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• W2014733368 abstract "Fires associated with recurrent El Nino events have caused severe damage to tropical peat swamp forests. Accurate quantitative information about the frequency and distribution of the burned areas is imperative to fire management but is lacking in the tropics. This article examines a novel method based on principal component analysis (PCA) of the normalized difference water index (NDWI) from multisensor data for simultaneously detecting areas burned due to multiple El Nino–related fires. The principal components of multitemporal NDWI (NDWI-PCs) were able to capture the areas burned in the 1998 and 2003 El Nino fires in NDWI-PC3 and 2, respectively. The proposed method facilitates the reduction of dimensionality in detecting the burned areas. From 22 image bands, the proposed method was able to accurately detect the burned areas of multiple fires with only three NDWI-PCs. The proposed method also shows superior performance to unsupervised classifications of the principal components of combined image bands, ..." @default.
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• W2014733368 date "2012-01-16" @default.
• W2014733368 modified "2023-10-03" @default.
• W2014733368 title "Simultaneous detection of burned areas of multiple fires in the tropics using multisensor remote-sensing data" @default.
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• W2014733368 doi "https://doi.org/10.1080/01431161.2011.643460" @default.
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