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

Enter multiple e-mails separated by comma.

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

Observation

Some of Embrapa's publications are published as ePub files. To read them, use or download one of the following free software options to your computer or mobile device. Android: Google Play Books; IOS: iBooks; Windows and Linux: Calibre.

 


Access other publications

Access the Agricultural Research Database (BDPA) to consult Embrapa's full library collection and records.
Visit Embrapa Bookstore to purchase books and other publications sold by Embrapa.