Problems

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

Find a learning path

Spatial Analysis Python Clear all

Not started, Which countries have no airport in the registry?Spatial analysisPython
A points-in-polygons count as a script the grader runs: one row per country, zeros kept, on a global registry that misses a lot of places.
PythonbeginnerDifficulty: beginner150 XP~30 min4 checksPythonbeginnerDifficulty: beginner15030m4
You hand in a Python script.
Datasets
Countries · MultiPolygon · 241 features · EPSG:4326
World airports · Point · 893 features · EPSG:4326
What you’ll do
Read both layers from /data and join points to polygons with a spatial predicate
Count per country without losing the countries that count zero
Assign the finished GeoDataFrame, one row per country, to result
GeoPandasspatial joinreproducibilityaviationglobalAlso trains Spatial Analysis
Open problem
Not started, Airports per state, as a script that runs againSpatial analysisPython
Spatially join a global airport layer to US states and hand back one row per state, zeros included — in a script the grader runs.
PythonintermediateDifficulty: intermediate190 XP~35 min5 checksPythonintermediateDifficulty: intermediate19035m5
You hand in a Python script.
Datasets
United States states · Polygon · 51 features · EPSG:4326
World airports · Point · 893 features · EPSG:4326
What you’ll do
Read both layers from /data and join airports to states with a spatial predicate
Count airports and major airports per state without losing a state that has none
Assign the finished GeoDataFrame, one row per state, to the variable named result
GeoPandasspatial joinreproducibilityaviationAlso trains Spatial Analysis
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, Where are the bikes, as a share of the docks?Spatial analysisPython
A scripted per-borough ratio from a live snapshot: bikes over docking points, every borough kept, so it can run again on the next snapshot.
PythonintermediateDifficulty: intermediate190 XP~35 min5 checksPythonintermediateDifficulty: intermediate19035m5
You hand in a Python script.
Datasets
London boroughs · Polygon · 33 features · EPSG:4326
Santander Cycles docking stations (live snapshot) · Point · 799 features · EPSG:4326
What you’ll do
Read both layers from /data and assign stations to boroughs with a spatial predicate
Sum two columns per borough and compute their ratio, with zero where the denominator is zero
Assign the finished GeoDataFrame, one row per borough, to result
GeoPandasspatial joinratioreproducibilitytransportLondonAlso trains Spatial Analysis
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, 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, 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, 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