Datasets:
fire_id int64 1 39.9M | xi int64 0 5 | yi int64 0 4 | lon float64 -162.85 175 | lat float64 -42.54 71.4 | dt timestamp[s]date 2018-01-01 00:00:00 2023-09-09 00:00:00 | img_size int64 256 256 | idx int64 0 16.4k | fire_type int64 0 2 | region_id int64 1 10 | num_fire int64 10 208k |
|---|---|---|---|---|---|---|---|---|---|---|
52,815 | 0 | 0 | 8.689139 | 53.138026 | 2018-03-18T00:00:00 | 256 | 861 | 1 | 1 | 1,722 |
10,181,375 | 0 | 0 | 16.113681 | 51.18083 | 2018-03-25T00:00:00 | 256 | 1,132 | 0 | 1 | 20 |
2,168,898 | 0 | 0 | -0.541008 | 38.376527 | 2018-04-08T00:00:00 | 256 | 1,638 | 1 | 1 | 68 |
10,181,375 | 0 | 0 | 16.113681 | 51.18083 | 2018-04-08T00:00:00 | 256 | 1,652 | 0 | 1 | 20 |
6,503,793 | 0 | 0 | 8.062567 | 51.766978 | 2018-04-08T00:00:00 | 256 | 1,662 | 0 | 1 | 49 |
708,411 | 0 | 0 | 15.985672 | 51.689499 | 2018-04-08T00:00:00 | 256 | 1,673 | 1 | 1 | 544 |
10,181,375 | 0 | 0 | 16.113681 | 51.18083 | 2018-04-09T00:00:00 | 256 | 1,705 | 0 | 1 | 20 |
7,133,120 | 0 | 0 | 6.058211 | 48.886768 | 2018-04-09T00:00:00 | 256 | 1,747 | 0 | 1 | 27 |
398,135 | 0 | 0 | 6.745419 | 49.355013 | 2018-04-11T00:00:00 | 256 | 1,819 | 1 | 1 | 1,020 |
191,888 | 0 | 0 | 9.979339 | 57.062522 | 2018-04-12T00:00:00 | 256 | 1,906 | 1 | 1 | 577 |
708,411 | 0 | 0 | 15.985672 | 51.689499 | 2018-04-14T00:00:00 | 256 | 2,123 | 1 | 1 | 544 |
560,136 | 0 | 0 | -5.839921 | 43.547431 | 2018-04-17T00:00:00 | 256 | 2,260 | 1 | 1 | 108 |
5,006,347 | 0 | 0 | 2.11687 | 50.699111 | 2018-04-17T00:00:00 | 256 | 2,261 | 0 | 1 | 16 |
13,393,451 | 0 | 0 | 1.76316 | 48.987828 | 2018-04-17T00:00:00 | 256 | 2,267 | 0 | 1 | 23 |
1,075,210 | 0 | 0 | 5.694395 | 50.823751 | 2018-04-18T00:00:00 | 256 | 2,272 | 1 | 1 | 50 |
5,006,347 | 0 | 0 | 2.11687 | 50.699111 | 2018-04-18T00:00:00 | 256 | 2,290 | 0 | 1 | 16 |
736,422 | 0 | 0 | 8.268056 | 47.071056 | 2018-04-18T00:00:00 | 256 | 2,293 | 1 | 1 | 155 |
6,503,793 | 0 | 0 | 8.062567 | 51.766978 | 2018-04-18T00:00:00 | 256 | 2,298 | 0 | 1 | 49 |
13,393,451 | 0 | 0 | 1.76316 | 48.987828 | 2018-04-18T00:00:00 | 256 | 2,303 | 0 | 1 | 23 |
708,411 | 0 | 0 | 15.985672 | 51.689499 | 2018-04-18T00:00:00 | 256 | 2,306 | 1 | 1 | 544 |
14,690,423 | 0 | 0 | -3.727767 | 43.143191 | 2018-04-19T00:00:00 | 256 | 2,310 | 0 | 1 | 10 |
2,886,012 | 0 | 0 | 8.049093 | 52.211642 | 2018-04-19T00:00:00 | 256 | 2,313 | 1 | 1 | 105 |
