Wildfire Ignition Probability
Natural - Southeastern Region
Probability of naturally caused wildfire ignitions across the southeastern United States.
About this dataset
Wildfire ignition probability data provides spatially explicit estimates of the likelihood that a wildfire will start in a given location. The resulting datasets, specific to the Western and Southeastern U.S. regions, offer geospatial estimates of wildfire ignition probabilities, distinguishing between human-caused and natural (lightning) ignitions, as well as providing combined probabilities for both. The authors employ Random Forest machine learning, customized for probabilistic predictions, to model ignition likelihood based on spatial trends in observed fire occurrences, topographic features, climatic factors, vegetation characteristics, and human development patterns. The resulting datasets are scaled to recent observed ignition rates (e.g. 2006-2020 fire occurrence database) and have a spatial resolution of 120 meters. These datasets are a valuable resource for wildfire risk assessments (QWRA), risk mitigation planning, and decision support in land management, policy development, and other fire-related contexts.
What’s included in this dataset
How to interpret this layer
The wildfire ignition probability analysis produced three primary spatial datasets for both the western and southeastern US. These datasets are available in the following formats:
- GeoTIFF (Albers Projection): This format is ideal for detailed GIS analysis within the continental United States as it preserves area measurements accurately.
- Cloud-Optimized GeoTIFF (Albers Projection): This format is optimized for cloud-based analysis, web performance, and working with large datasets.
- Cloud-Optimized GeoTIFF (Mercator Projection): This format is specifically designed for web mapping applications.
All datasets have a 120-meter pixel resolution with probability values ranging from 0 (very low likelihood) to a theoretical maximum of 1 (very high likelihood). However, it's important to note that in practice, the likelihood of a wildfire starting in any given pixel is quite low. Even in high-risk areas, the highest observed probability is around 0.0004, meaning a probability of 1, while theoretically possible, is extremely unlikely. All datasets are calibrated to match observed annual wildfire ignition rates from 2006-2020.
As described above, the datasets encompass three types of ignition probabilities:
- Human Ignition Probability: Indicates the likelihood of human-caused wildfire ignition.
- Natural Ignition Probability: Indicates the likelihood of lightning-caused wildfire ignition.
- Composite Ignition Probability: Represents the combined likelihood of wildfire ignition from both human and natural causes.
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Wildfire Ignition Probability
Probability of naturally caused wildfire ignitions across the southeastern United States.
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Licensing & Attribution
Licensed under Creative Commons Attribution–NonCommercial–ShareAlike 4.0 International (CC BY-NC-SA 4.0).
You may share and adapt this dataset for noncommercial purposes with attribution under the same license.
Required Attribution:
© 2025 Pyrologix, a Vibrant Planet company. Distributed by Vibrant Planet Data Commons. Licensed under CC BY-NC-SA 4.0.
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