ForeFire Adapter¶

Overview¶

forefire is a deterministic raster adapter that approximates simulator-style front propagation through fixed diffusion kernels.

At a Glance¶

Hazard Family

Wildfire

Public catalog grouping used for this model.

Maturity

Implemented

Catalog maturity label used on the index page.

Tasks

Spread

Benchmark Family

Wildfire Benchmark

Primary benchmark-family link used for compatible evaluation coverage.

Description¶

forefire is a deterministic raster adapter that approximates simulator-style front propagation through fixed diffusion kernels.

PyHazards exposes it as a benchmarkable baseline through the standard model registry.

Benchmark Compatibility¶

Primary benchmark family: Wildfire Benchmark

Mapped benchmark ecosystems: WildfireSpreadTS

External References¶

Paper: ForeFire: A Modular, Scriptable C++ Simulation Engine and Library for Wildland-Fire Spread | Repo: Repository

Registry Name¶

Primary entrypoint: forefire

Supported Tasks¶

Spread

Programmatic Use¶

import torch
from pyhazards.models import build_model

model = build_model(name="forefire", task="segmentation", in_channels=12)
logits = model(torch.randn(2, 12, 16, 16))
print(logits.shape)

Notes¶

This adapter is deterministic and does not learn parameters during the smoke test.