LEAF AREA INDEX MONITORING AND PROTECTIONG THROUGH REMOTE SENSING IN THE ITATIAIA NATIONAL PARK

Detalhes bibliográficos
Autor(a) principal: Nassur, Otávio Augusto Carvalho
Data de Publicação: 2016
Outros Autores: Ferreira, Elizabeth, Sáfadi, Thelma, Dantas, Antônio Augusto Aguilar
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Cerne (Online)
Texto Completo: https://cerne.ufla.br/site/index.php/CERNE/article/view/1098
Resumo: Satellite images of earth observation and meteorological sensors have been used for monitoring land use. Recently products obtained from satellite images have been disseminated, among them, several vegetation indices. EUMETSAT, through the Land –SAF, offers, among other products, the Leaf Area Index (LAI). Daily LAI products have beem acquired in raster format corresponding from 01/01/2010 to 30/12/2010. From a pixel located in the central portion of the Itatiaia National Park, a time series was generated, which was analyzed aiming at assessing the dynamics of leaf area index. The tendency observed in this period indicates that LAI decreased during 2010. It was possible to observe that changes in vegetation have close relationship with changes in rainfall and fires that affect the region. The ARIMA (7 1 0) model was able to describe the behavior of the LAI series, producing white noise and indicating correlations among 1, 6 and 7 days among the past observations. The prediction for future values resulted in an average error of 2.74%, indicating the potential of the model to identify changes in vegetation. Models of ARIMA class, in conjunction with orbital products, stand out as promises for use in the analysis of the vegetation of protected areas.
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spelling LEAF AREA INDEX MONITORING AND PROTECTIONG THROUGH REMOTE SENSING IN THE ITATIAIA NATIONAL PARKConservation unitsleaf area indexARIMA Modeltime series.Satellite images of earth observation and meteorological sensors have been used for monitoring land use. Recently products obtained from satellite images have been disseminated, among them, several vegetation indices. EUMETSAT, through the Land –SAF, offers, among other products, the Leaf Area Index (LAI). Daily LAI products have beem acquired in raster format corresponding from 01/01/2010 to 30/12/2010. From a pixel located in the central portion of the Itatiaia National Park, a time series was generated, which was analyzed aiming at assessing the dynamics of leaf area index. The tendency observed in this period indicates that LAI decreased during 2010. It was possible to observe that changes in vegetation have close relationship with changes in rainfall and fires that affect the region. The ARIMA (7 1 0) model was able to describe the behavior of the LAI series, producing white noise and indicating correlations among 1, 6 and 7 days among the past observations. The prediction for future values resulted in an average error of 2.74%, indicating the potential of the model to identify changes in vegetation. Models of ARIMA class, in conjunction with orbital products, stand out as promises for use in the analysis of the vegetation of protected areas.CERNECERNE2016-04-19info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://cerne.ufla.br/site/index.php/CERNE/article/view/1098CERNE; Vol. 21 No. 3 (2015); 511-517CERNE; v. 21 n. 3 (2015); 511-5172317-63420104-7760reponame:Cerne (Online)instname:Universidade Federal de Lavras (UFLA)instacron:UFLAenghttps://cerne.ufla.br/site/index.php/CERNE/article/view/1098/860Copyright (c) 2016 CERNEinfo:eu-repo/semantics/openAccessNassur, Otávio Augusto CarvalhoFerreira, ElizabethSáfadi, ThelmaDantas, Antônio Augusto Aguilar2016-04-19T11:33:20Zoai:cerne.ufla.br:article/1098Revistahttps://cerne.ufla.br/site/index.php/CERNEPUBhttps://cerne.ufla.br/site/index.php/CERNE/oaicerne@dcf.ufla.br||cerne@dcf.ufla.br2317-63420104-7760opendoar:2024-05-21T19:54:24.138387Cerne (Online) - Universidade Federal de Lavras (UFLA)true
dc.title.none.fl_str_mv LEAF AREA INDEX MONITORING AND PROTECTIONG THROUGH REMOTE SENSING IN THE ITATIAIA NATIONAL PARK
title LEAF AREA INDEX MONITORING AND PROTECTIONG THROUGH REMOTE SENSING IN THE ITATIAIA NATIONAL PARK
spellingShingle LEAF AREA INDEX MONITORING AND PROTECTIONG THROUGH REMOTE SENSING IN THE ITATIAIA NATIONAL PARK
Nassur, Otávio Augusto Carvalho
Conservation units
leaf area index
ARIMA Model
time series.
