Spatial Agreement of Burned Area Products Derived from Very High to Coarse-Resolution Satellite Imagery in African Biomes

Satellite data provide the spatial distributions of burned areas worldwide; assessing their accuracy and comparing burned area estimates from different products is relevant to gain insights into their reliability and sources of error. We compared BA maps derived from multispectral satellite data with different spatial resolutions, ranging from Planet (3 m) to Sentinel-2 (S2, 10–20 m), Sentinel-3 (S3, 300 m), and MODIS (250–500 m), over selected African sites for the year 2019. Planet and S2 images were processed to derive BA maps with a supervised Random Forest algorithm and used to assess the spatial agreement of the FireCCISFD20, FireCCI51, FireCCIS311, and MCD64A1 products by computing omission and commission errors, Dice Coefficient, and Relative bias. The products based on S2 images showed the greatest agreement with the very high-resolution Planet BA maps (overall Dice Coefficient was found to be greater than 80%). The coarse-resolution products showed a lower spatial agreement with reference perimeters. Among the coarse spatial resolution products, FireCCIS311 was found to outperform the others. The spatial resolution of satellite data was found to be influential on accuracy, with the omission error greater than the commission (RelB < 0) for coarser resolution BA products. The spatial patterns of burns and the vegetation type were found to be significant in the mapping accuracy, and BA detection in Sahelian savannas was found to be more accurate. This study provides insights into the variability of the spatial accuracy of different burned area products derived from very high- to coarse-resolution satellite imagery.

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Journal
Fire
Published
2025-03-26
DOI
https://doi.org/10.3390/fire8040126
Primary Topic
Fire effects on ecosystems
Type
article
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article

Spatial Agreement of Burned Area Products Derived from Very High to Coarse-Resolution Satellite Imagery in African Biomes

Giovanna Sona, Magí Franquesa, Daniela Stroppiana, Pietro Alessandro Brivio et al.
22 links
Fire
Fire effects on ecosystems
article

Spatial Agreement of Burned Area Products Derived from Very High to Coarse-Resolution Satellite Imagery in African Biomes

Giovanna Sona, Magí Franquesa, Daniela Stroppiana, Pietro Alessandro Brivio, M. Lucrecia Pettinari, Matteo Sali, Emilio Chuvieco
article en

Abstract

Satellite data provide the spatial distributions of burned areas worldwide; assessing their accuracy and comparing burned area estimates from different products is relevant to gain insights into their reliability and sources of error. We compared BA maps derived from multispectral satellite data with different spatial resolutions, ranging from Planet (3 m) to Sentinel-2 (S2, 10–20 m), Sentinel-3 (S3, 300 m), and MODIS (250–500 m), over selected African sites for the year 2019. Planet and S2 images were processed to derive BA maps with a supervised Random Forest algorithm and used to assess the spatial agreement of the FireCCISFD20, FireCCI51, FireCCIS311, and MCD64A1 products by computing omission and commission errors, Dice Coefficient, and Relative bias. The products based on S2 images showed the greatest agreement with the very high-resolution Planet BA maps (overall Dice Coefficient was found to be greater than 80%). The coarse-resolution products showed a lower spatial agreement with reference perimeters. Among the coarse spatial resolution products, FireCCIS311 was found to outperform the others. The spatial resolution of satellite data was found to be influential on accuracy, with the omission error greater than the commission (RelB < 0) for coarser resolution BA products. The spatial patterns of burns and the vegetation type were found to be significant in the mapping accuracy, and BA detection in Sahelian savannas was found to be more accurate. This study provides insights into the variability of the spatial accuracy of different burned area products derived from very high- to coarse-resolution satellite imagery.

FireVol. 8(4)
University of Milan (IT), Universidad de Alcalá (ES), Istituto per il Rilevamento Elettromagnetico dell'Ambiente (IT), Instituto Pirenaico de Ecología (ES), University of Milano-Bicocca (IT)
Openalex Percentile: Top 93%
Fire effects on ecosystems
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