989,760 | 0 | 0 | -1.750359 | 53.340146 | 2018-04-19T00:00:00 | 256 | 2,320 | 1 | 1 | 38 |
3,351,196 | 0 | 0 | 8.338798 | 51.598545 | 2018-04-19T00:00:00 | 256 | 2,321 | 1 | 1 | 70 |
5,006,347 | 0 | 0 | 2.11687 | 50.699111 | 2018-04-19T00:00:00 | 256 | 2,326 | 0 | 1 | 16 |
228,604 | 0 | 0 | 5.684289 | 48.718335 | 2018-04-19T00:00:00 | 256 | 2,329 | 0 | 1 | 11 |
410,992 | 0 | 0 | -0.241197 | 53.643326 | 2018-04-19T00:00:00 | 256 | 2,330 | 1 | 1 | 97 |
6,503,793 | 0 | 0 | 8.062567 | 51.766978 | 2018-04-19T00:00:00 | 256 | 2,331 | 0 | 1 | 49 |
11,353,809 | 0 | 0 | 0.543703 | 40.579635 | 2018-04-19T00:00:00 | 256 | 2,334 | 0 | 1 | 20 |
7,133,120 | 0 | 0 | 6.058211 | 48.886768 | 2018-04-19T00:00:00 | 256 | 2,337 | 0 | 1 | 27 |
24,598,659 | 0 | 0 | 21.466493 | 42.018056 | 2018-04-20T00:00:00 | 256 | 2,338 | 1 | 1 | 14 |
5,006,347 | 0 | 0 | 2.11687 | 50.699111 | 2018-04-20T00:00:00 | 256 | 2,348 | 0 | 1 | 16 |
11,099,243 | 0 | 0 | 21.01846 | 41.007456 | 2018-04-20T00:00:00 | 256 | 2,350 | 0 | 1 | 13 |
4,046,054 | 0 | 0 | 12.185816 | 47.79532 | 2018-04-20T00:00:00 | 256 | 2,352 | 1 | 1 | 21 |
95,464 | 0 | 0 | 21.941475 | 41.438645 | 2018-04-20T00:00:00 | 256 | 2,353 | 1 | 1 | 2,318 |
228,604 | 0 | 0 | 5.684289 | 48.718335 | 2018-04-20T00:00:00 | 256 | 2,354 | 0 | 1 | 11 |
6,503,793 | 0 | 0 | 8.062567 | 51.766978 | 2018-04-20T00:00:00 | 256 | 2,355 | 0 | 1 | 49 |
11,353,809 | 0 | 0 | 0.543703 | 40.579635 | 2018-04-20T00:00:00 | 256 | 2,362 | 0 | 1 | 20 |
3,849,975 | 0 | 0 | -8.686444 | 52.6462 | 2018-04-20T00:00:00 | 256 | 2,363 | 0 | 1 | 29 |
2,619,687 | 0 | 0 | 16.682986 | 43.958408 | 2018-04-22T00:00:00 | 256 | 2,415 | 0 | 1 | 18 |
12,171 | 0 | 0 | 6.721838 | 51.48401 | 2018-04-22T00:00:00 | 256 | 2,445 | 1 | 1 | 13,538 |
2,619,687 | 0 | 0 | 16.682986 | 43.958408 | 2018-04-23T00:00:00 | 256 | 2,461 | 0 | 1 | 18 |
2,245,274 | 0 | 0 | 11.026994 | 49.772727 | 2018-04-25T00:00:00 | 256 | 2,563 | 0 | 1 | 14 |
162,805 | 0 | 0 | 21.287954 | 64.665604 | 2018-04-25T00:00:00 | 256 | 2,579 | 1 | 1 | 405 |
17,407 | 0 | 0 | -8.332734 | 41.741825 | 2018-04-25T00:00:00 | 256 | 2,581 | 0 | 1 | 16 |
11,791 | 0 | 0 | 9.945652 | 45.150916 | 2018-04-25T00:00:00 | 256 | 2,599 | 1 | 1 | 446 |
7,133,120 | 0 | 0 | 6.058211 | 48.886768 | 2018-04-25T00:00:00 | 256 | 2,613 | 0 | 1 | 27 |
18,260,581 | 0 | 0 | 12.768595 | 42.186489 | 2018-04-26T00:00:00 | 256 | 2,635 | 0 | 1 | 19 |
