| Texto completo | |
| Autor(es): |
Lucchetta, Beatriz Cirino
;
Watanabe, Fernanda Sayuri Yoshino
;
Oliveira, Fernanda Silva
Número total de Autores: 3
|
| Tipo de documento: | Artigo Científico |
| Fonte: | Bol. Ciênc. Geod.; v. 30, p. 14-pg., 2024-01-01. |
| Resumo | |
The socio-environmental impacts caused by the collapse of a mining dam can be irreversible. In Brazil, the dam collapse at the C & oacute;rrego do Feij & atilde;o Mine was considered one of the worst disasters in the country. Remote sensingbased approaches have been used to detect and monitor areas affected by tailings from dam rupture. Therefore, it was proposed to identify the area affected by mining tailing mud, in Brumadinho, Minas Gerais State, through the analysis of three different spectral indices: Normalized Difference Vegetation Index (NDVI), Ferrous Minerals Ratio (FMR) and Clay Minerals Ratio (CMR). These indices were computed from the Operational Land Imager (OLI) images of Landsat-8. Different thresholds were tested to define the best range for delineating the affected area. For validation, the limits of the affected area, obtained from a higher resolution sensor, GeoEye-1, were used as reference. The methodology demonstrated great potential for detecting areas affected by dam failure. The indices NDVI and FMR delimited the area of interest with high performance, with precision varying between 95% and 92%; recall between 88% and 87%; F-score between 91% and 89%; and global accuracy between 84% and 80%, showing to be suitable mapping such disasters. (AU) | |
| Processo FAPESP: | 21/11296-4 - Análise da sensibilidade de imagens aéreas obtidas por câmeras multiespectrais para o monitoramento integrado de macrófitas e parâmetros da qualidade da água |
| Beneficiário: | Beatriz Cirino Lucchetta |
| Modalidade de apoio: | Bolsas no Brasil - Programa Capacitação - Treinamento Técnico |