Multivariate geostatistical application for climate characterization of Minas Gerais State, Brazil
Autor(a) principal: | |
---|---|
Data de Publicação: | 2010 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFLA |
Texto Completo: | http://link.springer.com/article/10.1007%2Fs00704-010-0273-z http://repositorio.ufla.br/jspui/handle/1/869 |
Resumo: | The objective of the present study was to assess for Minas Gerais the cokriging methodology, in order to characterize the spatial variability of Thornthwaite annual moisture index, annual rainfall, and average annual air temperature, based on geographical coordinates, altitude, latitude, and longitude. The climatic element data referred to 39 INMET climatic stations located in the state of Minas Gerais and in nearby areas and the covariables altitude, latitude, and longitude to the SRTM digital elevation model. Spatial dependence of data was observed through spherical cross semivariograms and cross covariance models. Box–Cox and log transformation were applied to the positive variables. In these situations, kriged predictions were back-transformed and returned to the same scale as the original data. Trend was removed using global polynomial interpolation. Universal simple cokriging best characterized the climate variables without tendentiousness and with high accuracy and precision when compared to simple cokriging. Considering the satisfactory implementation of universal simple cokriging for the monitoring of climatic elements, this methodology presents enormous potential for the characterization of climate change impact in Minas Gerais state. |
id |
UFLA_963f10fa517890e35dbeecc2841fd9bd |
---|---|
oai_identifier_str |
oai:localhost:1/869 |
network_acronym_str |
UFLA |
network_name_str |
Repositório Institucional da UFLA |
repository_id_str |
|
spelling |
Multivariate geostatistical application for climate characterization of Minas Gerais State, BrazilRemote Sensing,Nulti sensingThe objective of the present study was to assess for Minas Gerais the cokriging methodology, in order to characterize the spatial variability of Thornthwaite annual moisture index, annual rainfall, and average annual air temperature, based on geographical coordinates, altitude, latitude, and longitude. The climatic element data referred to 39 INMET climatic stations located in the state of Minas Gerais and in nearby areas and the covariables altitude, latitude, and longitude to the SRTM digital elevation model. Spatial dependence of data was observed through spherical cross semivariograms and cross covariance models. Box–Cox and log transformation were applied to the positive variables. In these situations, kriged predictions were back-transformed and returned to the same scale as the original data. Trend was removed using global polynomial interpolation. Universal simple cokriging best characterized the climate variables without tendentiousness and with high accuracy and precision when compared to simple cokriging. Considering the satisfactory implementation of universal simple cokriging for the monitoring of climatic elements, this methodology presents enormous potential for the characterization of climate change impact in Minas Gerais state.Springer2013-08-06T15:18:16Z2013-08-06T15:18:16Z2010info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleCARVALHO, L. G. et al. Multivariate geostatistical application for climate characterization of Minas Gerais State, Brazil. Theoretical and Applied Climatology, Wien, v. 102, n. 3/4, p. 471-428, Nov. 2010.http://link.springer.com/article/10.1007%2Fs00704-010-0273-zhttp://repositorio.ufla.br/jspui/handle/1/869http://link.springer.com/article/10.1007%2Fs00704-010-0273-zTheor Appl Climatolreponame:Repositório Institucional da UFLAinstname:Universidade Federal de Lavras (UFLA)instacron:UFLAhttp://link.springer.com/article/10.1007%2Fs00704-010-0273-zinfo:eu-repo/semantics/openAccessCarvalho, Luiz G. deAlves, Marcelo de CarvalhoOliveira, Marcelo S. deVianello, Rubens L.Sediyama, Gilberto C.Carvalho, Luis Marcelo Tavares deeng2013-09-04T18:43:59Zoai:localhost:1/869Repositório InstitucionalPUBhttp://repositorio.ufla.br/oai/requestnivaldo@ufla.br || repositorio.biblioteca@ufla.bropendoar:2013-09-04T18:43:59Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)false |
dc.title.none.fl_str_mv |
Multivariate geostatistical application for climate characterization of Minas Gerais State, Brazil |
title |
Multivariate geostatistical application for climate characterization of Minas Gerais State, Brazil |
