms
- Find the busiest tile per zoom
- Choose a switch-over zoom from the data
XYZ tileslabelsclusteringzoom levelsglobalAlso trains CartographyOpen problem - Not started, At which zoom does the dock layer fit in a tile?Web deliveryAnswersWeb GISintermediateDifficulty: intermediate190 XP~30 min4 checksWeb GISintermediateDifficulty: intermediate
Count features per XYZ tile across zoom levels to set a vector-tile pipeline's minimum zoom and its per-tile limit honestly.
You hand in your answers as values.
Dataset
- Santander Cycles docking stations (live snapshot) · Point · 799 features · EPSG:4326
What you’ll do
- Convert coordinates to tile indices at several zooms
- Count features per tile and find the maximum
- Choose a minimum zoom from the data rather than a default
vector tilesXYZtippecanoezoom levelsLondonAlso trains Spatial AnalysisOpen problem - Not started, How big does Web Mercator make Greenland?CartographyAnswersCartographyintermediateDifficulty: intermediate210 XP~30 min4 checksCartographyintermediateDifficulty: intermediate
Put a number on the most famous distortion in cartography: the same countries measured on the ellipsoid and on the projection every web map uses.
You hand in your answers as values.
Dataset
- Countries · MultiPolygon · 241 features · EPSG:4326
What you’ll do
- Measure area geodesically or in an equal-area projection
- Project the same polygons to Web Mercator and take their planar area
- Express the distortion as ratios a reader can repeat
Web Mercatorprojectionarea distortionEqual EarthglobalAlso trains Spatial AnalysisOpen problem - Not started, How green was London on 11 July 2025?Raster analysisAnswersRemote SensingintermediateDifficulty: intermediate220 XP~35 min4 checksRemote SensingintermediateDifficulty: intermediate
Compute NDVI from a two-band Sentinel-2 clip, handle nodata and integer types properly, and report the distribution a monitoring programme quotes.
You hand in your answers as values.
Dataset
- Greater London, Sentinel-2 red and NIR, 11 July 2025 · Raster · EPSG:32630
What you’ll do
- Compute a band ratio index with correct types
- Exclude nodata from every statistic
- Summarise the index as the programme's three figures
NDVISentinel-2band mathnodataLondonOpen problem - Not started, The buffer that shrank on the way to the mapCartographyAnswersCartographyintermediateDifficulty: intermediate200 XP~30 min4 checksCartographyintermediateDifficulty: intermediate
Quantify what a 400 m buffer drawn in EPSG:3857 actually covers on the ground in London, and how much of the coverage report it loses.
You hand in your answers as values.
Datasets
- Santander Cycles docking stations (live snapshot) · Point · 799 features · EPSG:4326
- London boroughs · Polygon · 33 features · EPSG:4326
What you’ll do
- Derive the Web Mercator scale factor at London's latitude
- Translate a projected buffer distance into its ground equivalent
- Re-run the coverage analysis with the shrunken buffer and measure the shortfall
Web Mercatorscale factorprojectionbufferLondonAlso trains Spatial AnalysisOpen problem - Not started, When the attributes and the geometry disagreeData qualityAnswersData ManagementintermediateDifficulty: intermediate200 XP~35 min5 checksData ManagementintermediateDifficulty: intermediate
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.
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 PythonOpen problem - Not started, Which ports in the registry are the same port?Data qualityAnswersData ManagementintermediateDifficulty: intermediate190 XP~30 min4 checksData ManagementintermediateDifficulty: intermediate
Find probable duplicates in a facility registry by combining a name match with a distance rule — and separate them from the honest homonyms.
You hand in your answers as values.
Dataset
- Ports · Point · 1,081 features · EPSG:4326
What you’ll do
- Find repeated identifiers in a registry
- Combine an attribute match with a spatial rule to separate duplicates from homonyms
- Size the missing attribute that would resolve the rest
data qualitydeduplicationhaversineregistryglobalAlso trains Spatial AnalysisOpen problem - Not started, Why a cloud-optimised GeoTIFF is cheap to serveWeb deliveryAnswersGIS ArchitectureintermediateDifficulty: intermediate200 XP~30 min4 checksGIS ArchitectureintermediateDifficulty: intermediate
Read a COG's internal structure — tiles, overviews, bytes — and turn it into the numbers a tile server's capacity plan rests on.
You hand in your answers as values.
Datasets
- Greater London land cover 2021 (ESA WorldCover 10 m) · Raster · EPSG:4326
- Greater London, Sentinel-2 red and NIR, 11 July 2025 · Raster · EPSG:32630
What you’ll do
- Read a GeoTIFF's block size and overview structure
- Count internal tiles from dimensions and block size
- Relate the structure to what a tile request costs
COGGeoTIFFtile servercapacity planningrasterAlso trains Web GISOpen problem