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@Article{ContiAra˙Cunh:2016:SpDaMo,
               author = "Conti, Luis Am{\'e}rico and Ara{\'u}jo, Carlos Alberto Sampaio 
                         de and Cunha-Lignon, Mar{\'{\i}}lia",
          affiliation = "{Universidade de S{\~a}o Paulo (USP)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {Universidade Estadual Paulista 
                         (UNESP)}",
                title = "Spatial database modeling for mangrove forests mapping; example of 
                         two estuarine systems in Brazil",
              journal = "Modelling Earth Systems and Enrironment",
                 year = "2016",
               volume = "2",
               number = "73",
                month = "June",
             keywords = "Remote sensing GIS Time change detection Subtropical wetland 
                         Coastal zone management Conservation Geospatial database Intr.",
             abstract = "This work considers mangrove cover changes in two subtropical 
                         estuaries in the southeastern coast of Brazil: Canane┤ia-Iguape 
                         Coastal System and Santos Estuarine System. A sequence of Landsat 
                         images from 1985 to 2014 from both areas was segmented, classified 
                         and analyzed in order to develop a systematic GIS approach for 
                         identifying and characterizing mangrove fragments in such 
                         estuaries and how they change over time. The main goal of our work 
                         is to propose a unified hierarchical spatial database model in a 
                         GIS framework developed to incorporate different types of spatial 
                         information such as spectral (e.g. vegetation indices), spatial 
                         (e.g. fragmentation indices) and temporal (e.g. change detection) 
                         at different scales. The examples analyzed showed that changes and 
                         fluctuations in mangrove habitats could be identified and 
                         characterized revealing potential tools for handling and analyzing 
                         data focused on environmental monitoring and the coastal resource 
                         protection and conservation.",
                  doi = "10.1007/s40808-016-0129-3",
                  url = "http://dx.doi.org/10.1007/s40808-016-0129-3",
                 issn = "2363-6203",
             language = "en",
           targetfile = "conti_spatial.pdf",
        urlaccessdate = "25 nov. 2020"
}


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