| Texto completo | |
| Autor(es): |
Shimabukuro, Yosio Edemir
;
Arai, Egidio
;
Da Silva, Gabriel Maximo
;
Dutra, Andeise Cerqueira
;
Mataveli, Guilherme
;
Hoffmann, Tania Beatriz
;
Godinho Cassol, Henrique Luis
;
Duarte, Valdete
;
Martini, Paulo Roberto
Número total de Autores: 9
|
| Tipo de documento: | Artigo Científico |
| Fonte: | IGARSS 2023 - 2023 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM; v. N/A, p. 4-pg., 2023-01-01. |
| Resumo | |
This article presents a new method for monitoring forest cover in the state of Rondonia, in the Brazilian Amazon. The proposed method applies the Linear Spectral Mixing Model (LSMM) to Landsat datasets (MSS, TM and OLI) to derive annual vegetation, soil, and shade fraction images for the period 1980 - 2020. These fraction images have the advantages of reducing the volume of data to be analyzed and highlighting the target characteristics. Then, we applied a threshold method to classify forest, non-forest, hydrography, and deforestation areas. The proposed method showed to be consistent and flexible allowing to change the threshold values according to the fraction images to obtain the results with high accuracy. The results obtained by the proposed method can be easily checked over the RGB image mosaic. This kind of information is very important for environmental and climate change studies and for supporting government conservation efforts. (AU) | |
| Processo FAPESP: | 22/01746-5 - O impacto das mudanças climáticas na fenologia da vegetação natural em terras secas do Hemisfério Sul |
| Beneficiário: | Andeise Cerqueira Dutra |
| Modalidade de apoio: | Bolsas no Brasil - Doutorado |
| 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 |