@Article{AlmeidaMoCāSoCePeBa:2005:GIReSe,
               author = "Almeida, Cl{\'a}udia Maria de and Monteiro, Antonio Miguel Vieira 
                         and C{\^a}mara, Gilberto and Soares-Filho, Britaldo Silveira and 
                         Cerqueira, Custavo Coutinho and Pennachin, Cassio Lopes and Batty, 
                         Michael",
          affiliation = "Instituto Nacional de Pesquisas Espaciais, Divis{\~a}o de 
                         Sensoriamento Remoto (INPE, DSR) and {Divis{\~a}o de 
                         Processamento de Imagens} and {Divis{\~a}o de Processamento de 
                         Imagens} and UFMG and UFMG and Intelligenesis Brasil Ltda, Belo 
                         Horizonte and UCL",
                title = "GIS and remote sensing as tools for the simulation of urban 
                         land-use change",
              journal = "International Journal of Remote Sensing",
                 year = "2005",
               volume = "26",
               number = "4",
                pages = "759--774",
                month = "Feb.",
             keywords = "Algorithms, Computer simulation, Economic and social effects, 
                         Forecasting, Geographic information systems, Image analysis, 
                         Mathematical models, Probability, Random processes, Remote 
                         sensing, Urban planning, Bayesian probabilistic methods, Remote 
                         sensing imagery, Urban land-use change, Urban structure, Land use, 
                         GIS, infrastructural development, land use change, remote sensing, 
                         socioeconomic status, urban area, Bauru, Brazil, Sao Paulo 
                         [Brazil], South America, Western Hemisphere, World.",
             abstract = "This paper is concerned with building up methodological guidelines 
                         for modelling urban land-use change through Geographical 
                         Information Sytems. remote sensing imagery and Bayesian 
                         probabilistic methods. A medium-sized town in the west of Sao 
                         Paulo State. Bauru. was adopted as a case studs. Its urban 
                         structure was converted into a 100m / 100m resolution grid and 
                         transition probabilities were calculated for each grid cell by 
                         means of the weights of evidence' statistical method and upon the 
                         basis of the information related to the technical infrastructure 
                         and socio-economic aspects of the town. The probabilities obtained 
                         from there fed a cellular automaton simulation model 
                         DINAMICA-developed by the Centre for Remote Sensing of the Federal 
                         University of Minas Gerais (CSR-UFMG). based on stochastic 
                         transition algorithms. Different simulation outputs for the case 
                         study town in the period 1979 1988 were generated. and statistical 
                         validation tests were then conducted for the best results. 
                         employing a multiple resolution fitting procedure. This modelling 
                         experiment revealed the plausibility of adopting Bayesian 
                         empirical methods based on the available knowledge of technical 
                         infrastructure and socio-economic status to simulate urban 
                         land-use change. It indicates their possible further applicability 
                         for generating forecasts of growth trends Brazilian cities and 
                         cities.",
           copyholder = "SID/SCD",
                  doi = "10.1080/01431160512331316865",
                  url = "http://dx.doi.org/10.1080/01431160512331316865",
                 issn = "0143-1161",
             language = "en",
           targetfile = "IJRS.pdf",
        urlaccessdate = "03 maio 2024"
}