3,320,854 | 0 | 0 | 5.674183 | 50.766484 | 2018-04-26T00:00:00 | 256 | 2,650 | 1 | 1 | 71 |
2,190,453 | 0 | 0 | 20.250404 | 42.018056 | 2018-04-26T00:00:00 | 256 | 2,656 | 0 | 1 | 14 |
9,928,981 | 0 | 0 | 11.94664 | 45.390092 | 2018-04-28T00:00:00 | 256 | 2,737 | 1 | 1 | 39 |
95,464 | 0 | 0 | 21.941475 | 41.438645 | 2018-04-30T00:00:00 | 256 | 2,844 | 1 | 1 | 2,318 |
1,452,802 | 0 | 0 | 17.195023 | 48.458947 | 2018-05-04T00:00:00 | 256 | 3,030 | 1 | 1 | 139 |
6,503,793 | 0 | 0 | 8.062567 | 51.766978 | 2018-05-04T00:00:00 | 256 | 3,043 | 0 | 1 | 49 |
1,054,992 | 0 | 0 | 5.957151 | 49.506603 | 2018-05-05T00:00:00 | 256 | 3,072 | 1 | 1 | 280 |
2,666,853 | 0 | 0 | 5.367634 | 50.571101 | 2018-05-05T00:00:00 | 256 | 3,075 | 1 | 1 | 62 |
2,245,274 | 0 | 0 | 11.026994 | 49.772727 | 2018-05-05T00:00:00 | 256 | 3,082 | 0 | 1 | 14 |
398,135 | 0 | 0 | 6.745419 | 49.355013 | 2018-05-05T00:00:00 | 256 | 3,084 | 1 | 1 | 1,020 |
5,813,172 | 0 | 0 | -1.487603 | 41.479069 | 2018-05-05T00:00:00 | 256 | 3,092 | 1 | 1 | 35 |
2,313,182 | 0 | 0 | 9.736795 | 48.371362 | 2018-05-05T00:00:00 | 256 | 3,094 | 1 | 1 | 43 |
539,626 | 0 | 0 | 9.905228 | 53.525422 | 2018-05-05T00:00:00 | 256 | 3,096 | 1 | 1 | 380 |
5,098,708 | 0 | 0 | 2.153926 | 56.493218 | 2018-05-05T00:00:00 | 256 | 3,100 | 1 | 1 | 80 |
228,604 | 0 | 0 | 5.684289 | 48.718335 | 2018-05-05T00:00:00 | 256 | 3,101 | 0 | 1 | 11 |
6,503,793 | 0 | 0 | 8.062567 | 51.766978 | 2018-05-05T00:00:00 | 256 | 3,107 | 0 | 1 | 49 |
36,443 | 0 | 0 | -0.601644 | 53.579321 | 2018-05-05T00:00:00 | 256 | 3,117 | 1 | 1 | 1,969 |
11,353,809 | 0 | 0 | 0.543703 | 40.579635 | 2018-05-05T00:00:00 | 256 | 3,120 | 0 | 1 | 20 |
5,641,946 | 0 | 0 | 15.857663 | 52.716942 | 2018-05-05T00:00:00 | 256 | 3,121 | 0 | 1 | 12 |
3,849,975 | 0 | 0 | -8.686444 | 52.6462 | 2018-05-05T00:00:00 | 256 | 3,122 | 0 | 1 | 29 |
2,245,274 | 0 | 0 | 11.026994 | 49.772727 | 2018-05-06T00:00:00 | 256 | 3,136 | 0 | 1 | 14 |
470,024 | 0 | 0 | 10.700234 | 48.778971 | 2018-05-06T00:00:00 | 256 | 3,142 | 1 | 1 | 219 |
6,503,793 | 0 | 0 | 8.062567 | 51.766978 | 2018-05-06T00:00:00 | 256 | 3,151 | 0 | 1 | 49 |
4,439,444 | 0 | 0 | -8.251886 | 41.802461 | 2018-05-06T00:00:00 | 256 | 3,152 | 0 | 1 | 10 |
13,393,451 | 0 | 0 | 1.76316 | 48.987828 | 2018-05-06T00:00:00 | 256 | 3,156 | 0 | 1 | 23 |
52,815 | 0 | 0 | 8.689139 | 53.138026 | 2018-05-06T00:00:00 | 256 | 3,158 | 1 | 1 | 1,722 |
