Remote Sensing · Fuel Intelligence · Australia

Annual fuel mapping
at 20m resolution

High-resolution fuel hazard, fuel load, fuel type and forest structure datasets derived from satellite and airborne remote sensing — updated annually across Australia.

Explore the Map View Datasets
forestfuelmaps.flarewildfire.app
Select catalog
Fuel Hazard
Select metric
Overall Fuel Hazard
Year
2024
Overall Fuel Hazard
LowExtreme
Live map — access required
20m
Spatial resolution
9 yrs
Annual time series
4
Dataset catalogs
15+
Derived metrics

Four catalogs. One platform.

Each catalog is derived from multi-source remote sensing data and calibrated against field observations, delivering operationally-ready inputs for fire behaviour modelling and land management.

Fuel Hazard

Fire Hazard
Classification

Six-layer hazard assessment aligned with the DSE Overall Fuel Hazard Assessment Guide (Report 82). Rated 1–5 from Low to Extreme, covering bark, elevated, near-surface and surface fuel strata.

Overall FH Surface Near-Surface Elevated Bark Combined
Fuel Load

Aboveground
Biomass Density

Total dry mass of living vegetation derived from NASA's GEDI spaceborne LiDAR Level 4A product. Expressed in tonnes per hectare and calibrated for Australian vegetation communities.

GEDI L4A t/ha 0–500 t/ha Terrain palette
Fuel Type

Bushfire Fuel
Classification

Discrete vegetation fuel type mapping using the NBIC ACS Stage 2 scheme. 40+ classes spanning closed forests, plantations, woodlands, shrublands, grasslands and WUI zones.

NBIC ACS Stage 2 40+ classes WUI zones BFC
Forest Metrics

Forest Structure
& Extent

Six structural metrics characterising canopy architecture from GEDI and optical fusion. Inputs for biodiversity assessments, carbon accounting and fire behaviour stratification.

Canopy height FPC PAI FHD Woody extent

Satellite sensors to operational maps

01
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Multi-source acquisition

Fuses data from spaceborne LiDAR (GEDI), Sentinel and Landsat optical time series, and airborne surveys to capture 3D vegetation structure annually.

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02

AlphaEarth embedding

Deep learning foundation models trained on Australian ecosystems extract structural and spectral features, enabling wall-to-wall prediction at 20m resolution.

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03

Cloud-optimised delivery

Products are served as Cloud-Optimised GeoTIFFs via a TiTiler endpoint — enabling fast, browser-based visualisation and direct GIS integration.

Ready to explore
your landscape?

Open the interactive map to browse fuel hazard, biomass and forest metrics across any region of Australia from 2017–2025.

Open Map →