@Article{FerreiraWagAraShiSou:2019:TrSpCl,
               author = "Ferreira, Matheus Pinheiro and Wagner, Fabien Hubert and 
                         Arag{\~a}o, Luiz Eduardo Oliveira e Cruz de and Shimabukuro, 
                         Yosio Edemir and Souza Filho, Carlos Roberto de",
          affiliation = "{Instituto Militar de Engenharia (IME)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)} and {Universidade Estadual de Campinas (UNICAMP)}",
                title = "Tree species classification in tropical forests using visible to 
                         shortwave infrared WorldView-3 images and texture analysis",
              journal = "ISPRS Journal of Photogrammetry and Remote Sensing",
                 year = "2019",
               volume = "149",
                pages = "119--131",
                month = "Mar.",
                 note = "{Pr{\^e}mio CAPES Elsevier 2023 - ODS 15: Vida terrestre}",
             keywords = "Tropical forests, Biodiversity, Tree species discrimination, 
                         Very-high resolution, Canopy structure, GLCM.",
             abstract = "Tropical forest conservation and management can significantly 
                         benefit from information about the spatial distribution of tree 
                         species. Very-high resolution (VHR) spaceborne platforms have been 
                         hailed as a promising technology for mapping tree species over 
                         broad spatial extents. WorldView-3, the most advanced VHR sensor, 
                         provides spectral data in 16 bands covering the visible to 
                         near-infrared (VNIR, 4001040 nm) and shortwaveinfrared (SWIR, 
                         12102365 nm) wavelength ranges. It also collects images at 
                         unprecedented levels of details using a panchromatic band with 
                         0.3-m of spatial resolution. However, the potential of WorldView-3 
                         at its full spectral and spatial resolution for tropical tree 
                         species classification remains unknown. In this study, we 
                         performed a comprehensive assessment of WorldView-3 images 
                         acquired in the dry and wet seasons for tree species 
                         discrimination in tropical semi-deciduous forests. Classification 
                         experiments were performed using VNIR individually and combined 
                         with SWIR channels. To take advantage of the sub-metric resolution 
                         of the panchromatic band for classification, we applied an 
                         individual tree crown (ITC)-based approach that employed 
                         pansharpened VNIR bands and gray level co-occurrence matrix 
                         texture features. We determined whether the combination of images 
                         from the two annual seasons improves the classification accuracy. 
                         Finally, we investigated which plant traits influenced species 
                         detection. The new SWIR sensing capabilities of WorldView-3 
                         increased the average producers accuracy up to 7.8%, by enabling 
                         the detection of non-photosynthetic vegetation within ITCs. The 
                         combination of VNIR bands from the two annual seasons did not 
                         improve the classification results when compared to the results 
                         obtained using images from each season individually. The use of 
                         VNIR bands at their original 1.2-m spatial resolution yielded 
                         average producers accuracies of 43.1 ± 3.1% and 38.8 ± 3% in the 
                         wet and dry seasons, respectively. The ITC-based approach improved 
                         the accuracy to 70 ± 8% in the wet and 68.4 ± 7.4% in the dry 
                         season. Texture analysis of the panchromatic band enabled the 
                         detection of species-specific differences in crown structure, 
                         which improved species detection. The use of texture analysis, 
                         pan-sharpening, and ITC delineation is a potential approach to 
                         perform tree species classification in tropical forests with 
                         WorldView-3 satellite images.",
                  doi = "10.1016/j.isprsjprs.2019.01.019",
                  url = "http://dx.doi.org/10.1016/j.isprsjprs.2019.01.019",
                 issn = "0924-2716",
             language = "en",
           targetfile = "ferreira_tree.pdf",
        urlaccessdate = "28 abr. 2024"
}