| Full text | |
| Author(s): |
Shimabukuro, Yosio Edemir
;
de Oliveira, Gabriel
;
Pereira, Gabriel
;
Arai, Egidio
;
Cardozo, Francielle
;
Dutra, Andeise Cerqueira
;
Mataveli, Guilherme
Total Authors: 7
|
| Document type: | Journal article |
| Source: | FIRE-SWITZERLAND; v. 6, n. 7, p. 14-pg., 2023-07-01. |
| Abstract | |
The Pantanal biome-a tropical wetland area-has been suffering a prolonged drought that started in 2019 and peaked in 2020. This favored the occurrence of natural disasters and led to the 2020 Pantanal fire crisis. The purpose of this work was to map the burned area's extent during this crisis in the Brazilian portion of the Pantanal biome using Sentinel-2 MSI images. The classification of the burned areas was performed using a machine learning algorithm (Random Forest) in the Google Earth Engine platform. Input variables in the algorithm were the percentiles 10, 25, 50, 75, and 90 of monthly (July to December) mosaics of the shade fraction, NDVI, and NBR images derived from Sentinel-2 MSI images. The results showed an overall accuracy of 95.9% and an estimate of 44,998 km(2) burned in the Brazilian portion of the Pantanal, which resulted in severe ecosystem destruction and biodiversity loss in this biome. The burned area estimated in this work was higher than those estimated by the MCD64A1 (35,837 km(2)), Fire_cci (36,017 km(2)), GABAM (14,307 km(2)), and MapBiomas Fogo (23,372 km(2)) burned area products, which presented lower accuracies. These differences can be explained by the distinct datasets and methods used to obtain those estimates. The proposed approach based on Sentinel-2 images can potentially refine the burned area's estimation at a regional scale and, consequently, improve the estimate of trace gases and aerosols associated with biomass burning, where global biomass burning inventories are widely known for having biases at a regional scale. Our study brings to light the necessity of developing approaches that aim to improve data and theory about the impacts of fire in regions critically sensitive to climate change, such as the Pantanal, in order to improve Earth systems models that forecast wetland-atmosphere interactions, and the role of these fires on current and future climate change over these regions. (AU) | |
| FAPESP's process: | 22/01746-5 - The impact of climate change on drylands vegetation phenology in the Southern Hemisphere |
| Grantee: | Andeise Cerqueira Dutra |
| Support Opportunities: | Scholarships in Brazil - Doctorate |
| FAPESP's process: | 19/25701-8 - The influence of land use and land cover on fine particulate matter (PM2.5µm) emissions from fire in Amazonia and Cerrado biomes integrating modelling and remote sensing |
| Grantee: | Guilherme Augusto Verola Mataveli |
| Support Opportunities: | Scholarships in Brazil - Post-Doctoral |
| FAPESP's process: | 23/02386-5 - Characterization and monitoring of land surface phenology of natural vegetation in drylands |
| Grantee: | Andeise Cerqueira Dutra |
| Support Opportunities: | Scholarships abroad - Research Internship - Doctorate |
| FAPESP's process: | 23/03206-0 - Improving biomass burning emissions estimates by updating emission factors values |
| Grantee: | Guilherme Augusto Verola Mataveli |
| Support Opportunities: | Scholarships abroad - Research Internship - Post-doctor |
| FAPESP's process: | 16/02018-2 - Interannual variation of Amazon Basin greenhouse gas balances and their controls in a warming and increasingly variable climate – Carbam: the Amazon carbon balance long-term study |
| Grantee: | Luciana Vanni Gatti |
| Support Opportunities: | Research Program on Global Climate Change - Thematic Grants |
| FAPESP's process: | 20/15230-5 - Research Centre for Greenhouse Gas Innovation - RCG2I |
| Grantee: | Julio Romano Meneghini |
| Support Opportunities: | Research Grants - Research Centers in Engineering Program |