Problems

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

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Data Management Clear all

Not started, Can the cycle parking feed report real capacity?Data preparationSQL
Clean a Berlin cycle parking staging table for an operations map and capacity rollup.
Data ManagementbeginnerDifficulty: beginner130 XP~25 min7 checksData ManagementbeginnerDifficulty: beginner13025m7
You hand in a spatial SQL query.
Dataset
Berlin bicycle parking capacity staging · Point · 27 features · EPSG:4326
What you’ll do
Resolve source precedence before casting.
Keep unknown capacity distinct from zero.
Return geometry for the operational map.
data-preparationberlinsqlAlso trains PostGIS / SQL
Open problem
Not started, Make the pharmacy handover loadableData preparationPython
Repair a field table so a Paris health directory can map its pharmacy locations reliably.
Data ManagementbeginnerDifficulty: beginner125 XP~25 min6 checksData ManagementbeginnerDifficulty: beginner12525m6
You hand in a Python script.
Dataset
Raw Paris pharmacy handover · Table · 21 rows · EPSG:4326
What you’ll do
Parse and validate coordinates before constructing point geometry.
Preserve the first source record for each reference.
Deliver a typed, spatially plausible point layer.
data-preparationcoordinatesquality-controlparisAlso trains Python
Open problem
Not started, Package one playground location per source featureData preparationDataset file
Turn mixed playground points and areas into a projected GeoPackage site directory.
Data ManagementbeginnerDifficulty: beginner130 XP~30 min6 checksData ManagementbeginnerDifficulty: beginner13030m6
You hand in a prepared dataset file.
Dataset
Sydney playground mixed-geometry source · Point · 8 features · EPSG:4326
What you’ll do
Convert mixed source geometry into a consistent site layer.
Reproject coordinates to the receiving metric CRS.
Package exact schema and layer name in GeoPackage.
data-preparationsydneyfileAlso trains Spatial Analysis
Open problem
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 checksRemote SensingbeginnerDifficulty: beginner14025m5
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
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 checksData ManagementbeginnerDifficulty: beginner13025m5
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
Not started, Which airports sit inside a city?Spatial analysisGeoJSON
Point-in-polygon screening: the airports whose point falls inside a built-up footprint, for a noise-exposure programme.
Spatial AnalysisbeginnerDifficulty: beginner130 XP~20 min5 checksSpatial AnalysisbeginnerDifficulty: beginner13020m5
You hand in a GeoJSON result.
Datasets
World airports · Point · 893 features · EPSG:4326
Urban areas · Polygon · 2,143 features · EPSG:4326
What you’ll do
Test each point for containment in any polygon of a second layer
Return the qualifying points once each, with their attributes
point-in-polygonspatial joinscreeningaviationglobalAlso trains Data Management
Open problem
Not started, Which boroughs is the cycle-hire scheme actually in?Spatial analysisGeoJSON
Join 799 docking stations to 33 boroughs and rank them by docks per square kilometre.
Spatial AnalysisbeginnerDifficulty: beginner130 XP~25 min6 checksSpatial AnalysisbeginnerDifficulty: beginner13025m6
You hand in a GeoJSON result.
Datasets
London boroughs · Polygon · 33 features · EPSG:4326
Santander Cycles docking stations (live snapshot) · Point · 799 features · EPSG:4326
What you’ll do
Spatially join docking stations to the borough that contains them
Sum docking points per borough without dropping the boroughs that have none
Measure borough area in a metric CRS and compute docks per km²
spatial joinaggregationCRStransportLondonAlso trains Data Management
Open problem
Not started, Accept the rasters, or send them backData qualityAnswers
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.
Data ManagementintermediateDifficulty: intermediate200 XP~35 min6 checksData ManagementintermediateDifficulty: intermediate20035m6
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 Sensing
Open problem
Not started, Build the global seismic reconnaissance watchlistDecision supportPython
Turn a fixed USGS event feed into a mapped, reproducible shallow strong-event watchlist for requesting impact products.
Spatial AnalysisintermediateDifficulty: intermediate240 XP~40 min5 checksSpatial AnalysisintermediateDifficulty: intermediate24040m5
You hand in a Python script.
