Refining historical burned area data from satellite observations

Details

Ressource 1Download: Fernandez-Garcia & Kull 2023 IJAEOG.pdf (7598.87 [Ko])
State: Public
Version: Final published version
License: CC BY 4.0
Serval ID
serval:BIB_719D26D062FE
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Refining historical burned area data from satellite observations
Journal
International Journal of Applied Earth Observation and Geoinformation
Author(s)
Fernández-García Víctor, Kull Christian A.
ISSN
1569-8432
Publication state
Published
Issued date
06/2023
Peer-reviewed
Oui
Volume
120
Pages
103350
Language
english
Abstract
• The burned area reported by global satellite products is largely biased.
•We aimed to correct burned area biases before Sentinel-2 era.
•A solution is to combine coarse resolution burned area with environmental data.
•Validations in independent sites and years demonstrate that our tool is operational.
Sentinel-2 imagery has revealed a substantial underestimation of burned area (BA) compared with earlier satellite products with coarser spatial resolution. In this context, we investigate the predictability of biases between the reference Sentinel-2 BA product developed for Sub-Saharan Africa (FireCCISFD) in 2019 and commonly used global coarse resolution BA products (MCD64, Fire CCI and C3S), providing tools to refine historical annual BA data before the Sentinel-2 era. To do so, we built a comprehensive dataset of environmental predictors of BA biases, with variables or proxies of (I) the annual BA estimated from the coarse-resolution product, (II) BA sizes, (III) the persistence and strength of BA signals, (IV) the maximum potential BA, and (V) the obstruction of land surface observation from satellites. Full and parsimonious random forest models were performed and validated through out-of-bag (OOB) estimations, and reconstructed BAs were validated with external data over space, and over time. The explained variance in BA biases was ≥78.58% (OOB) for all full and parsimonious models. The reconstructed BA data showed a high correspondence with the reference BA in the validation sites over space (≥91.15% var. explained) and time (≥90.37% var. explained), notably reducing biases of coarse resolution products. As an example of the model applicability, the spatial patterns of Madagascar’s BA were reconstructed for 2005, 2010, 2015 and 2020, revealing a burned extent between two and four times higher than previous estimations. The proposed models are operational solutions to obtain regional and global virtually unbiased BA estimates since 2000.
Keywords
Madagascar, remote sensing, Africa, fire, satellite data, wildfire, feux de brousse
Open Access
Yes
Funding(s)
Other / Swiss Network of International Studies (SNIS)
Create date
18/05/2023 9:16
Last modification date
19/05/2023 6:12
Usage data