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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitemarte.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Repositoryltid.inpe.br/sbsr/2004/11.22.22.31
Last Update2005:03.29.12.18.18 (UTC) administrator
Metadata Repositoryltid.inpe.br/sbsr/2004/11.22.22.31.44
Metadata Last Update2018:06.06.02.42.57 (UTC) administrator
Secondary KeyINPE-12746-PRE/8036
ISBN85-17-00018-8
Citation KeyAlmeidaGler:2005:CeAuNe
TitleCellular automata and neural networks as a modelling framework for the simulation of urban land use change
FormatCD-ROM, On-line.
Year2005
Access Date2024, May 05
Secondary TypePRE CN
Number of Files1
Size1166 KiB
2. Context
Author1 Almeida, Cláudia Maria de
2 Gleriani, José Marinaldo
Resume Identifier1 8JMKD3MGP5W/3C9JGS3
Group1 DSR-INPE-MCT-BR
Affiliation1 Instituto Nacional de Pesquisas Espaciais (INPE)
2 Universidade Federal de Viçosa (UFV)
Author e-Mail Address1 almeida@ltid.inpe.br
EditorEpiphanio, José Carlos Neves
Fonseca, Leila Maria Garcia
e-Mail Addressalmeida@ltid.inpe.br
Conference NameSimpósio Brasileiro de Sensoriamento Remoto, 12 (SBSR)
Conference LocationGoiânia
Date16-21 abr. 2005
PublisherINPE
Publisher CitySão José dos Campos
Pages3697-3706
Book TitleAnais
Tertiary TypeArtigos
OrganizationInstituto Nacional de Pesquisas Espaciais
History (UTC)2005-06-23 20:12:42 :: sbsr -> administrator ::
2009-06-03 16:04:21 :: administrator -> sbsr ::
2009-06-30 14:26:19 :: sbsr -> erich@sid.inpe.br ::
2010-05-14 02:47:10 :: erich@sid.inpe.br -> marciana ::
2011-02-16 14:00:27 :: marciana -> administrator :: 2005
2018-06-06 02:42:57 :: administrator -> :: 2005
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Keywordsurban modelling
land use dynamics
neural networks
cellular automata
town planning
AbstractEmpirical models designed to simulate and predict urban land use change are generally based on the utilisation of statistical techniques to reckon the land use change probabilities. In contrast to these methods, artificial neural networks arise as an alternative to assess such probabilities by means of non-parametric approaches. This work introduces a simulation experiment on urban land use change in which a supervised back-propagation neural network has been employed in the parameterisation of the simulation model. The thereof estimated spatial land use transition probabilities feed a cellular automaton (CA) simulation model, based on stochastic transition rules. The model has been tested in a medium-sized town in the midwest of São Paulo State, Piracicaba. A series of simulation outputs for the case study town in the period 1985-1999 were produced, and statistical validation tests were then conducted for the best results, upon basis of a multiple resolution fitting procedure.
AreaSRE
TypePlanejamento Urbano e Regional
Arrangementurlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDSR > Cellular automata and...
doc Directory Contentaccess
source Directory Content
almeidasbsr2005.doc 22/11/2004 22:31 537.5 KiB 
agreement Directory Contentthere are no files
4. Conditions of access and use
data URLhttp://urlib.net/ibi/ltid.inpe.br/sbsr/2004/11.22.22.31
zipped data URLhttp://urlib.net/zip/ltid.inpe.br/sbsr/2004/11.22.22.31
LanguageInglês
Target File3697.pdf
User Groupadministrator
erich@sid.inpe.br
Visibilityshown
5. Allied materials
Mirror Repositorydpi.inpe.br/marte@80/2007/10.17.19.59
Next Higher Units8JMKD3MGPCW/3ER446E
Host Collectiondpi.inpe.br/banon/2003/12.10.19.30
6. Notes
Mark1
Empty Fieldsarchivingpolicy archivist callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination documentstage doi edition identifier issn label lineage nextedition notes numberofvolumes orcid parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission rightsholder schedulinginformation secondarydate secondarymark serieseditor session shorttitle sponsor subject tertiarymark url versiontype volume


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