@Article{Espirito-SantoShimKupl:2005:MaFoSu,
               author = "Espirito-Santo, F. D. B. and Shimabukuro, Yosio Edemir and 
                         Kuplich, Tatiana Mora",
          affiliation = "Instituto Nacional de Pesquisas Espaciais, Divis{\~a}o de 
                         Sensoriamento Remoto (INPE, DSR)",
                title = "Mapping forest successional stages following deforestation in 
                         Brazilian Amazonia using multi-temporal Landsat images",
              journal = "International Journal of Remote Sensing",
                 year = "2005",
               volume = "26",
               number = "3",
                pages = "635--642",
                month = "Feb",
             keywords = "Classification (of information), Deforestation, Image sensors, 
                         Mapping, Remote sensing, Satellite communication systems, Signal 
                         detection, Enhanced thematic mapper plus (ETM+), Forest 
                         successional stages, Satellite sensor imagery, Thematic mapper 
                         (TM), Forestry, deforestation, land classification, Landsat 
                         thematic mapper, satellite imagery, succession, vegetation 
                         mapping, Classification, Deforestation, Forestry, Mapping, Remote 
                         Sensing, Satellites, Amazonia, South America, Western Hemisphere, 
                         World.",
             abstract = "Tropical forest successional stages have been mapped previously 
                         with multi-temporal satellite sensor imagery. The precise 
                         identification and classification of such stages, however, has 
                         proved difficult. This Letter presents a new method for the 
                         classification of forest successional stages following 
                         deforestation in Brazilian Amazonia. Multi-temporal Landsat 
                         Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) and 
                         derived fraction images and field data were used in a 
                         semi-automatic classification approach. The results were 
                         encouraging and signal the application of the method for the 
                         entire Brazilian Amazonia.",
           copyholder = "SID/SCD",
                  doi = "10.1080/0143116042000274078",
                  url = "http://dx.doi.org/10.1080/0143116042000274078",
                 issn = "0143-1161",
             language = "en",
           targetfile = "88.pdf",
        urlaccessdate = "21 maio 2024"
}