title_short LEAF AREA INDEX MONITORING AND PROTECTIONG THROUGH REMOTE SENSING IN THE ITATIAIA NATIONAL PARK
title_full LEAF AREA INDEX MONITORING AND PROTECTIONG THROUGH REMOTE SENSING IN THE ITATIAIA NATIONAL PARK
title_fullStr LEAF AREA INDEX MONITORING AND PROTECTIONG THROUGH REMOTE SENSING IN THE ITATIAIA NATIONAL PARK
title_full_unstemmed LEAF AREA INDEX MONITORING AND PROTECTIONG THROUGH REMOTE SENSING IN THE ITATIAIA NATIONAL PARK
title_sort LEAF AREA INDEX MONITORING AND PROTECTIONG THROUGH REMOTE SENSING IN THE ITATIAIA NATIONAL PARK
author Nassur, Otávio Augusto Carvalho
author_facet Nassur, Otávio Augusto Carvalho
Ferreira, Elizabeth
Sáfadi, Thelma
Dantas, Antônio Augusto Aguilar
author_role author
author2 Ferreira, Elizabeth
Sáfadi, Thelma
Dantas, Antônio Augusto Aguilar
author2_role author
author
author
dc.contributor.author.fl_str_mv Nassur, Otávio Augusto Carvalho
Ferreira, Elizabeth
Sáfadi, Thelma
Dantas, Antônio Augusto Aguilar
dc.subject.por.fl_str_mv Conservation units
leaf area index
ARIMA Model
time series.
topic Conservation units
leaf area index
ARIMA Model
time series.
description Satellite images of earth observation and meteorological sensors have been used for monitoring land use. Recently products obtained from satellite images have been disseminated, among them, several vegetation indices. EUMETSAT, through the Land –SAF, offers, among other products, the Leaf Area Index (LAI). Daily LAI products have beem acquired in raster format corresponding from 01/01/2010 to 30/12/2010. From a pixel located in the central portion of the Itatiaia National Park, a time series was generated, which was analyzed aiming at assessing the dynamics of leaf area index. The tendency observed in this period indicates that LAI decreased during 2010. It was possible to observe that changes in vegetation have close relationship with changes in rainfall and fires that affect the region. The ARIMA (7 1 0) model was able to describe the behavior of the LAI series, producing white noise and indicating correlations among 1, 6 and 7 days among the past observations. The prediction for future values resulted in an average error of 2.74%, indicating the potential of the model to identify changes in vegetation. Models of ARIMA class, in conjunction with orbital products, stand out as promises for use in the analysis of the vegetation of protected areas.
publishDate 2016
dc.date.none.fl_str_mv 2016-04-19
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://cerne.ufla.br/site/index.php/CERNE/article/view/1098
url https://cerne.ufla.br/site/index.php/CERNE/article/view/1098
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://cerne.ufla.br/site/index.php/CERNE/article/view/1098/860
dc.rights.driver.fl_str_mv Copyright (c) 2016 CERNE
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2016 CERNE
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv CERNE
CERNE
publisher.none.fl_str_mv CERNE
CERNE
dc.source.none.fl_str_mv CERNE; Vol. 21 No. 3 (2015); 511-517
CERNE; v. 21 n. 3 (2015); 511-517
2317-6342
0104-7760
reponame:Cerne (Online)
instname:Universidade Federal de Lavras (UFLA)
instacron:UFLA
instname_str Universidade Federal de Lavras (UFLA)
instacron_str UFLA
institution UFLA
reponame_str Cerne (Online)
collection Cerne (Online)
repository.name.fl_str_mv Cerne (Online) - Universidade Federal de Lavras (UFLA)
repository.mail.fl_str_mv cerne@dcf.ufla.br||cerne@dcf.ufla.br
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