Geostatistical Approach for Spatial Interpolation of Meteorological Data
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Anais da Academia Brasileira de Ciências (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652016000602121 |
Resumo: | ABSTRACT Meteorological data are used in many studies, especially in planning, disaster management, water resources management, hydrology, agriculture and environment. Analyzing changes in meteorological variables is very important to understand a climate system and minimize the adverse effects of the climate changes. One of the main issues in meteorological analysis is the interpolation of spatial data. In recent years, with the developments in Geographical Information System (GIS) technology, the statistical methods have been integrated with GIS and geostatistical methods have constituted a strong alternative to deterministic methods in the interpolation and analysis of the spatial data. In this study; spatial distribution of precipitation and temperature of the Aegean Region in Turkey for years 1975, 1980, 1985, 1990, 1995, 2000, 2005 and 2010 were obtained by the Ordinary Kriging method which is one of the geostatistical interpolation methods, the changes realized in 5-year periods were determined and the results were statistically examined using cell and multivariate statistics. The results of this study show that it is necessary to pay attention to climate change in the precipitation regime of the Aegean Region. This study also demonstrates the usefulness of the geostatistical approach in meteorological studies. |
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Geostatistical Approach for Spatial Interpolation of Meteorological Datageostatistical interpolationgeographic information systemordinary krigingmeteorological dataABSTRACT Meteorological data are used in many studies, especially in planning, disaster management, water resources management, hydrology, agriculture and environment. Analyzing changes in meteorological variables is very important to understand a climate system and minimize the adverse effects of the climate changes. One of the main issues in meteorological analysis is the interpolation of spatial data. In recent years, with the developments in Geographical Information System (GIS) technology, the statistical methods have been integrated with GIS and geostatistical methods have constituted a strong alternative to deterministic methods in the interpolation and analysis of the spatial data. In this study; spatial distribution of precipitation and temperature of the Aegean Region in Turkey for years 1975, 1980, 1985, 1990, 1995, 2000, 2005 and 2010 were obtained by the Ordinary Kriging method which is one of the geostatistical interpolation methods, the changes realized in 5-year periods were determined and the results were statistically examined using cell and multivariate statistics. The results of this study show that it is necessary to pay attention to climate change in the precipitation regime of the Aegean Region. This study also demonstrates the usefulness of the geostatistical approach in meteorological studies.Academia Brasileira de Ciências2016-12-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652016000602121Anais da Academia Brasileira de Ciências v.88 n.4 2016reponame:Anais da Academia Brasileira de Ciências (Online)instname:Academia Brasileira de Ciências (ABC)instacron:ABC10.1590/0001-3765201620150103info:eu-repo/semantics/openAccessOZTURK,DERYAKILIC,FATMAGULeng2017-06-12T00:00:00Zoai:scielo:S0001-37652016000602121Revistahttp://www.scielo.br/aabchttps://old.scielo.br/oai/scielo-oai.php||aabc@abc.org.br1678-26900001-3765opendoar:2017-06-12T00:00Anais da Academia Brasileira de Ciências (Online) - Academia Brasileira de Ciências (ABC)false |
dc.title.none.fl_str_mv |
Geostatistical Approach for Spatial Interpolation of Meteorological Data |
title |
Geostatistical Approach for Spatial Interpolation of Meteorological Data |
spellingShingle |
Geostatistical Approach for Spatial Interpolation of Meteorological Data OZTURK,DERYA geostatistical interpolation geographic information system ordinary kriging meteorological data |
title_short |
Geostatistical Approach for Spatial Interpolation of Meteorological Data |
title_full |
Geostatistical Approach for Spatial Interpolation of Meteorological Data |
title_fullStr |
Geostatistical Approach for Spatial Interpolation of Meteorological Data |
title_full_unstemmed |
Geostatistical Approach for Spatial Interpolation of Meteorological Data |
title_sort |
Geostatistical Approach for Spatial Interpolation of Meteorological Data |
author |
OZTURK,DERYA |
author_facet |
OZTURK,DERYA KILIC,FATMAGUL |
author_role |
author |
author2 |
KILIC,FATMAGUL |
author2_role |
author |
dc.contributor.author.fl_str_mv |
OZTURK,DERYA KILIC,FATMAGUL |
dc.subject.por.fl_str_mv |
geostatistical interpolation geographic information system ordinary kriging meteorological data |
topic |
geostatistical interpolation geographic information system ordinary kriging meteorological data |
description |
ABSTRACT Meteorological data are used in many studies, especially in planning, disaster management, water resources management, hydrology, agriculture and environment. Analyzing changes in meteorological variables is very important to understand a climate system and minimize the adverse effects of the climate changes. One of the main issues in meteorological analysis is the interpolation of spatial data. In recent years, with the developments in Geographical Information System (GIS) technology, the statistical methods have been integrated with GIS and geostatistical methods have constituted a strong alternative to deterministic methods in the interpolation and analysis of the spatial data. In this study; spatial distribution of precipitation and temperature of the Aegean Region in Turkey for years 1975, 1980, 1985, 1990, 1995, 2000, 2005 and 2010 were obtained by the Ordinary Kriging method which is one of the geostatistical interpolation methods, the changes realized in 5-year periods were determined and the results were statistically examined using cell and multivariate statistics. The results of this study show that it is necessary to pay attention to climate change in the precipitation regime of the Aegean Region. This study also demonstrates the usefulness of the geostatistical approach in meteorological studies. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-12-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652016000602121 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652016000602121 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/0001-3765201620150103 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Academia Brasileira de Ciências |
publisher.none.fl_str_mv |
Academia Brasileira de Ciências |
dc.source.none.fl_str_mv |
Anais da Academia Brasileira de Ciências v.88 n.4 2016 reponame:Anais da Academia Brasileira de Ciências (Online) instname:Academia Brasileira de Ciências (ABC) instacron:ABC |
instname_str |
Academia Brasileira de Ciências (ABC) |
instacron_str |
ABC |
institution |
ABC |
reponame_str |
Anais da Academia Brasileira de Ciências (Online) |
collection |
Anais da Academia Brasileira de Ciências (Online) |
repository.name.fl_str_mv |
Anais da Academia Brasileira de Ciências (Online) - Academia Brasileira de Ciências (ABC) |
repository.mail.fl_str_mv |
||aabc@abc.org.br |
_version_ |
1754302862430568448 |