LEAF AREA INDEX MONITORING AND PROTECTIONG THROUGH REMOTE SENSING IN THE ITATIAIA NATIONAL PARK
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Outros Autores: | , , |
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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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 |
_version_ |
1799874942833000448 |