Abstract

In the absence of historical fire records, end-users intend to adopt free satellite-derived fire products, including global burn area (BA) and active fire (AF) products, to understand the historical fire dynamics for better forest management. Previous literature evaluated the accuracy of these fire products in regions with different environments, but no study evaluated the performance of these fire products in fire-prone, cloudy and mountainous areas. This study contributed to filling this gap, through the first evaluation of four broadly used fire products: MODIS-based MCD64A1, MCD14ML, VIIRS-based VNP14DLIMGTDL_NRT (hereafter simplified as VNP14DL), and ESA Fire_CCI51 over subtropical China. Two methods were applied to this end, the spatio-temporal clustering algorithm based on official historical fire records and the density-based random sampling and estimation method from the Landsat 8 fire scenes. The results show that both the AF and BA products show poor fire detection ability in this area (with all the F1-Score < 0.5). Among them, the VNP14DL performed best, followed by MCD14ML, Fire_CCI51, and MCD64A1. The MCD14ML had the best detection capability for small fires (< 50 hectares). AF products have an overall higher fire detection ability than BA products. These findings provide insights for the improvement of fire detection algorithms of these fire products in the fire-prone, cloudy and mountainous area over subtropical China.

Full Text
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