| Texto completo | |
| Autor(es): |
Shimabukuro, Yosio Edemir
;
Arai, Egidio
;
da Silva, Gabriel Maximo
;
Duarte, Valdete
Número total de Autores: 4
|
| Tipo de documento: | Artigo Científico |
| Fonte: | IGARSS 2024-2024 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, IGARSS 2024; v. N/A, p. 5-pg., 2024-01-01. |
| Resumo | |
Deforestation is the replacement of forest by other land use, while degradation is a reduction of long-term canopy cover and/ or forest stock. In the Brazilian Amazon, forest degradation mainly results from selective logging of intact/unmanaged forests and uncontrolled fires. While the contribution of deforestation to carbon emissions is well-known, determining the impact of forest degradation remains challenging. This work presents a semi-automated procedure for classifying forest degradation in Mato Grosso State using fraction images derived from the Linear Spectral Mixing Model (LSMM). Sentinel-2 MSI and Landsat OLI images acquired in 2023 over the study area were selected to develop the proposed method. Discrimination against logging from fires, which produce different levels of forest damage, is important for the UNFCCC (United Nations Framework Convention on Climate Change) REDD+ (Reducing Emissions from Deforestation and Forest Degradation) program. (AU) | |
| Processo FAPESP: | 19/19371-5 - Análise espaço-temporal do uso e cobertura da terra no estado de São Paulo utilizando técnicas de sensoriamento remoto |
| Beneficiário: | Yosio Edemir Shimabukuro |
| Modalidade de apoio: | Auxílio à Pesquisa - Regular |