A Spatiotemporal Recommendation Engine for Prescribed Burning in the Southeast US

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Many ecosystems in the Southeast US are dependent upon frequent low-intensity surface fires to sustain native biodiversity, ecosystem services, and endangered species populations. Successful application of prescribed fire in this region requires careful planning and assessment of the risks and tradeoffs involved when deciding whether or not to conduct a burn. Many of these risks are closely tied to ambient environmental conditions and are reflected in sets of ‘prescription’ parameters that define safe and effective operating conditions to meet objectives or regulatory requirements. 

To facilitate effective decision making and acknowledging growing uncertainties related to climate change effects on wildland fire operations, we developed a spatiotemporal recommendation engine to identify near-term optimal burning opportunities for prescribed fire implementation. The initial iteration of the recommendation engine is demonstrated through a case study of short-term meteorological conditions for Eglin Air Force Base, located in Florida, USA.