11,353,809 | 0 | 0 | 0.543703 | 40.579635 | 2018-05-06T00:00:00 | 256 | 3,163 | 0 | 1 | 20 |
190,464 | 0 | 0 | 24.181639 | 65.770526 | 2018-05-07T00:00:00 | 256 | 3,168 | 1 | 1 | 999 |
6,503,793 | 0 | 0 | 8.062567 | 51.766978 | 2018-05-07T00:00:00 | 256 | 3,185 | 0 | 1 | 49 |
5,455,467 | 0 | 0 | 5.141933 | 51.23136 | 2018-05-07T00:00:00 | 256 | 3,191 | 1 | 1 | 24 |
12,171 | 0 | 0 | 6.721838 | 51.48401 | 2018-05-07T00:00:00 | 256 | 3,197 | 1 | 1 | 13,538 |
1,075,210 | 0 | 0 | 5.694395 | 50.823751 | 2018-05-08T00:00:00 | 256 | 3,199 | 1 | 1 | 50 |
553,149 | 0 | 0 | 6.971119 | 51.521065 | 2018-05-08T00:00:00 | 256 | 3,208 | 1 | 1 | 119 |
76,258 | 0 | 0 | 6.849847 | 49.247215 | 2018-05-08T00:00:00 | 256 | 3,211 | 1 | 1 | 515 |
2,245,274 | 0 | 0 | 11.026994 | 49.772727 | 2018-05-08T00:00:00 | 256 | 3,215 | 0 | 1 | 14 |
470,024 | 0 | 0 | 10.700234 | 48.778971 | 2018-05-08T00:00:00 | 256 | 3,225 | 1 | 1 | 219 |
3,320,854 | 0 | 0 | 5.674183 | 50.766484 | 2018-05-08T00:00:00 | 256 | 3,226 | 1 | 1 | 71 |
275,530 | 0 | 0 | 7.011543 | 51.298733 | 2018-05-08T00:00:00 | 256 | 3,228 | 1 | 1 | 323 |
6,503,793 | 0 | 0 | 8.062567 | 51.766978 | 2018-05-08T00:00:00 | 256 | 3,233 | 0 | 1 | 49 |
8,349,548 | 0 | 0 | 2.11687 | 50.699111 | 2018-05-08T00:00:00 | 256 | 3,244 | 0 | 1 | 22 |
3,351,196 | 0 | 0 | 8.338798 | 51.598545 | 2018-05-09T00:00:00 | 256 | 3,265 | 1 | 1 | 70 |
6,503,793 | 0 | 0 | 8.062567 | 51.766978 | 2018-05-09T00:00:00 | 256 | 3,284 | 0 | 1 | 49 |
972,278 | 0 | 0 | 7.321461 | 52.471029 | 2018-05-09T00:00:00 | 256 | 3,287 | 1 | 1 | 86 |
52,815 | 0 | 0 | 8.689139 | 53.138026 | 2018-05-09T00:00:00 | 256 | 3,291 | 1 | 1 | 1,722 |
36,443 | 0 | 0 | -0.601644 | 53.579321 | 2018-05-09T00:00:00 | 256 | 3,292 | 1 | 1 | 1,969 |
8,349,548 | 0 | 0 | 2.11687 | 50.699111 | 2018-05-09T00:00:00 | 256 | 3,295 | 0 | 1 | 22 |
190,464 | 0 | 0 | 24.181639 | 65.770526 | 2018-05-10T00:00:00 | 256 | 3,298 | 1 | 1 | 999 |
809,058 | 0 | 0 | 17.131019 | 58.679483 | 2018-05-11T00:00:00 | 256 | 3,357 | 1 | 1 | 503 |
1,054,992 | 0 | 0 | 5.957151 | 49.506603 | 2018-05-11T00:00:00 | 256 | 3,369 | 1 | 1 | 280 |
190,464 | 0 | 0 | 24.181639 | 65.770526 | 2018-05-12T00:00:00 | 256 | 3,422 | 1 | 1 | 999 |
2,581,774 | 0 | 0 | 8.032249 | 51.857932 | 2018-05-15T00:00:00 | 256 | 3,617 | 1 | 1 | 18 |
11,353,809 | 0 | 0 | 0.543703 | 40.579635 | 2018-05-15T00:00:00 | 256 | 3,629 | 0 | 1 | 20 |
