author = "Ferreira, Matheus Pinheiro and Zortea, Maciel and Zanotta, Daniel 
                         Capella and F{\'e}ret, Jean-Baptiste and Shimabukuro, Yosio 
                         Edemir and Souza Filho, Carlos Roberto de",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and Institute 
                         of Informatics, Federal University of Rio Grande do Sul (UFRGS), 
                         Porto Alegre, Brazil and Institute for Education Science and 
                         Technology, Rio Grande, Brazil and Territoires, Environnement, 
                         Teledetection et Information Spatiale, Montpellier, France and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)} and 
                         Universidade Estadual de Campinas, Institute of Geosciences, 
                         Campinas, Brazil",
                title = "On the use of shortwave infrared for tree species discrimination 
                         in tropical semideciduous forest",
            booktitle = "Proceedings...",
                 year = "2015",
               editor = "N. , Paparoditis and A. -M. , Raimond and G. , Sithole and G. , 
                         Rabatel and A. , Coltekin and F. , Rottensteiner and X. , Briottet 
                         and S. , Christophe and I. , Dowman and S. O. , Elberink and G. , 
                         Patane and C. , Mallet",
                pages = "473--476",
         organization = "International Archives of the Photogrammetry, Remote Sensing and 
                         Spatial Information Sciences (ISPRS Archives)",
             keywords = "Hyperspectral remote sensing, tropical forests, classification.",
             abstract = "Tree species mapping in tropical forests provides valuable 
                         insights for forest managers. Keystone species can be located for 
                         collection of seeds for forest restoration, reducing fieldwork 
                         costs. However, mapping of tree species in tropical forests using 
                         remote sensing data is a challenge due to high floristic and 
                         spectral diversity. Little is known about the use of different 
                         spectral regions as most of studies performed so far used 
                         visible/near-infrared (390-1000 nm) features. In this paper we 
                         show the contribution of shortwave infrared (SWIR, 1045-2395 nm) 
                         for tree species discrimination in a tropical semideciduous 
                         forest. Using high-resolution hyperspectral data we also simulated 
                         WorldView-3 (WV-3) multispectral bands for classification 
                         purposes. Three machine learning methods were tested to 
                         discriminate species at the pixel-level: Linear Discriminant 
                         Analysis (LDA), Support Vector Machines with Linear (L-SVM) and 
                         Radial Basis Function (RBF-SVM) kernels, and Random Forest (RF). 
                         Experiments were performed using all and selected features from 
                         the VNIR individually and combined with SWIR. Feature selection 
                         was applied to evaluate the effects of dimensionality reduction 
                         and identify potential wavelengths that may optimize species 
                         discrimination. Using VNIR hyperspectral bands, RBF-SVM achieved 
                         the highest average accuracy (77.4%). Inclusion of the SWIR 
                         increased accuracy to 85% with LDA. The same pattern was also 
                         observed when WV-3 simulated channels were used to classify the 
                         species. The VNIR bands provided and accuracy of 64.2% for LDA, 
                         which was increased to 79.8 % using the new SWIR bands that are 
                         operationally available in this platform. Results show that 
                         incorporating SWIR bands increased significantly average accuracy 
                         for both the hyperspectral data and WorldView-3 simulated bands.",
  conference-location = "La grande Motte, France",
      conference-year = "28 Sept. - 02 Oct.",
                  doi = "10.5194/isprsarchives-XL-3-W3-473-2015",
                  url = "http://dx.doi.org/10.5194/isprsarchives-XL-3-W3-473-2015",
                 isbn = "16821750",
                label = "lattes: 9686528152912455 1 FerreiraZoZaF{\'e}ShSo:2015:UsShIn",
             language = "pt",
         organisation = "International Society for Photogrammetry and Remote Sensing",
           targetfile = "1_ferreira.pdf",
                  url = "http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-3-W3/473/2015/isprsarchives-XL-3-W3-473-2015.pdf",
               volume = "40",
        urlaccessdate = "24 jan. 2021"