Dataset
Global M5.5+ earthquakes, Jan–Mar 2025 · Point · 86 features · EPSG:4326
What you’ll do
Apply two inclusive, unit-aware filters to the frozen event snapshot
Carry stable event identifiers and response metadata into a point GeoDataFrame
Map event magnitude as a proportional point result without claiming it is impact
USGSearthquakesGeoPandasemergency screeningglobalAlso trains Python, Data Management, Cartography
Open problem
Not started, Protect the bus stop key during the loadData preparationSQL
Recover zero-padded stop identifiers before a transport timetable join.
Data ManagementintermediateDifficulty: intermediate210 XP~40 min7 checksData ManagementintermediateDifficulty: intermediate21040m7
You hand in a spatial SQL query.
Dataset
Singapore bus stop code staging · Point · 31 features · EPSG:4326
What you’ll do
Preserve identifier semantics through SQL casting.
Resolve repeated source rows deterministically.
Return a clean point layer for the timetable join.
data-preparationsingaporesqlAlso trains PostGIS / SQL
Open problem
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 checksData ManagementintermediateDifficulty: intermediate20035m5
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
Not started, Where should a waterway survey start?Decision supportSQL
Screen large global urban footprints for mapped river contact while keeping scale limitations explicit.
Spatial AnalysisintermediateDifficulty: intermediate320 XP~50 min9 checksSpatial AnalysisintermediateDifficulty: intermediate32050m9
You hand in a spatial SQL query.
Datasets
Urban areas · Polygon · 2,143 features · EPSG:4326
Rivers and lake centrelines · LineString · 461 features · EPSG:4326
What you’ll do
Apply a spatial join to real river and urban geometry
Keep zero-contact footprints in the inventory
Distinguish map-scale contact classes for survey planning
Natural Earthurban waterPostGISspatial screeningcategorical mapglobalAlso trains PostGIS / SQL, Cartography, Data Management
Open problem
Not started, Where should the sewer service desk review closure lag?Decision supportPython
Turn a fixed 311 complaint cohort into a map of requests open longer than an analyst-defined day.
Spatial AnalysisintermediateDifficulty: intermediate320 XP~50 min5 checksSpatial AnalysisintermediateDifficulty: intermediate32050m5
You hand in a Python script.
Dataset
NYC 311 sewer requests, 1–7 June 2025 · Point · 408 features · EPSG:4326
What you’ll do
Calculate closure lag from timestamp fields without inventing values for open requests
Select the service manager's review queue
Map the concentration of selected requests while retaining per-request details
NYC 311urban servicestemporal GISheat mapGeoPandasAlso trains Python, Cartography, Data Management
Open problem
Not started, Which capitals are more than an hour from a scheduled airport?Decision supportGeoJSON
Nearest-neighbour from 200 national capitals to 872 civil airports, geodesically, with a threshold that has to be applied honestly.
Spatial AnalysisintermediateDifficulty: intermediate230 XP~40 min5 checksSpatial AnalysisintermediateDifficulty: intermediate23040m5
You hand in a GeoJSON result.
Datasets
Populated places · Point · 1,251 features · EPSG:4326
World airports · Point · 893 features · EPSG:4326
What you’ll do
Filter the places to national capitals and the airports to civil scheduled-traffic fields
Find each capital's nearest qualifying airport with a geodesic distance
Keep the capitals beyond 75 km and report the airport and the distance
nearest neighbourgeodesichaversinelogisticsglobalAlso trains Data Management
Open problem
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 checksData ManagementintermediateDifficulty: intermediate29045m6
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
Not started, Which ports in the registry are the same port?Data qualityAnswers
Find probable duplicates in a facility registry by combining a name match with a distance rule — and separate them from the honest homonyms.
Data ManagementintermediateDifficulty: intermediate190 XP~30 min4 checksData ManagementintermediateDifficulty: intermediate19030m4
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 Analysis
Open problem
Not started, Are these country polygons fit to assign cities to?Data qualitySQL
A point-in-polygon audit that exposes what 1:50m generalisation does to a coastline — and which places the attribute and the geometry disagree about.
PostGIS / SQLadvancedDifficulty: advanced300 XP~45 min5 checksPostGIS / SQLadvancedDifficulty: advanced30045m5
You hand in a spatial SQL query.
