Evaluation of low-resolution remotely sensed datasets for burned area assessment within the wildland-urban interface

Abstract

The impacts of wildfires are often intensified within the wildland-urban interface (WUI) where built structures intermingle with wildland vegetation. Because fire impacts in the WUI are high, detailed fire occurrence information is especially valuable to fire scientists and risk managers. While it is known that burned area datasets with coarse spatial resolution frequently underestimate burned area due to the omission of small fires, the extent to which they do so has not been quantified in states such as Oklahoma in the south-central United States. Here, we explore how much burned area low-resolution datasets miss, where they miss burned area, and how different datasets detect burned area within the wildland-urban interface in Oklahoma, USA. We compare the MODIS MCD64A1 burned area product, the Monitoring Trends in Burn Severity (MTBS) product and a higher-resolution dataset developed using Sentinel-2 imagery and find that the low-resolution datasets underestimate burned area by approximately 46% and were unable to detect major hotspots of fire occurrence. Overall, our study provides an estimate of the extent to which large-scale, low-resolution burned area datasets underestimate the number and distribution of small fires in Oklahoma.