Evaluation of Stochastic Geographical Matters
Autor(a) principal: | |
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Data de Publicação: | 2011 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10362/64858 |
Resumo: | Negreiros, J., Costa, A. C., & Painho, M. (2011). Evaluation of Stochastic Geographical Matters: Morphologic Geostatistics, Conditional Sequential Simulation and Geographical Weighted Regression. Trends in Applied Science Research, 6(3), 237-255. https://doi.org/10.3923/tasr.2011.237.255 |
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Evaluation of Stochastic Geographical MattersMorphologic Geostatistics, Conditional Sequential Simulation and Geographical Weighted RegressionNegreiros, J., Costa, A. C., & Painho, M. (2011). Evaluation of Stochastic Geographical Matters: Morphologic Geostatistics, Conditional Sequential Simulation and Geographical Weighted Regression. Trends in Applied Science Research, 6(3), 237-255. https://doi.org/10.3923/tasr.2011.237.255The aim of this study is to highlight four main stochastic modeling procedures for spatial data within Geographical Information Systems (GIS) which are still unknown by most GIS users: Morphologic Geostatistics (MG), Geographical Weighted Regression (GWR), Conditional Sequential Simulation (CSS) for continuous and categorical variables. Sequential simulation, for instance, is a widely used geostatistical tool for obtaining a set of equiprobable simulated realizations of variables from natural phenomena, conditional to observed data, honoring their spatial distribution and uncertainty. While Gaussian simulation involves the generation of many independent realizations of a Gaussian random field but requiring the transformation of original variables, direct sequential simulation (DSS) has been proposed for simulating directly in the original data space and does not rely on multi-Gaussian assumptions. A generic Pb contamination dataset is used to illustrate the MG and CSS procedures. Major relationships among Kriging estimation, spatial autocorrelation, geographical regression and the missing data issue are also reviewed in the last section.NOVA Information Management School (NOVA IMS)RUNNegreiros, JoãoCosta, Ana CristinaPainho, Marco2019-03-28T23:16:36Z2011-01-012011-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10362/64858engPURE: 204459https://doi.org/10.3923/tasr.2011.237.255info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T04:30:50Zoai:run.unl.pt:10362/64858Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:34:13.037108Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Evaluation of Stochastic Geographical Matters Morphologic Geostatistics, Conditional Sequential Simulation and Geographical Weighted Regression |
title |
Evaluation of Stochastic Geographical Matters |
spellingShingle |
Evaluation of Stochastic Geographical Matters Negreiros, João |
title_short |
Evaluation of Stochastic Geographical Matters |
title_full |
Evaluation of Stochastic Geographical Matters |
title_fullStr |
Evaluation of Stochastic Geographical Matters |
title_full_unstemmed |
Evaluation of Stochastic Geographical Matters |
title_sort |
Evaluation of Stochastic Geographical Matters |
author |
Negreiros, João |
author_facet |
Negreiros, João Costa, Ana Cristina Painho, Marco |
author_role |
author |
author2 |
Costa, Ana Cristina Painho, Marco |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
NOVA Information Management School (NOVA IMS) RUN |
dc.contributor.author.fl_str_mv |
Negreiros, João Costa, Ana Cristina Painho, Marco |
description |
Negreiros, J., Costa, A. C., & Painho, M. (2011). Evaluation of Stochastic Geographical Matters: Morphologic Geostatistics, Conditional Sequential Simulation and Geographical Weighted Regression. Trends in Applied Science Research, 6(3), 237-255. https://doi.org/10.3923/tasr.2011.237.255 |
publishDate |
2011 |
dc.date.none.fl_str_mv |
2011-01-01 2011-01-01T00:00:00Z 2019-03-28T23:16:36Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10362/64858 |
url |
http://hdl.handle.net/10362/64858 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
PURE: 204459 https://doi.org/10.3923/tasr.2011.237.255 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
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openAccess |
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application/pdf |
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reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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