umfeld-at — context layers around a place in Austria alpha

One coordinate in, everything around it out: municipality, land-price estimate, Natura 2000 / national parks, OpenStreetMap proximity, official geographic names, legal references — and the declared land-use statistics of the cell the point falls in. Austria-wide. JSON, CORS, no key.

Cadastre stays client-side. Parcels, footprints and land use come straight from the official BEV vector tile cadastre (VTC, CC BY 4.0) — vtcseamless (open source, MIT) stitches the tiles into seamless parcel geometries in your client. You send us a point plus the parcel features you already hold and get the context layers around it back.

Start here

GET /api/v1/context?lon=15.0857&lat=47.0665
GET /api/v1/context?lon=15.0857&lat=47.0665&area_sqm=812&building_count=1
    &footprint_area_sqm=140&landuse_areas=41:140,52:672&kg=63349
GET /api/v1/ne/cells?lon=15.0857&lat=47.0665&k=1&format=json

NE cells — declared land-use statistics per H3 cell

The one layer that is about the land itself, published as statistics per hexagon instead of objects: for every H3 res-12 cell (~307 m²) the declared land-use split in nine groups (buildings, building land, arable, grassland, forest, water, traffic, alpine, other), structure cover and count, surveyed-boundary share, unit count, boundary metres per hectare and orientation; per res-10 cell (~1.5 ha) a K record with unit-size percentiles and register counts. Tokenless, keyed by H3 cell id, lon/lat or bbox; 30-byte rows, zstd chunks, immutable ETags. The observed layer — LiDAR heights, tree apices, structures, NDVI, forest loss, terrain for the same cells — is served by the sibling srtm-lidar-at (/api/v1/cells?bbox=, /api/v1/cells/{h3}, /api/v1/kg/{code}/cells; CC BY 4.0, no key). Same H3 ids, so declared and observed zip together client-side on cell_id.

GET /api/v1/ne
    # pin, limits, coverage (kgs_built), dictionary ids
GET /api/v1/ne/cells?lon=15.0857&lat=47.0665&k=1&format=json
    # the cell under a point + 1 ring
GET /api/v1/ne/cells?bbox=15.08,47.06,15.10,47.08&list=1
    # which res-9 chunks cover a viewport (+ their ETags)
GET /api/v1/ne/chunk/{h3_res9}
    # all rows of one chunk (zstd | bin | json); ETag immutable → cache 24 h
GET /api/v1/ne/cell/{h3}
    # one res-12 cell decoded, with its res-10 K record
GET /api/v1/ne/{kg}
    # whole-KG container (CC BY 4.0 product download)
GET /api/v1/context?lon=&lat=&include=ne
    # the same cell inside the context bundle
GET /api/v1/ne/stats?kg=63330
    # confirmed change over time: m² per group transition, roof area, structures

Coverage: as of 2026-10-17 04:51 UTC: 7 850 of 7 850 KGs with a declared layer (100.0 %), 3 256 with an observed layer live at srtm-lidar-at (4 more already shared with us, awaiting publication there — poll, not a gap) [peer state 04:43 UTC]; 278 326 942 res-12 cells in 1 040 061 res-9 chunks. It grows by submission — a KG appears the moment its cells land in the store, declared layer here, observed layer from srtm-lidar-at (/api/v1/ne/manifest → status per KG; an unbuilt KG answers 404 + Retry-After, a bbox touching one is partial, never "no cells"). Record layouts, decode snippets and the playbook: llm.txt § NE cells · contract: /api/v1/docs/ne.md. Attribution: © BEV (CC BY 4.0), bearbeitet · observed layer © srtm-lidar-at (CC BY 4.0).

Declared layer digested by peers — land area whose declared (survey) cells a peer re-digested from the BEV tiles, per day (res-10 chunks, ~1.5 ha each). Each bar is split by how often that land had been digested up to then — first digest on top, 2nd, 3rd–4th, 5th–9th, 10th+ pass below; only land seen before can show change, and the deeper the pass, the longer its history. The observed layer (satellite & LiDAR, srtm-lidar-at) is a separate measurement: it is not in the bars, each day's card lists it on its own line.

Documentation

Full reference (plain text, for humans and LLM agents) · NE cells contract · Licences & attribution per source (json) · Caching policy · Feedback

Every response carries meta.license and an X-Data-Attribution header naming its own source; obligations differ (CC BY 4.0, EEA, WDPA non-commercial, ODbL). Datenquelle: STATISTIK AUSTRIA · BEV – Geographische Namen (DLM) · © BEV (CC BY 4.0), bearbeitet · EEA Natura 2000 · UNEP-WCMC & IUCN WDPA · © OpenStreetMap contributors · RIS, Bundeskanzleramt. Not operated by or affiliated with Statistik Austria, BEV, EEA, UNEP-WCMC, OpenStreetMap or the Bundeskanzleramt. Stage: alpha — field names and limits may still move between epochs.