The net benefits of human-ignited wildfire forecasting: the case of Tribal land units in the United States.

ABSTRACT: Research shows that some categories of human-ignited wildfires might be forecastable, due to their temporal clustering, with the possibility that resources could be pre-deployed to help reduce the incidence of such wildfires. We estimated several kinds of incendiary and other human-ignited wildfire forecast models at the weekly time step for tribal land units in the United States, evaluating their forecast skill out of sample. Analyses show that an Autoregressive Conditional Poisson (ACP) model of both incendiary and non-incendiary human-ignited wildfires is more accurate out of sample compared to alternatives, and the simplest of the ACP models performed the best. Additionally, an ensemble of these and simpler, less analytically intensive approaches performed even better. Wildfire hotspot

SUBMITTER: Prestemon JP 

PROVIDER: S-EPMC5535272 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature