Data/hora: 17/06/2024 12:09:28

Biblioteca(s): | Embrapa Cerrados.
Data corrente: | 10/05/2022
Data da última atualização: | 10/05/2022
Autoria: | SILVA, C. A.; GUERRISI, G.; DEL FRATE, F.; SANO, E. E.
Afiliação: | CLAUDIA ARANTES SILVA; GIORGIA GUERRISI; FABIO DEL FRATE; EDSON EYJI SANO, CPAC.
Título: | Near-real time deforestation detection in the Brazilian Amazon with Sentinel-1 and neural networks.
Ano de publicação: | 2022
Fonte/Imprenta: | European Journal of Remote Sensing, v. 55, n. 1, 2022.
Páginas: | p. 129-149
Idioma: | Inglês
Conteúdo: | Optical-based near-real time deforestation alert systems in the Brazilian Amazon are ineffective in the rainy season. This study identify clear-cut deforested areas through Neural Network (NN) algorithm based on C-band, VV- and VH-polarized, Sentinel-1 images. Statistical parameters of backscatter coefficients (mean, standard deviation, and the difference between maximum and minimum values ? MMD) were computed from 30 Sentinel-1 images, from 2019, used as input parameters of the NN classifier. The samples were manually selected, including forested and deforested areas. After deforestation, mean backscatter signals decreased on the average of 2 dB for VV and 2.3 dB for VH from May to September?October. A Multi-Layer Perceptron (MLP) network was used for detecting near-real time forest disturbances larger than 2 ha. Case studies were performed for both polarizations considered the following input sets to the MLP: mean; mean and standard deviation; mean and MMD; and mean, standard deviation, and MMD. For the 2019 dataset, the latter showed the best performance of the NN algorithm with accuracy and F1 score of 99%. Automatic extraction using 2018 Sentinel-1 images reached accuracy and F1 score of 89% with the MapBiomas reference data and accuracy of 81% and F1 score of 79% with the PRODES reference data.
Palavras-Chave: | Desflorestamento; Extração automática de imagens; Floresta Amazônica; Rede neural.
Thesagro: | Desmatamento; Floresta Tropical.
Categoria do assunto: | --
URL: | http://ainfo.cnptia.embrapa.br/digital/bitstream/doc/1142848/1/Sano-Near-real-time-deforestation-detection-in-the.pdf
Registro original: | Embrapa Cerrados (CPAC)
Exemplares: | CPAC - (37284-1) - UPC - AP - DD - DIGITAL -  - DIGITAL - DIS