Problems
Real geospatial problems, graded automatically. Choose a track, a level and what you want to hand in.
- Not started, Build the global seismic reconnaissance watchlistDecision supportPythonSpatial AnalysisintermediateDifficulty: intermediate240 XP~40 min5 checksSpatial AnalysisintermediateDifficulty: intermediate
Turn a fixed USGS event feed into a mapped, reproducible shallow strong-event watchlist for requesting impact products.
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, CartographyOpen problem - Not started, Where should the sewer service desk review closure lag?Decision supportPythonSpatial AnalysisintermediateDifficulty: intermediate320 XP~50 min5 checksSpatial AnalysisintermediateDifficulty: intermediate
Turn a fixed 311 complaint cohort into a map of requests open longer than an analyst-defined day.
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 ManagementOpen problem - Not started, Build an earthquake contact reconnaissance queueProjectDecision support3 stepsSpatial AnalysisadvancedDifficulty: advanced550 XP~95 min12 checksSpatial AnalysisadvancedDifficulty: advanced
Screen strong shallow events, quantify airfield and settlement proximity, and hand over a traceable contact map.
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, CartographyOpen project