@InProceedings{FerreiraShimSouz:2017:TrTrSp,
               author = "Ferreira, Matheus Pinheiro and Shimabukuro, Yosio Edemir and Souza 
                         Filho, Carlos Roberto",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)}",
                title = "Tropical tree species discrimination using very high-resolution 
                         satellite images and texture analysis",
            booktitle = "Anais...",
                 year = "2017",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "546--553",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 18. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "In this study, we evaluate the use of texture descriptors obtained 
                         from very high-resolution satellite imagery to improve tree 
                         species classification in a tropical forest. Gray level 
                         co-occurrence matrix (GLCM), gabor and wavelet features were 
                         combined with reflectance bands of the WorldView-2 (WV-2) and 
                         QuickBird-2 (QB-2) satellite sensors to perform species 
                         classification. The use of QB-2 and WV-2 reflectance data yielded 
                         26.6% and 44.8% of average accuracy, respectively. Texture 
                         features combined with QB-2 bands did not improve significantly 
                         the results. However, the combination of GLCM features with WV-2 
                         reflectance bands increased the average accuracy up to 5.7%, 
                         exceeding 15% for some species. Pioneer species such as Cecropia 
                         hololeuca and climax species such as Cariniana legalis were 
                         classified with approximately 90% accuracy. The results highlight 
                         the potential use of WV-2 imagery to monitor tropical forest 
                         environments.",
  conference-location = "Santos",
      conference-year = "28-31 maio 2017",
                 isbn = "978-85-17-00088-1",
                label = "59219",
             language = "en",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3PS44FM",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PS44FM",
           targetfile = "59219.pdf",
                 type = "Floresta e outros tipos de vegeta{\c{c}}{\~a}o",
        urlaccessdate = "27 abr. 2024"
}