pct_land_ever_flooded< 0.004160.00416–0.030.03–0.1220.122–0.675≥ 0.675
Indonesia kabupaten flood frequency (Sentinel-1, 2025)
514 kabupaten/kota carrying what Sentinel-1 actually saw under water in 2025: 9,571.8 km² flooded at least once, 0.507% of the 1,892,816 km² it observed at all, at a mean 48.4 looks per pixel. pct_land_ever_flooded is the headline column…SelengkapnyaSembunyikan
514 kabupaten/kota carrying what Sentinel-1 actually saw under water in 2025: 9,571.8 km² flooded at least once, 0.507% of the 1,892,816 km² it observed at all, at a mean 48.4 looks per pixel. pct_land_ever_flooded is the headline column and what the card colours by; mean_flood_frequency is the column to model on; observed_coverage_pct is the column to read FIRST. Never rank on mean_flood_frequency without filtering on coverage — Kepulauan Anambas tops the national frequency table off 0.69% observed coverage, which is an exposure artefact and not a flood finding. And a low value in a dense city is not evidence of safety: Sentinel-1 sees standing open water on a 6-day revisit, so a flash flood that drains between overpasses is invisible, and layover, shadow and double-bounce off flooded walls make built-up land the worst case for SAR flood mapping. Kota Administrasi Jakarta Barat and Jakarta Timur both score 0.000% for a year whose floods were real and reported. This is a rural/peri-urban instrument and an observed-flood-extent record for one calendar year, not a flood history — it complements JRC Global Surface Water occurrence (1984–2021, 'is this ground ever water') rather than replacing it.Asal-usul data
Lisensi
ODbL-1.0 (geometry) + Copernicus (CEMS-FLOODS) (flood frequency)
Atribusi
Contains information from OpenStreetMap © OpenStreetMap contributors, available under the Open Database License (ODbL) 1.0. Flood frequency derived from the Copernicus Emergency Management Service Global Flood Monitoring (CEMS GFM) ensemble_flood_extent, 2025, obtained via the EODC STAC: Contains modified Copernicus Emergency Management Service information 2026. CEMS-FLOODS licence, https://ecds.ecmwf.int/licences/cems-floods
Tahun data
2025
Diambil pada
2026-08-05
Fitur
514
Geometri
Multi-bagian
Transformasi
Derived 2026-08-05 from the CEMS GFM ensemble_flood_extent archive for calendar 2025 — 18,001 Sentinel-1 scenes across 100 Equi7 tiles — by counting, for every 20 m pixel, the observations that scored it FLOODED and the observations that scored it at all, then aggregating both tallies to the 514-unit OSM ADM2 layer that ships beside this one. Frequency is flooded_count / valid_count and is undefined where valid_count is 0, so every share here divides by OBSERVED land and never by all land: a pixel nobody looked at is missing, not dry. Raw flood counts are deliberately not the headline — national Sentinel-1 item counts step from 11.6k (2021) to 18.0k (2025) as the constellation grows, and a count would read that growth as rising flood incidence. The temporal reduction runs in the native Equi7 grid and reprojection runs once per tile with nearest-neighbour resampling, which is the exact operation for tallies (interpolation can return flooded_count > valid_count, an impossible state) and yields frequencies identical to reprojecting all 18,001 scenes first. Pixel areas are latitude-weighted row by row on an authalic sphere (R = 6,371,007.181 m) rather than assumed square. This file is that 514-row table joined onto the shipped boundary geometry on kab_kota_name + bps_province_name — 514/514 matched, no fuzzy fallback — with the flood columns carried verbatim and kab_kota_name, kind and bps_province_name taken from boundaries/idn_adm2_osm.geojson. Rebuild it from the upstream table gfm_flood_freq_kab_2025.csv, sha256 1df4aefe2adde76956bbde091387f82e8c31291cea813e0bd999637f27e90441, and that boundary file; both are committed, so nothing here rests on a raster no one can see.
Apa yang Anda dapat
16 properti, dibaca dari 200 fitur pertama di antara 514 fitur.
kab_kota_name
Kabupaten Aceh Barat
kind
kabupaten
bps_province_name
Aceh
pct_land_ever_flooded
0.742562
flooded_km2
20.5884
mean_flood_frequency
0.00016479
observed_coverage_pct
99.9768
mean_observations
58.937
max_observations
59
expected_flooded_km2_per_look
0.45691
polygon_km2_raster
2772.653
observed_km2
2772.01
land_area_km2_boundary
2760.28
px_polygon
6942173
px_observed
6940564
px_ever_flooded
51538