@InProceedings{RibeiroAmarMont:2017:GeEsDe,
               author = "Ribeiro, Renata Maciel and Amaral, Silvana and Monteiro, 
                         Ant{\^o}nio Miguel Vieira",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)}",
                title = "A desconcentra{\c{c}}{\~a}o da popula{\c{c}}{\~a}o urbana nas 
                         cidades paraenses: geoinforma{\c{c}}{\~a}o no estudo do 
                         descompasso entre o crescimento da popula{\c{c}}{\~a}o e da 
                         extens{\~a}o de {\'a}reas urbanas",
            booktitle = "Anais...",
                 year = "2017",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "6123--6130",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 18. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "Trends of urbanization and cities growth in the Brazilian Amazon 
                         are associated with economic activities that reflect the pressure 
                         from international markets on trading of export products. Current 
                         economic activities define the shape of the land cover, urban 
                         sprawl and also how fast a city grows. Where land cover change and 
                         local elite authors promote land commodification, it will also 
                         cause urban space remodel, as consequence, altering urban 
                         population density. This paper aims to study the evolution of 
                         urbanized areas and the relationship with population growth, using 
                         remote sensing data and geoinformation techniques to identify 
                         variations in population density. Eight municipalities in the 
                         southwestern of Para state were selected as study area: 
                         Santar{\'e}m, Medicil{\^a}ndia, Uruar{\'a}, Placas, 
                         Rur{\'o}polis, Aveiro, Belterra e Trair{\~a}o. TerraClass land 
                         cover mapping for 2008, 2010, 2012 and 2014 were used to evaluate 
                         the urban area class evolution, and IBGE census and estimated 
                         population data was used for population counts of the same period. 
                         Using GIS and geographical data base for the spatial analysis, we 
                         calculate the urban demographic density of the municipalities. The 
                         results were validated based on field work data, characterizing 
                         urban sprawl by new urbanized allotments, housing estates, 
                         condominiums and informal spontaneous occupation. It was observed 
                         an unexpected general decrease of urban demographic density values 
                         along these years: urban areas increased faster than urban 
                         population. The resulted typology of urban population density for 
                         Amazon municipalities provides information that will support 
                         studies about underlying economic factors of the urbanization, and 
                         further urban planning discussions.",
  conference-location = "Santos",
      conference-year = "28-31 maio 2017",
                 isbn = "978-85-17-00088-1",
                label = "59346",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3PSMCBR",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PSMCBR",
           targetfile = "59346.pdf",
                 type = "Urbaniza{\c{c}}{\~a}o",
        urlaccessdate = "27 abr. 2024"
}