Add OSM building footprint fetcher to exposure module#9
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New exposure/osm.py: get_osm_buildings(lat, lon, buffer_deg, ...) -> BuildingCollection. Queries the Overpass API for OSM way["building"] elements inside the bbox and returns each as a BuildingFootprint with its (lat, lon) polygon, area in m^2, OSM id, and tags. Models added to exposure/models.py: - BuildingFootprint (frozen dataclass; immutable polygon and tags) - BuildingCollection (sequence + total_area_m2 helper) Polygon area uses a local equirectangular projection with a cos(lat) factor at the polygon centroid. Building-scale polygons see sub-0.1% error from this approximation, well below the noise of OSM source data. A public `parse_overpass_response(payload)` helper lets tests load a saved Overpass JSON without touching the network. The committed tests/fixtures/robit_bata_osm.json (32 KB, 35 buildings) drives the offline tests; one integration test queries Overpass live for central Vaduz to exercise the full network path. Implemented with stdlib only (urllib + json + math) — no new dependency on osmnx, geopandas, or shapely.
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Summary
exposure/osm.py:get_osm_buildings(lat, lon, buffer_deg, ...) -> BuildingCollection. Queries the Overpass API for OSMway["building"]elements inside the bbox.exposure/models.py:BuildingFootprint(frozen; immutable polygon and tags)BuildingCollection(sequence +total_area_m2()helper)parse_overpass_response(payload)lets tests load saved JSON without touching the network.Notable: stdlib-only
Implemented with
urllib,json,math— no new dependency onosmnx,geopandas, orshapely. If we later need vector ops (rasterize / spatial joins for damage estimation against HAND), we'll addgeopandasthen.Test plan
len > 10so OSM edits don't break it.Pipeline progress