@Article{SotheAlmSchLieDia:2021:AuTuSe,
               author = "Sothe, Camile and Almeida, Cl{\'a}udia Maria de and Schimalski, 
                         Marcos Benedito and Liesenberg, Veraldo and Diaz, Pedro 
                         Achanccaray",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Universidade do 
                         Estado de Santa Catarina (UDESC)} and {Universidade do Estado de 
                         Santa Catarina (UDESC)} and {Pontif{\'{\i}}cia Universidade 
                         Cat{\'o}lica do Rio de Janeiro (PUC-Rio)}",
                title = "Automatic tuning of segmentation parameters for tree crown 
                         delineation with VHR imagery",
              journal = "Geocarto International",
                 year = "2021",
               volume = "36",
               number = "19",
                pages = "2241--2259",
             keywords = "image segmentation, Individual tree crown, metaheuristic methods, 
                         object-based image analysis, optimization function.",
             abstract = "In the case of tree species delineation with very high spatial 
                         resolution (VHR) images, is desirable that each segment 
                         corresponds to one individual tree crown (ITC). However, in order 
                         to have a segmentation algorithm that generates segments matching 
                         to ITCs, its parameters ought to be properly tuned. Aiming to 
                         avoid time-consuming trial-and-error procedures associated with 
                         this task, some initiatives for the automatic search of 
                         segmentation parameters have been developed, such as metaheuristic 
                         methods. The objective of this work was to test the automatic 
                         tuning of segmentation parameters of three segmentation algorithms 
                         for the delineation of ITCs belonging to a native endangered 
                         species in a subtropical forest area, comparing this method with 
                         the traditional trial-and-error approach. Two datasets 
                         (WorldView-2 and an orthoimage) and three segmentation algorithms 
                         (multiresolution, mean-shift and graph-based) were tested. For the 
                         automatic approach, a hybrid metaheuristic method was applied to 
                         accomplish the automatic search of parameters for the segmentation 
                         algorithms, while for the trial-and-error, a visual assessment was 
                         conducted for each set of parameters tested. Four supervised 
                         metrics were used to assess the quality of the segmentation 
                         results for the optimization approach and for the final set of 
                         parameters chosen in the trial-and-error approach. Results showed 
                         that none of the algorithms, datasets or approaches differ too 
                         much. The evaluation metrics values were lower, indicating that 
                         the reference ITCs polygons matched with the segmentation results. 
                         Despite the similar results, the automatic tuning of segmentation 
                         parameters proved to be a feasible alternative to reduce the 
                         subjectivity and the human effort in the choice of segmentation 
                         parameters as compared to the trial-and error approach.",
                  doi = "10.1080/10106049.2019.1690056",
                  url = "http://dx.doi.org/10.1080/10106049.2019.1690056",
                 issn = "1010-6049",
             language = "en",
           targetfile = "sothe_automatic.pdf",
        urlaccessdate = "09 maio 2024"
}