Mixed-effects modeling for analyzing land use change in the Brazilian Pantanal subregion of Cáceres
Autor(a) principal: | |
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Data de Publicação: | 2019 |
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/1822/73239 |
Resumo: | In this paper, we discuss the use of mixed-effects modeling for analyzing land use change in the Brazilian Pantanal subregion of Cáceres, Mato Grosso State, Brazil. The proposed method, easily extendable to similar case studies, consisted of two steps. First, spatio-temporal data, consisting of Landsat images of the study area from 1993, 1999, 2004, 2009, and 2015, were obtained. The data are polygons with numerical data (year and area) and categorical data (land use and soil type). Second, we analyzed the data using four linear mixed models able to incorporate both the fixed and the random effects underlying the clustered data. The proposed models allowed analyzed complex data structures, such as multilevel data, taking into account particularities of each land use type as a function of the year. The models were fitted to identify land use changes over time. In particular, the point estimate of the random slope in the case of the Pasture class is 0.34, which indicates an increase of about 40% in hectare and the point estimate for the Forest is −0.32, which indicates a decrease of about 27% in hectare in next 5 years. |
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Mixed-effects modeling for analyzing land use change in the Brazilian Pantanal subregion of CáceresAnthropogenic processesRemote sensingStatistical modelsVegetation coverWetlandCiências Naturais::MatemáticasScience & TechnologyIn this paper, we discuss the use of mixed-effects modeling for analyzing land use change in the Brazilian Pantanal subregion of Cáceres, Mato Grosso State, Brazil. The proposed method, easily extendable to similar case studies, consisted of two steps. First, spatio-temporal data, consisting of Landsat images of the study area from 1993, 1999, 2004, 2009, and 2015, were obtained. The data are polygons with numerical data (year and area) and categorical data (land use and soil type). Second, we analyzed the data using four linear mixed models able to incorporate both the fixed and the random effects underlying the clustered data. The proposed models allowed analyzed complex data structures, such as multilevel data, taking into account particularities of each land use type as a function of the year. The models were fitted to identify land use changes over time. In particular, the point estimate of the random slope in the case of the Pasture class is 0.34, which indicates an increase of about 40% in hectare and the point estimate for the Forest is −0.32, which indicates a decrease of about 27% in hectare in next 5 years.This research was financed by the Mato Grosso State Research Foundation, Brazil (FAPEMAT).ElsevierUniversidade do MinhoGalvanin, Edinéia A. S.Menezes, RaquelPereira, Murilo H. X.Neves, Sandra M. A. S.20192019-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/1822/73239engGalvanin, E. A. S., Menezes, R., Pereira, M. H. X., & Neves, S. M. A. S. (2019). Mixed-effects modeling for analyzing land use change in the Brazilian Pantanal subregion of Cáceres. Remote Sensing Applications: Society and Environment, 13, 408-414. doi: https://doi.org/10.1016/j.rsase.2018.12.0082352-938510.1016/j.rsase.2018.12.008https://www.sciencedirect.com/science/article/pii/S2352938518300600info: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:RCAAP2023-07-21T12:31:21Zoai:repositorium.sdum.uminho.pt:1822/73239Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T19:26:36.731061Repositório 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 |
Mixed-effects modeling for analyzing land use change in the Brazilian Pantanal subregion of Cáceres |
title |
Mixed-effects modeling for analyzing land use change in the Brazilian Pantanal subregion of Cáceres |
spellingShingle |
Mixed-effects modeling for analyzing land use change in the Brazilian Pantanal subregion of Cáceres Galvanin, Edinéia A. S. Anthropogenic processes Remote sensing Statistical models Vegetation cover Wetland Ciências Naturais::Matemáticas Science & Technology |
title_short |
Mixed-effects modeling for analyzing land use change in the Brazilian Pantanal subregion of Cáceres |
title_full |
Mixed-effects modeling for analyzing land use change in the Brazilian Pantanal subregion of Cáceres |
title_fullStr |
Mixed-effects modeling for analyzing land use change in the Brazilian Pantanal subregion of Cáceres |
title_full_unstemmed |
Mixed-effects modeling for analyzing land use change in the Brazilian Pantanal subregion of Cáceres |
title_sort |
Mixed-effects modeling for analyzing land use change in the Brazilian Pantanal subregion of Cáceres |
author |
Galvanin, Edinéia A. S. |
author_facet |
Galvanin, Edinéia A. S. Menezes, Raquel Pereira, Murilo H. X. Neves, Sandra M. A. S. |
author_role |
author |
author2 |
Menezes, Raquel Pereira, Murilo H. X. Neves, Sandra M. A. S. |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
Universidade do Minho |
dc.contributor.author.fl_str_mv |
Galvanin, Edinéia A. S. Menezes, Raquel Pereira, Murilo H. X. Neves, Sandra M. A. S. |
dc.subject.por.fl_str_mv |
Anthropogenic processes Remote sensing Statistical models Vegetation cover Wetland Ciências Naturais::Matemáticas Science & Technology |
topic |
Anthropogenic processes Remote sensing Statistical models Vegetation cover Wetland Ciências Naturais::Matemáticas Science & Technology |
description |
In this paper, we discuss the use of mixed-effects modeling for analyzing land use change in the Brazilian Pantanal subregion of Cáceres, Mato Grosso State, Brazil. The proposed method, easily extendable to similar case studies, consisted of two steps. First, spatio-temporal data, consisting of Landsat images of the study area from 1993, 1999, 2004, 2009, and 2015, were obtained. The data are polygons with numerical data (year and area) and categorical data (land use and soil type). Second, we analyzed the data using four linear mixed models able to incorporate both the fixed and the random effects underlying the clustered data. The proposed models allowed analyzed complex data structures, such as multilevel data, taking into account particularities of each land use type as a function of the year. The models were fitted to identify land use changes over time. In particular, the point estimate of the random slope in the case of the Pasture class is 0.34, which indicates an increase of about 40% in hectare and the point estimate for the Forest is −0.32, which indicates a decrease of about 27% in hectare in next 5 years. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019 2019-01-01T00:00:00Z |
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/1822/73239 |
url |
http://hdl.handle.net/1822/73239 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Galvanin, E. A. S., Menezes, R., Pereira, M. H. X., & Neves, S. M. A. S. (2019). Mixed-effects modeling for analyzing land use change in the Brazilian Pantanal subregion of Cáceres. Remote Sensing Applications: Society and Environment, 13, 408-414. doi: https://doi.org/10.1016/j.rsase.2018.12.008 2352-9385 10.1016/j.rsase.2018.12.008 https://www.sciencedirect.com/science/article/pii/S2352938518300600 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Elsevier |
publisher.none.fl_str_mv |
Elsevier |
dc.source.none.fl_str_mv |
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 |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799132754476007424 |