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@Article{WagnerPSHZGPSSA:2018:InTrCr,
               author = "Wagner, Fabien Hubert and Perreira, Matheus Pinheiro and Sanchez 
                         Ipia, Alber Hamersson and Hirye, Mayumi C. M. and Zortea, Maciel 
                         and Gloor, Emanuel and Phillips, Oliver L. and Souza Filho, Carlos 
                         Roberto de and Shimabukuro, Yosio Edemir and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
          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 {IBM Research Brazil} and {University of 
                         Leeds} and {University of Leeds} and {Universidade Estadual de 
                         Campinas (UNICAMP)} and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)} and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "Individual tree crown delineation in a highly diverse tropical 
                         forest using very high resolution satellite images",
              journal = "ISPRS Journal of Photogrammetry and Remote Sensing",
                 year = "2018",
               volume = "145",
               number = "pt B",
                pages = "362--377",
                month = "Nov.",
             keywords = "Image segmentation, Multispectral image, Tropical forests, Species 
                         identification, Rolling ball algorithm, Mathematical morphology.",
             abstract = "Mapping tropical tree species at landscape scales to provide 
                         information for ecologists and forest managers is a new challenge 
                         for the remote sensing community. For this purpose, detection and 
                         delineation of individual tree crowns (ITCs) is a prerequisite. 
                         Here, we present a new method of automatic tree crown delineation 
                         based only on very high resolution images from WorldView-2 
                         satellite and apply it to a region of the Atlantic rain forest 
                         with highly heterogeneous tropical canopy cover the Santa Genebra 
                         forest reserve in Brazil. The method works in successive steps 
                         that involve pre-processing, selection of forested pixels, 
                         enhancement of borders, detection of pixels in the crown borders, 
                         correction of shade in large trees and, finally, segmentation of 
                         the tree crowns. Principally, the method uses four techniques: 
                         rolling ball algorithm and mathematical morphological operations 
                         to enhance the crown borders and ease the extraction of tree 
                         crowns; bimodal distribution parameters estimations to identify 
                         the shaded pixels in the gaps, borders, and crowns; and focal 
                         statistics for the analysis of neighbouring pixels. Crown 
                         detection is validated by comparing the delineated ITCs with a 
                         sample of ITCs delineated manually by visual interpretation. In 
                         addition, to test if the spectra of individual species are 
                         conserved in the automatic delineated crowns, we compare the 
                         accuracy of species prediction with automatic and manual 
                         delineated crowns with known species. We find that our method 
                         permits detection of up to 80% of ITCs. The seven species with 
                         over 10 crowns identified in the field were mapped with reasonable 
                         accuracy (30.596%) given that only WorldView-2 bands and texture 
                         features were used. Similar classification accuracies were 
                         obtained using both automatic and manual delineation, thereby 
                         confirming that species spectral responses are preserved in the 
                         automatic method and thus permitting the recognition of species at 
                         the landscape scale. Our method might support tropical forest 
                         applications, such as mapping species and canopy characteristics 
                         at the landscape scale.",
                  doi = "10.1016/j.isprsjprs.2018.09.013",
                  url = "http://dx.doi.org/10.1016/j.isprsjprs.2018.09.013",
                 issn = "0924-2716",
             language = "en",
           targetfile = "wagner_individual.pdf",
        urlaccessdate = "22 jan. 2021"
}


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