---
license: other
pretty_name: WildfireIA Anonymous Benchmark Release
task_categories:
- tabular-classification
- tabular-regression
- image-classification
- other
tags:
- wildfire
- benchmark
- geospatial
- multimodal
- croissant
size_categories:
- 10K<n<100K
---

# WildfireIA Anonymous Benchmark Release

This anonymous release contains the WildfireIA benchmark data used for review.
WildfireIA is an event-level benchmark for predicting whether a reported
Natural wildfire escapes initial attack from public information available at
fire discovery time.

## Contents

- `data/canonical/raw_feature_tables/`: canonical benchmark tables. These are
  the primary dataset artifact. They contain event-level tables, source-level
  feature tables, patch-level canonical tables, labels, splits, and manifests.
- Model-ready caches are not included in this compact release; regenerate
  them deterministically from the canonical tables with `code/dataloader.py`.
- `code/`: anonymous copies of the cache generation, training, and summary
  scripts.
- `metadata/`: release manifest and cache generation commands.
- `croissant.json`: Croissant metadata with Responsible AI fields.

## Tasks

Task 1 predicts initial attack failure. The sample unit is one FPA-FOD Natural
wildfire event. Events with final size at most 10 ha are labeled 0, events with
final size at least 50 ha are labeled 1, and intermediate-size events are
excluded from the Task 1 supervised split.

Task 2 predicts remaining time-to-containment as a regression target,
`log(1 + containment_hours)`, using the same discovery-time input contract.

## Rebuilding Model-Ready Caches

The canonical tables can regenerate all official model-ready caches:

```bash
python code/dataloader.py \
  --base_dir . \
  --canonical_dir data/canonical/raw_feature_tables \
  --output_dir data/model_ready \
  --task ia_failure \
  --representation all \
  --weather_days 5 \
  --input_protocol all \
  --overwrite
```

Additional ablation caches are generated by changing `--input_protocol` and
`--weather_days`; see `metadata/cache_generation_commands.md`.

## Responsible Use

The benchmark is intended for reproducible scientific comparison and ablation
analysis. It should not be used as a standalone operational dispatch system
without agency validation. The data are public-source derived, but they include
wildfire locations, fire-station locations, roads, population density, and other
geospatial context.