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Quantifying Post-Fire Changes in the Aboveground Biomass of an Amazonian Forest Based on Field and Remote Sensing Data

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Autor(es):
Pontes-Lopes, Aline ; Dalagnol, Ricardo ; Dutra, Andeise Cerqueira ; de Jesus Silva, Camila Valeria ; Lima de Alencastro Graca, Paulo Mauricio ; de Oliveira E Cruz de Aragao, Luiz Eduardo
Número total de Autores: 6
Tipo de documento: Artigo Científico
Fonte: REMOTE SENSING; v. 14, n. 7, p. 20-pg., 2022-04-01.
Resumo

Fire is a major forest degradation component in the Amazon forests. Therefore, it is important to improve our understanding of how the post-fire canopy structure changes cascade through the spectral signals registered by medium-resolution satellite sensors over time. We contrasted accumulated yearly temporal changes in forest aboveground biomass (AGB), measured in permanent plots, and in traditional spectral indices derived from Landsat-8 images. We tested if the spectral indices can improve Random Forest (RF) models of post-fire AGB losses based on pre-fire AGB, proxied by AGB data from immediately after a fire. The delta normalized burned ratio, non-photosynthetic vegetation, and green vegetation (Delta NBR, Delta NPV, and Delta GV, respectively), relative to pre-fire data, were good proxies of canopy damage through tree mortality, even though small and medium trees were the most affected tree size. Among all tested predictors, pre-fire AGB had the highest RF model importance to predicting AGB within one year after fire. However, spectral indices significantly improved AGB loss estimates by 24% and model accuracy by 16% within two years after a fire, with Delta GV as the most important predictor, followed by Delta NBR and Delta NPV. Up to two years after a fire, this study indicates the potential of structural and spectral-based spatial data for integrating complex post-fire ecological processes and improving carbon emission estimates by forest fires in the Amazon. (AU)

Processo FAPESP: 19/21662-8 - Quantificando mortalidade de árvores com lasers: usando uma abordagem de fusão de dados e modelagem de última geração para estimar a perda de biomassa em florestas tropicais
Beneficiário:Ricardo Dal'Agnol da Silva
Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado
Processo FAPESP: 18/15001-6 - ARBOLES: um entendimento da biodiversidade e resiliência das florestas LATAM baseado em características funcionais
Beneficiário:Luiz Eduardo Oliveira e Cruz de Aragão
Modalidade de apoio: Auxílio à Pesquisa - Regular
Processo FAPESP: 16/21043-8 - LiDAR aerotransportado para a quantificação de mudanças nos estoques de biomassa e na dinâmica da estrutura de florestas afetadas por fogo na Amazônia Central
Beneficiário:Aline Pontes Lopes
Modalidade de apoio: Bolsas no Brasil - Doutorado