<?xml version="1.0" encoding="ISO-8859-1"?>
<metadatalist>
	<metadata ReferenceType="Journal Article">
		<site>mtc-m12.sid.inpe.br 800</site>
		<holdercode>{isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S}</holdercode>
		<identifier>6qtX3pFwXQZ3r59YD6/Hprx2</identifier>
		<repository>sid.inpe.br/iris@1912/2005/09.08.16.59</repository>
		<lastupdate>2006:07.26.14.35.12 sid.inpe.br/banon/2001/04.06.10.52 marciana</lastupdate>
		<metadatarepository>sid.inpe.br/iris@1912/2005/09.08.16.59.50</metadatarepository>
		<metadatalastupdate>2018:06.05.00.40.31 sid.inpe.br/banon/2001/04.06.10.52 administrator {D 2005}</metadatalastupdate>
		<secondarykey>INPE-13061-PRE/8327</secondarykey>
		<doi>10.1080/01431160512331316865</doi>
		<issn>0143-1161</issn>
		<citationkey>AlmeidaMoCâSoCePeBa:2005:GIReSe</citationkey>
		<title>GIS and remote sensing as tools for the simulation of urban land-use change</title>
		<year>2005</year>
		<month>Feb.</month>
		<typeofwork>journal article</typeofwork>
		<secondarytype>PRE PI</secondarytype>
		<numberoffiles>1</numberoffiles>
		<size>445 KiB</size>
		<author>Almeida, Cláudia Maria de,</author>
		<author>Monteiro, Antonio Miguel Vieira,</author>
		<author>Câmara, Gilberto,</author>
		<author>Soares-Filho, Britaldo Silveira,</author>
		<author>Cerqueira, Custavo Coutinho,</author>
		<author>Pennachin, Cassio Lopes,</author>
		<author>Batty, Michael,</author>
		<resumeid></resumeid>
		<resumeid>8JMKD3MGP5W/3C9JGJN</resumeid>
		<group>DSR-INPE-MCT-BR</group>
		<group>DPI-INPE-MCT-BR</group>
		<group>DPI-INPE-MCT-BR</group>
		<group>CSR-INPE-MCT-BR</group>
		<group>CSR-INPE-MCT-BR</group>
		<group></group>
		<group>CASA-INPE-MCT-BR</group>
		<affiliation>Instituto Nacional de Pesquisas Espaciais, Divisão de Sensoriamento Remoto (INPE, DSR)</affiliation>
		<affiliation>Divisão de Processamento de Imagens</affiliation>
		<affiliation>Divisão de Processamento de Imagens</affiliation>
		<affiliation>UFMG</affiliation>
		<affiliation>UFMG</affiliation>
		<affiliation>Intelligenesis Brasil Ltda, Belo Horizonte</affiliation>
		<affiliation>UCL</affiliation>
		<e-mailaddress>almeida@dsr.inpe.br</e-mailaddress>
		<journal>International Journal of Remote Sensing</journal>
		<volume>26</volume>
		<number>4</number>
		<pages>759-774</pages>
		<transferableflag>1</transferableflag>
		<contenttype>External Contribution</contenttype>
		<versiontype>publisher</versiontype>
		<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.</keywords>
		<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.</abstract>
		<area>SRE</area>
		<language>en</language>
		<targetfile>IJRS.pdf</targetfile>
		<usergroup>administrator</usergroup>
		<usergroup>banon</usergroup>
		<usergroup>jefferson</usergroup>
		<usergroup>sergio</usergroup>
		<readergroup>administrator</readergroup>
		<readergroup>marciana</readergroup>
		<visibility>shown</visibility>
		<copyholder>SID/SCD</copyholder>
		<archivingpolicy>denypublisher denyfinaldraft12</archivingpolicy>
		<readpermission>deny from all and allow from 150.163</readpermission>
		<documentstage>not transferred</documentstage>
		<nexthigherunit>8JMKD3MGPCW/3EQCCU5</nexthigherunit>
		<nexthigherunit>8JMKD3MGPCW/3ER446E</nexthigherunit>
		<citingitemlist>sid.inpe.br/mtc-m21/2012/07.13.14.40.32 1</citingitemlist>
		<dissemination>WEBSCI; PORTALCAPES; MGA; COMPENDEX.</dissemination>
		<hostcollection>sid.inpe.br/banon/2001/04.06.10.52</hostcollection>
		<username>marciana</username>
		<lasthostcollection>sid.inpe.br/banon/2001/04.06.10.52</lasthostcollection>
		<url>http://mtc-m12.sid.inpe.br/rep-/sid.inpe.br/iris@1912/2005/09.08.16.59</url>
	</metadata>
</metadatalist>