Literature DB >> 35817109

Building a small fire database for Sub-Saharan Africa from Sentinel-2 high-resolution images.

Emilio Chuvieco1, Ekhi Roteta2, Matteo Sali3, Daniela Stroppiana3, Martin Boettcher4, Grit Kirches4, Thomas Storm4, Amin Khairoun5, M Lucrecia Pettinari5, Magí Franquesa5, Clément Albergel6.   

Abstract

Coarse resolution sensors are not very sensitive at detecting small fire patches, making current estimations of global burned areas (BA) very conservative. Using medium or high-resolution sensors to generate BA products becomes then a priority, particularly in areas where fires tend to be small and frequent. Building on previous work that developed a small fire dataset (SFD) for Sub-Saharan Africa for 2016, this paper presents a new version of the dataset for 2019 using the two Sentinel-2 satellites (A and B) and VIIRS active fires. Total estimated BA was 4.8 Mkm2. This value was much higher than estimations from two global, coarser-spatial resolution BA products based on MODIS data for the same area and period: 80 % greater than estimates from FireCCI51 (based on MODIS 250 m bands) and 120 % larger than MCD64A1 (based on MODIS 500 m bands). The main differences were observed in those months with higher fire occurrence (November to January for the Northern Hemisphere regions and June to September for the Southern Hemisphere ones). Accuracy assessment of the SFD product was based on a novel sampling strategy designed to obtain independent fire reference perimeters. Validation results showed remarkable high accuracy values comparing to existing global BA products. Overall omission errors (OE) were estimated as 8.5 %, commission errors (CE) as 15.0 %, with a Dice Coefficient of 87.7 %. All of these estimations implied significant improvements over the global, coarser spatial resolution BA products (OE > 50 % and CE > 20 % for the same area and period), as well as over the previous SFD product for 2016 of the same area, generated from a single Sentinel-2 satellite and MODIS active fires (OE = 26.5 % and CE = 19.3 %). Temporal accuracies greatly increased as well with the new product, with 92.5 % of fires detected within the first 10 days of occurrence.
Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Africa; Biomass burning; Burned Area; Fire; MODIS; Sentinel-2

Mesh:

Year:  2022        PMID: 35817109     DOI: 10.1016/j.scitotenv.2022.157139

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   10.753


  1 in total

1.  On the use of Earth Observation to support estimates of national greenhouse gas emissions and sinks for the Global stocktake process: lessons learned from ESA-CCI RECCAP2.

Authors:  Ana Bastos; Philippe Ciais; Stephen Sitch; Luiz E O C Aragão; Frédéric Chevallier; Dominic Fawcett; Thais M Rosan; Marielle Saunois; Dirk Günther; Lucia Perugini; Colas Robert; Zhu Deng; Julia Pongratz; Raphael Ganzenmüller; Richard Fuchs; Karina Winkler; Sönke Zaehle; Clément Albergel
Journal:  Carbon Balance Manag       Date:  2022-10-01
  1 in total

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