@InProceedings{SatoMaCaKoFoAlVa:2011:ClÁrEx,
               author = "Sato, Luciane Yumie and Martins, Flora da Silva Ramos Vieira and 
                         Cantinho, Roberta Zecchini and Korting, Thales Sehn and Fonseca, 
                         Leila Maria Garcia and Almeida, Cl{\'a}udio Aparecido de and 
                         Valeriano, Dalton de Morisson",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais - INPE} and {Instituto 
                         Nacional de Pesquisas Espaciais - INPE} and {Instituto Nacional de 
                         Pesquisas Espaciais - INPE} and {Instituto Nacional de Pesquisas 
                         Espaciais - INPE} and {Instituto Nacional de Pesquisas Espaciais - 
                         INPE} and {Instituto Nacional de Pesquisas Espaciais - INPE} and 
                         {Instituto Nacional de Pesquisas Espaciais - INPE}",
                title = "Classifica{\c{c}}{\~a}o de {\'a}reas exploradas por sistema de 
                         corte seletivo na Amaz{\^o}nia",
            booktitle = "Anais...",
                 year = "2011",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Galv{\~a}o, L{\^e}nio 
                         Soares",
                pages = "6688--6695",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 15. (SBSR).",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             keywords = "p{\'a}tios, MLME, GeoDMA, LMM, log dump.",
             abstract = "Selective logging is a major cause of forest degradation. Its 
                         monitoring represents a key application of remote sensing and 
                         associated technologies of GIS. In this way, the DETEX Project has 
                         shown significant improvements in the detection of these areas, 
                         but the implemented methodology suffered from clear limitations. 
                         This paper aims to enhance the existing techniques of areas 
                         classification where selective cutting has occurred. In this 
                         purpose, the Linear Mixing Model (LMM) and the ratio between bands 
                         were used to detect impacted zones. Areas already cleared were 
                         removed from the analysis using the PRODES mask and the cropped 
                         image was imported into TerraView, where a mesh of 1 km2 has been 
                         created. The system GeoDMA was used to extract, from each cell, 
                         representative attributes of the identified classes (i) 
                         non-forest, (ii) forest, (iii) initial selective logging, (iv) 
                         intermediary selective logging and (v) advanced selective logging. 
                         From summary statistics of the sampled cells (mean, standard 
                         deviation, entropy, amplitude, sum and mode), a decision tree was 
                         carried out to classify the remaining ones. Overall accuracy was 
                         73% and the main discrepancies occurred in border areas. The 
                         classification technique was quite efficient in identifying 
                         initial (83%), advanced (85%) and intermediary (100%) explorations 
                         where they occurred. Although affected areas could not be 
                         quantified, these results can be useful in order to implement a 
                         powerful warning system.",
  conference-location = "Curitiba",
      conference-year = "30 abr. - 5 maio 2011",
                 isbn = "{978-85-17-00056-0 (Internet)} and {978-85-17-00057-7 (DVD)}",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "3ERPFQRTRW/3A2QQF2",
                  url = "http://urlib.net/ibi/3ERPFQRTRW/3A2QQF2",
           targetfile = "p1113.pdf",
                 type = "Desflorestamento",
        urlaccessdate = "02 maio 2024"
}