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Mapping Fire Susceptibility in the Brazilian Amazon Forests Using Multitemporal Remote Sensing and Time-Varying Unsupervised Anomaly Detection

The economic and environmental impacts of wildfires have leveraged the development of new technologies to prevent and reduce the occurrence of these devastating events. Indeed, identifying and mapping fire-susceptible areas arise as critical tasks, not only to pave the way for rapid responses to att...

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Principais autores: Andréa Eliza O. Luz, Rogério G. Negri, Klécia G. Massi, Marilaine Colnago, Erivaldo A. Silva, Wallace Casaca
Format: Artigo
Sprog:Inglês
Udgivet: MDPI AG 2022-05-01
Serier:Remote Sensing
Fag:
remote sensing
multitemporal data
anomaly detection
forest fires
spectral indices
Online adgang:https://www.mdpi.com/2072-4292/14/10/2429
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