Datasets
Populated places · Point · 1,251 features · EPSG:4326
Countries · MultiPolygon · 241 features · EPSG:4326
What you’ll do
Join points to the polygon containing them with an outer join
Compare an attribute to a derived value with NULL-safe semantics
Return the disagreement list, including the points nothing contains
ST_Containsouter joinIS DISTINCT FROMgeneralisationdata qualityAlso trains Data Management
Open problem
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 checksSpatial AnalysisadvancedDifficulty: advanced55095m12
Worked in 3 steps, each checked before the next one opens.
Select the event queue · SQL
Measure contact gaps · Answers
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
Not started, Defend a borough greening shortlistProjectDecision support3 steps
Measure canopy and summer vegetation on their own grids, then add low-ground context and apply one transparent shortlist rule.
Remote SensingadvancedDifficulty: advanced620 XP~110 min13 checksRemote SensingadvancedDifficulty: advanced620110m13
Worked in 3 steps, each checked before the next one opens.
Audit the vegetation rasters · Answers
Deliver the borough evidence table · Dataset file
Add low-ground context and shortlist · GeoJSON
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
Greater London elevation (Copernicus DEM GLO-30) · Raster · EPSG:4326
London boroughs · Polygon · 33 features · EPSG:4326
What you’ll do
Audit the two vegetation measures from observed raster pixels
Hand over a per-borough canopy and NDVI table as a GIS file
Add area-weighted low ground and an explicit shortlist flag
zonal statisticsNDVIland coverDEMmulti-criteriaLondonAlso trains Spatial Analysis, Data Management
Open project
Not started, Deliver a field-ready public asset registerProjectData preparation4 steps
Merge two open asset extracts into a quality-controlled GeoPackage for field inspection.
Data ManagementadvancedDifficulty: advanced600 XP~105 min17 checksData ManagementadvancedDifficulty: advanced600105m17
Worked in 4 steps, each checked before the next one opens.
Audit both incoming sources · Answers
Build the common asset model · Dataset file
Verify and round coordinates · GeoJSON
Package and verify the handover · Dataset file
Datasets
Melbourne toilet source · Point · 7 features · EPSG:4326
Melbourne drinking-water source · Point · 21 features · EPSG:4326
What you’ll do
Profile and reconcile two source layers without multiplying assets.
Normalise access without representing unknown status as public.
Deliver a reproducible, typed WGS 84 GeoPackage handover.
data-preparationprojectgeopackagemelbournehandoverAlso trains Spatial Analysis, Cartography
Open project
Not started, Deliver an access-safe public toilet layerData preparationDataset file
Classify access honestly and deliver a typed projected GeoPackage without null locations.
Data ManagementadvancedDifficulty: advanced365 XP~55 min6 checksData ManagementadvancedDifficulty: advanced36555m6
You hand in a prepared dataset file.
Dataset
Amsterdam toilet access staging · Point · 14 features · EPSG:4326
What you’ll do
Distinguish missing access from public access.
Preserve first-source precedence and drop null geometry.
Deliver a named GeoPackage in the receiving CRS.
data-preparationamsterdamfileAlso trains Spatial Analysis
Open problem
Not started, Design the global event map and detail serviceGeospatial systemsDecisions
Separate a frequently refreshed spatial overview from authoritative event details and revision history.
GIS ArchitectureadvancedDifficulty: advanced430 XP~65 min6 checksGIS ArchitectureadvancedDifficulty: advanced43065m6
You hand in a set of design decisions.
Dataset
Global M5.5+ earthquakes, Jan–Mar 2025 · Point · 86 features · EPSG:4326
What you’ll do
Size the cost of browser fan-out against the measured snapshot
Choose a shared ingestion and overview delivery pattern
Separate global summary from per-event detail
system designUSGSGeoJSON feedcacheevent revisionsglobalAlso trains Web GIS, Data Management
Open problem
Not started, Design the searchable imagery archiveGeospatial systemsDecisions
Choose a search, storage, preview and revision pattern for an imagery service with reproducible results.
GIS ArchitectureadvancedDifficulty: advanced460 XP~70 min5 checksGIS ArchitectureadvancedDifficulty: advanced46070m5
You hand in a set of design decisions.