FireComp: Next-Day Fire Spread
Global benchmark for next-day wildfire spread prediction from 375 m VIIRS active-fire detections, with ERA5 weather, GFS forecasts and Alpha Earth terrain embeddings. 256×256 patches, 9 regions, 2017–2025.
Code, documentation, loaders and paper: https://github.com/justuskarlsson/FireComp
Paper
This dataset accompanies the FireComp paper, accepted and presented at GCPR 2026 (German Conference on Pattern Recognition). It is released so the benchmark results in that paper can be reproduced and built upon. See the GitHub repository for the citation entry.
Contents
| Path | Description |
|---|---|
next_day_v3/ |
Main dataset: 8 HDF5 shards (dataset_*.h5, zstd) + per-shard metadata (dataset_*.json), samples.json, stats.json (normalization) |
next_day_v3/splits/{train,val,test}.jsonl |
Flat sample index per split (stratified temporal 60/15/25 within each region) — what the dataset viewer shows |
next_day_v3_case_study/ |
Small case-study subset used for paper figures |
regions/ |
Region definitions (wildfire_regions.json / .tif) |
fire_areas.npz |
Per-fire spatial area lookup (fire-size stratification) |
vnp14_fires/vnp14_fires_2012.h5 |
VIIRS fire-event index, 2012–2025 (~55 GB) — see below |
vnp14_fires_2012.h5
Individual VNP14IMG active-fire detections clustered into fire events by a
spatio-temporal BFS, which is what defines the fire_id used everywhere else in
the benchmark. Not needed to train on the dataset above, but required for most of
the analysis and visualization: per-fire statistics, size/region breakdowns,
wild-vs-tame classification, fire-shape (solidity) analysis and the paper figures.
| Group | Contents |
|---|---|
stats/, stats_{10,100,1000,10000}/ |
Per-fire records (id, start_date, end_date, bbox, country, avg_xy_neighbors, ignition_ratio, …), the suffix being a minimum-detection-count filter |
pixels/ |
Every detection: fire_id, date, position, cls, ignition, image_id |
projection_by_fire/, projection_by_t/ |
Detections rasterized per fire / per timestep (projection_by_fire covers fires with ≥100 detections) |
images/, meta/ |
Source granule index and archive date range |
Usage
Clone/download into data/ of the GitHub repo and follow its README.
Reading the shards requires h5py and hdf5plugin (zstd filter).
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