Detecting Amazonian deforestation using multitemporal thematic mapper imageries and spectral mixture analysis.

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Authorship: LU, D.; BATISTELLA, M.; MORAN, E.

Summary: Linear spectral mixture analysis (LSMA) and multitemporal Thematic Mapper (TM) data were used to detect deforestation in Altamira and Machadinho, Brazilian Amazon. Standardized principal component analysis was used to transform TM data into uncorrelated principal components (PCs). Three endmembers were selected and an unconstrained least root-mean squared error solution was used to unmix the first four PCs into three fraction images. Mature forest classification was implemented using thresholds and deforestation detection using binary image overlay. This study indicates that LSMA is an effective method to identify mature forest and detect deforested areas with high accuracies.

Publication year: 2003

Types of publication: Annals and event proceedings


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