spellingShingle |
Multivariate geostatistical application for climate characterization of Minas Gerais State, Brazil Carvalho, Luiz G. de Remote Sensing, Nulti sensing |
title_short |
Multivariate geostatistical application for climate characterization of Minas Gerais State, Brazil |
title_full |
Multivariate geostatistical application for climate characterization of Minas Gerais State, Brazil |
title_fullStr |
Multivariate geostatistical application for climate characterization of Minas Gerais State, Brazil |
title_full_unstemmed |
Multivariate geostatistical application for climate characterization of Minas Gerais State, Brazil |
title_sort |
Multivariate geostatistical application for climate characterization of Minas Gerais State, Brazil |
author |
Carvalho, Luiz G. de |
author_facet |
Carvalho, Luiz G. de Alves, Marcelo de Carvalho Oliveira, Marcelo S. de Vianello, Rubens L. Sediyama, Gilberto C. Carvalho, Luis Marcelo Tavares de |
author_role |
author |
author2 |
Alves, Marcelo de Carvalho Oliveira, Marcelo S. de Vianello, Rubens L. Sediyama, Gilberto C. Carvalho, Luis Marcelo Tavares de |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Carvalho, Luiz G. de Alves, Marcelo de Carvalho Oliveira, Marcelo S. de Vianello, Rubens L. Sediyama, Gilberto C. Carvalho, Luis Marcelo Tavares de |
dc.subject.por.fl_str_mv |
Remote Sensing, Nulti sensing |
topic |
Remote Sensing, Nulti sensing |
description |
The objective of the present study was to assess for Minas Gerais the cokriging methodology, in order to characterize the spatial variability of Thornthwaite annual moisture index, annual rainfall, and average annual air temperature, based on geographical coordinates, altitude, latitude, and longitude. The climatic element data referred to 39 INMET climatic stations located in the state of Minas Gerais and in nearby areas and the covariables altitude, latitude, and longitude to the SRTM digital elevation model. Spatial dependence of data was observed through spherical cross semivariograms and cross covariance models. Box–Cox and log transformation were applied to the positive variables. In these situations, kriged predictions were back-transformed and returned to the same scale as the original data. Trend was removed using global polynomial interpolation. Universal simple cokriging best characterized the climate variables without tendentiousness and with high accuracy and precision when compared to simple cokriging. Considering the satisfactory implementation of universal simple cokriging for the monitoring of climatic elements, this methodology presents enormous potential for the characterization of climate change impact in Minas Gerais state. |
publishDate |
2010 |
dc.date.none.fl_str_mv |
2010 2013-08-06T15:18:16Z 2013-08-06T15:18:16Z |
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 |
CARVALHO, L. G. et al. Multivariate geostatistical application for climate characterization of Minas Gerais State, Brazil. Theoretical and Applied Climatology, Wien, v. 102, n. 3/4, p. 471-428, Nov. 2010. http://link.springer.com/article/10.1007%2Fs00704-010-0273-z http://repositorio.ufla.br/jspui/handle/1/869 http://link.springer.com/article/10.1007%2Fs00704-010-0273-z |
identifier_str_mv |
CARVALHO, L. G. et al. Multivariate geostatistical application for climate characterization of Minas Gerais State, Brazil. Theoretical and Applied Climatology, Wien, v. 102, n. 3/4, p. 471-428, Nov. 2010. |
url |
http://link.springer.com/article/10.1007%2Fs00704-010-0273-z http://repositorio.ufla.br/jspui/handle/1/869 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
http://link.springer.com/article/10.1007%2Fs00704-010-0273-z info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
http://link.springer.com/article/10.1007%2Fs00704-010-0273-z |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
Springer |
publisher.none.fl_str_mv |
Springer |
dc.source.none.fl_str_mv |
Theor Appl Climatol reponame:Repositório Institucional da UFLA instname:Universidade Federal de Lavras (UFLA) instacron:UFLA |
instname_str |
Universidade Federal de Lavras (UFLA) |
instacron_str |
UFLA |
institution |
UFLA |
reponame_str |
Repositório Institucional da UFLA |
collection |
Repositório Institucional da UFLA |
repository.name.fl_str_mv |
Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA) |
repository.mail.fl_str_mv |
nivaldo@ufla.br || repositorio.biblioteca@ufla.br |
_version_ |
1807835050519035904 |