@InProceedings{FerreiraZaZoKöFoShSo:2014:AuTrCr,
               author = "Ferreira, Matheus Pinheiro and Zanotta, Daniel Capella and Zortea, 
                         Maciel and K{\"o}rting, Thales Sehn and Fonseca, Leila M. G. and 
                         Shimabukuro, Yosio Edemir and Souza Filho, Carlos R.",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {2Norwegian Computer 
                         Center – Oslo – Norway} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)} and {Instituto Nacional de Pesquisas Espaciais (INPE)} and 
                         Institute of Geosciences, University of Campinas – Campinas – SP – 
                         Brazil",
                title = "Automatic tree crown delineation in tropical forest using 
                         hyperspectral data",
            booktitle = "Proceedings...",
                 year = "2014",
                pages = "784",
         organization = "IEEE International Geoscience and Remote Sensing Symposium, 
                         (IGARSS 2014).",
            publisher = "IEEE",
             keywords = "Brazilian Atlantic Forest, image segmentation, individual tree 
                         crowns, forest management, deciduous tree species.",
             abstract = "This paper aims to use unique features of hyperspectral data on an 
                         automatic process for outlining individual tree crowns (ITCs) in a 
                         tropical forest area, with special focus on semideciduous species. 
                         In order to enhance biophysical and biochemical properties of 
                         canopy species, a set of vegetation indices were computed. These 
                         indices served as input for a region growing segmentation 
                         algorithm that takes into account mutual similarity of pixels and 
                         spectral separability between neighbor segments. Segmentation 
                         output was evaluated on the basis of a score computed with the 
                         proportion of the area of the segments located within manually 
                         delineated ITCs. Results show that the segmentation approach is 
                         able to automatically delineate up to 70% of the control ITCs.",
  conference-location = "Quebec City",
      conference-year = "2014",
                  doi = "10.1109/IGARSS.2014.6946541",
                  url = "http://dx.doi.org/10.1109/IGARSS.2014.6946541",
                 isbn = "9781479957750",
                label = "lattes: 9686528152912455 1 FerreiraZaZoKoFoShFo:2014:AuTrCr",
             language = "pt",
           targetfile = "matheus.pdf",
        urlaccessdate = "27 abr. 2024"
}