Burned Area Estimation Using a New Accuracy Verification Method Based on Sentinel-2 Images

Quantifying the accuracy of burned area (BA) estimations is crucial in wildfire monitoring and loss assessment based on remote sensing technology. In this letter, a novel approach to quantitatively evaluate the accuracy of BA estimations, called the vector distance algorithm (VDA), was proposed based on boundary sampling and $t$ tests. To validate the effectiveness of this approach, Sentinel-2 images were used to estimate the BA, and a field survey and a GaoFen-6 (GF-6) image were then utilized to evaluate the accuracy based on the VDA. The results were as follows: 1) the proposed algorithm could provide not only the percent accuracy of the evaluation but also the confidence interval of the BA; 2) the accuracy validation of the BA extracted by the normalized burn ratio (NBR) index and normalized difference vegetation index (NDVI) was verified by the VDA; 3) based on the field survey, the VDA confirmed that the NBR index had high accuracy, while the NDVI index had a large error, which is consistent with the results of using ground truth observations as a reference; and 4) the analysis based on the GF-6 image showed similar results. This study indicated that the VDA is effective and has the potential for widespread use in evaluating the accuracy of a BA.