@InProceedings{SianiCaFrLoAmMoKo:2015:CaAPMa,
               author = "Siani, Sacha Maru{\~a} Ortiz and Campos, J{\'a}rvis and 
                         Fran{\c{c}}a, David Guimar{\~a}es Monteiro and Lotte, Rodolfo 
                         Georjute and Amaral, Silvana and Monteiro, Ant{\^o}nio Miguel 
                         Vieira and Korting, Thales Sehn",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {} and 
                         {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 {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)}",
                title = "Land-cover classification of an intra-urban environment using 
                         high-resolution images and geographic object-based image analysis: 
                         the case of APA Mananciais do Rio Para{\'{\i}}ba do Sul",
            booktitle = "Anais...",
                 year = "2015",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "997--1004",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 17. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "Protected areas of sustainable use such as the Environmental 
                         Protection Areas (APA) encompass urban areas. Because the 
                         characteristic urban spaces are under dynamic changes, they 
                         usually entail problems related to planning land cover. Such areas 
                         are fragile, especially when located inside protected areas, so it 
                         is necessary to monitor and evaluate them. Remote sensing data 
                         provides important information for urban planning and management 
                         issues, and have a great potential to assist conservation unit 
                         managers in monitoring such protected areas. Urban environments 
                         are characterized by high spectral and spatial heterogeneity and, 
                         consequently, most urban pixels in moderate resolution imagery 
                         contain multiple land-cover materials. The objective of this paper 
                         is to demonstrate the capability of RapidEye sensor data, for the 
                         intra-urban scale classification of land cover in protected areas, 
                         and to develop a semi-automatic classification method based on 
                         geographic object-based image analysis and data mining techniques, 
                         for efficiently identifying small changes in urban areas. The APA 
                         of Mananciais do Rio Para{\'{\i}}ba do Sul (APA-MRPS), aimed to 
                         preserve the water sources for more than 15 million people, was 
                         selected as study site. The results showed that RapidEye data and 
                         the methodology used were effective in classifying constructed 
                         areas, enabling the identification of small changes in land cover. 
                         The data and methodology may be able to assist managers in the 
                         monitoring and evaluation processes of protected areas, especially 
                         APAs.",
  conference-location = "Jo{\~a}o Pessoa",
      conference-year = "25-29 abr. 2015",
                 isbn = "978-85-17-0076-8",
                label = "188",
             language = "en",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3JM47L3",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3JM47L3",
           targetfile = "p0188.pdf",
                 type = "Classifica{\c{c}}{\~a}o e minera{\c{c}}{\~a}o de dados",
        urlaccessdate = "27 abr. 2024"
}