Dataset
Greater London, Sentinel-2 red and NIR, 11 July 2025 · Raster · EPSG:32630
What you’ll do
Separate scene discovery from pixel storage and map rendering
Select an access pattern suited to small viewport reads and flexible band expressions
Preserve exact-version provenance through corrections
system designSTACcloud optimized GeoTIFFraster tilesprovenanceAlso trains Remote Sensing, Data Management, Web GIS
Open problem
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 checksPythonadvancedDifficulty: advanced32055m5
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
Not started, Mean NDVI per borough, across a projection boundaryRaster analysisGeoJSON
Zonal statistics where the raster is in UTM and the polygons are in WGS 84: reproject the right layer, compute the index per borough, and hand back a map.
Remote SensingadvancedDifficulty: advanced300 XP~50 min7 checksRemote SensingadvancedDifficulty: advanced30050m7
You hand in a GeoJSON result.
Datasets
Greater London, Sentinel-2 red and NIR, 11 July 2025 · Raster · EPSG:32630
London boroughs · Polygon · 33 features · EPSG:4326
What you’ll do
Recognise a CRS mismatch between a raster and a vector layer
Reproject the vector layer rather than resample the raster
Compute a per-zone mean of a derived index
NDVIzonal statisticsCRSUTMSentinel-2LondonAlso trains Spatial Analysis, Data Management
Open problem
Not started, Model event and airfield condition checksGeospatial systemsSchema
Design a PostGIS schema that keeps earthquake events, airfields and repeated condition checks traceable.
Data ManagementadvancedDifficulty: advanced520 XP~85 min12 checksData ManagementadvancedDifficulty: advanced52085m12
You hand in a database schema (DDL).
What you’ll do
Model stable event and airfield identities with timestamped condition observations
Declare point type and WGS 84 SRID at the database boundary
Build spatial and chronological indexes that support the response dashboard
projectPostGISschemadata engineeringemergency responseAlso trains PostGIS / SQL, GIS Architecture
Open problem
Not started, Plan a cycle redistribution shiftProjectDecision support3 steps
Classify the dock snapshot, propose bounded bike moves, and size the resulting shift with its unserved stations visible.
Spatial AnalysisadvancedDifficulty: advanced600 XP~100 min11 checksSpatial AnalysisadvancedDifficulty: advanced600100m11
Worked in 3 steps, each checked before the next one opens.
Classify the snapshot · SQL
Map feasible transfers · GeoJSON
Size the preliminary shift · Answers
Dataset
Santander Cycles docking stations (live snapshot) · Point · 799 features · EPSG:4326
What you’ll do
Classify full and empty active stations in SQL
Build a bounded nearest-source transfer map
Size a shift and report unserved empties from the same rules
nearest neighbouroperationscapacityCRStransportLondonAlso trains Data Management, GIS Architecture
Open project
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 checksData ManagementadvancedDifficulty: advanced37055m6
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
Not started, Screen capital access exceptionsDecision supportGeoJSON
Use airport and port proximity to flag capitals that need direct logistics verification.
Spatial AnalysisadvancedDifficulty: advanced580 XP~100 min6 checksSpatial AnalysisadvancedDifficulty: advanced580100m6
You hand in a GeoJSON result.
Datasets
Populated places · Point · 1,251 features · EPSG:4326
World airports · Point · 893 features · EPSG:4326
Ports · Point · 1,081 features · EPSG:4326
What you’ll do
Compute nearest-neighbour distances from capitals to two facility layers, geodesically
Apply an ordered rule set to derive a category
Return the exceptions with the distances that justify them
nearest neighbourgeodesicclassificationlogisticsglobalAlso trains Data Management
Open problem
Not started, Screen Newham’s greening gridProjectRaster analysis3 steps
Audit a real land-cover chip, deliver a measured grid file, and identify cells for field verification.
Remote SensingadvancedDifficulty: advanced600 XP~100 min10 checksRemote SensingadvancedDifficulty: advanced600100m10
Worked in 3 steps, each checked before the next one opens.
