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1. Identity statement
Reference TypeJournal Article
Sitemtc-m16c.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier6qtX3pFwXQZGivnK3Y/ULGEt
Repositorysid.inpe.br/mtc-m18@80/2008/07.15.23.03   (restricted access)
Last Update2008:07.15.23.03.19 (UTC) administrator
Metadata Repositorysid.inpe.br/mtc-m18@80/2008/07.15.23.03.21
Metadata Last Update2018:06.04.04.05.23 (UTC) administrator
DOIhttp://dx.doi.org/10.1080/13658810701731168
ISSN1365-8816
1362-3087
Citation KeyAlmeidaGlerCastSoar:2008:UsNeNe
TitleUsing neural networks and cellular automata for modeling intra-urban land use dynamics
ProjectModelagem Dinâmica de Processos Sociais e Ambientais
Year2008
MonthNov
Access Date2024, Apr. 28
Secondary TypePRE PI
Number of Files1
Size885 KiB
2. Context
Author1 Almeida, Cláudia Maria de
2 Gleriani, José Marinaldo
3 Castejon, Emiliano Ferreira
4 Soares-Filho, Britaldo Silveira
Group1 DSR-OBT-INPE-MCT-BR
2
3 DPI-OBT-INPE-MCT-BR
Affiliation1 Instituto Nacional de Pesquisas Espaciais (INPE)
2 Universidade Federal de Viçosa
3 Instituto Nacional de Pesquisas Espaciais (INPE)
4 Universidade Federal de Minas Gerais
Author e-Mail Address1 almeida@dsr.inpe.br
2 gleriani@ufv.br
3 castejon@dpi.inpe.br
4 britaldo@csr.ufmg.br
e-Mail Addressalmeida@dsr.inpe.br
JournalInternational Journal of Geographical Information Science
Volume22
Number9
Pages943-963
Secondary MarkA_INTERDISCIPLINAR C_MATEMÁTICA_/_PROBABILIDADE_E_ESTATÍSTICA
History (UTC)2008-07-15 23:03:21 :: ariovaldo -> administrator ::
2018-06-04 04:05:23 :: administrator -> ariovaldo :: 2008
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
KeywordsNeural networks
Cellular automata
Urban modelling
Land-use dynamics
Fuzzy similarity measures
Town planning
AbstractEmpirical models designed to simulate and predict urban land-use change in real situations are generally based on the utilization of statistical techniques to compute 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 intra-urban land-use change in which a supervised back-propagation neural network has been employed in the parameterization of several biophysical and infrastructure variables considered in the simulation model. The spatial land-use transition probabilities estimated thereof 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 Satildeo Paulo State, Piracicaba. A series of simulation outputs for the case study town in the period 1985-1999 were generated, and statistical validation tests were then conducted for the best results, based on fuzzy similarity measures.
AreaSRE
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Contentthere are no files
4. Conditions of access and use
Languageen
Target FileIJGIS_Neural Networks.pdf
User Groupadministrator
ariovaldo
Visibilityshown
Read Permissiondeny from all and allow from 150.163
5. Allied materials
Next Higher Units8JMKD3MGPCW/3EQCCU5
8JMKD3MGPCW/3ER446E
URL (untrusted data)http://www.informaworld.com/smpp/content~content=a794967420~db=all?jumptype=alert&alerttype=author,email
DisseminationWEBSCI; PORTALCAPES.
Host Collectionsid.inpe.br/mtc-m18@80/2008/03.17.15.17
6. Notes
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