Audit the class chip · Answers
Hand over the measured grid · Dataset file
Map field-verification cells · GeoJSON
Datasets
Newham WorldCover 2021 class chip · Raster · EPSG:4326
London boroughs · Polygon · 33 features · EPSG:4326
What you’ll do
Audit class counts in the clipped raster
Prepare a traceable borough grid as an uploaded GIS file
Return only cells that meet a stated greening screen
NewhamWorldCoverurban greeningoffline rasterAlso trains Data Management, Spatial Analysis
Open project
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 checksCartographyadvancedDifficulty: advanced50085m7
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
Not started, Which big cities does the gazetteer not know?Data qualityGeoJSON
Test one layer's completeness against another: large urban footprints with no populated place inside them at all.
Data ManagementadvancedDifficulty: advanced300 XP~45 min5 checksData ManagementadvancedDifficulty: advanced30045m5
You hand in a GeoJSON result.
Datasets
Urban areas · Polygon · 2,143 features · EPSG:4326
Populated places · Point · 1,251 features · EPSG:4326
What you’ll do
Measure footprint area in an equal-area projection and apply a size floor
Test each footprint for containment of any point from a second layer
Return the uncovered footprints with the area that says how much they matter
completenessspatial joinequal-areagazetteerglobalAlso trains Spatial Analysis
Open problem
Not started, Which metros straddle an international border?Spatial analysisGeoJSON
Overlay 2,143 urban footprints on 241 countries and keep the ones with real built-up area on both sides of a line.
Spatial AnalysisadvancedDifficulty: advanced320 XP~50 min5 checksSpatial AnalysisadvancedDifficulty: advanced32050m5
You hand in a GeoJSON result.
Datasets
Urban areas · Polygon · 2,143 features · EPSG:4326
Countries · MultiPolygon · 241 features · EPSG:4326
What you’ll do
Overlay a footprint layer on a boundary layer
Measure the pieces in an equal-area projection and apply a minimum
Aggregate pieces back to the footprint and keep the multi-country ones
overlayequal-areaaggregationbordersglobalAlso trains Data Management
Open problem
Not started, Which neighborhoods merit a service follow-up?Decision supportSQL
Join geocoded service requests to neighborhood polygons and map a review share only where the sample supports it.
PostGIS / SQLadvancedDifficulty: advanced390 XP~65 min8 checksPostGIS / SQLadvancedDifficulty: advanced39065m8
You hand in a spatial SQL query.
Datasets
2020 Neighborhood Tabulation Areas · MultiPolygon · 262 features · EPSG:4326
NYC 311 sewer requests, 1–7 June 2025 · Point · 408 features · EPSG:4326
What you’ll do
Join incident locations to neighborhoods with a boundary-inclusive predicate
Compute elapsed-time review share with a clear denominator
Suppress very small denominator areas before mapping percentages
NYC 311PostGISspatial joinservice operationsgraduated mapAlso trains Spatial Analysis, Cartography, Data Management
Open problem
Not started, River kilometres per country, measured on the ellipsoidSpatial analysisPython
Clip the river centrelines to the country polygons and measure each piece geodesically — no projection is right for a layer that spans the planet.
PythonexpertDifficulty: expert400 XP~70 min6 checksPythonexpertDifficulty: expert40070m6
You hand in a Python script.
Datasets
Countries · MultiPolygon · 241 features · EPSG:4326
Rivers and lake centrelines · LineString · 461 features · EPSG:4326
What you’ll do
Find every river–country pair that intersects
Cut each river to the country polygon
Measure the pieces geodesically and sum per country
GeoPandaspyprojgeodesicoverlayhydrologyglobalAlso trains Spatial Analysis, Data Management
Open problem
Not started, Screen rivers for a shared-water annexSpatial analysisPython
Measure mapped river lengths by country and screen the rivers whose courses are meaningfully shared.
PythonexpertDifficulty: expert650 XP~120 min7 checksPythonexpertDifficulty: expert650120m7
You hand in a Python script.
Datasets
Rivers and lake centrelines · LineString · 461 features · EPSG:4326
Countries · MultiPolygon · 241 features · EPSG:4326
What you’ll do
Intersect every river with every country it touches and measure each piece geodesically
Aggregate the pieces per river into a count of meaningful holders and a dominance share
Assign the shared rivers, ranked by how evenly they are shared, to result
GeoPandaspyprojgeodesicoverlayhydrologyglobalAlso trains Spatial Analysis, Data Management
Open problem

That’s all 36 problems.

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