LAI Improved to dry forest in Semiarid of the Brazil.

Savannas are globally important ecosystems of great significance to human economies. Savannas exist in water-limited regions which forces tree canopies open and heterogeneous. The open canopy structure allows grass to co-dominate in the savannas by occupying different niches in space and time. Leaf area index (LAI) and fraction of photosynthetically active radiation absorbed by vegetation (FPAR) characterize vegetation canopy functioning and energy absorption capacity. LAI and FPAR are key parameters in most ecosystem productivity models and global models of climate, hydrology, biogeochemistry and ecology. Given the above, this study aimed to develop an equation of LAI calibrated by savannah in semiarid northeastern Brazil and proposed a model to better estimate the LAI for dry forest, such as the savanna (Caatinga). The model developed in this study may be used to improve the estimates of Leaf Area Index [LAI] in dry forest with NDVI. One model for savanna-specific of leaf area index (LAI) has been developed. The use of S Curve statistical methods to calibrate the leaf area index (LAI) proved to be an efficient method. The model development gives good results in most of the LAI range known for Caatinga stands in Northeast of Brazil. The Root Mean Square Error (RMSE) calculated on an independent LAI dataset was 0.10, which is about 6% of the average measured LAI. This method offers a simple and operational alternative to application of complex and computationally intensive techniques, and could be used to design other species-specific LAIs. This study reinforces the importance of developing models to better estimate the LAI in different ecosystems since there are no similarities of the LAI between dry and humid climate.

Saved in:
Bibliographic Details
Main Authors: GALVÍNCIO, J. D., MOURA, M. S. B. de, SILVA, T. G. F. da, SILVA, B. B. da, NAUE, C. R.
Other Authors: JOSICLÊDA DOMICIANO GALVÍNCIO; MAGNA SOELMA BESERRA DE MOURA, CPATSA; THIERES GEORGE FREIRE DA SILVA; BERNARDO BARBOSA DA SILVA; CARINE ROSA NAUE.
Format: Artigo de periódico biblioteca
Language:English
eng
Published: 2013-12-17
Subjects:LAI, Ecossistemas secos, Modelo de desenvolvimento, Fieldspec, Savanas, Natural resource., Recurso natural, Sensoriamento remoto, Caatinga.,
Online Access:http://www.alice.cnptia.embrapa.br/alice/handle/doc/974172
Tags: Add Tag
No Tags, Be the first to tag this record!
id dig-alice-doc-974172
record_format koha
spelling dig-alice-doc-9741722017-08-16T00:32:48Z LAI Improved to dry forest in Semiarid of the Brazil. GALVÍNCIO, J. D. MOURA, M. S. B. de SILVA, T. G. F. da SILVA, B. B. da NAUE, C. R. JOSICLÊDA DOMICIANO GALVÍNCIO; MAGNA SOELMA BESERRA DE MOURA, CPATSA; THIERES GEORGE FREIRE DA SILVA; BERNARDO BARBOSA DA SILVA; CARINE ROSA NAUE. LAI Ecossistemas secos Modelo de desenvolvimento Fieldspec Savanas Natural resource. Recurso natural Sensoriamento remoto Caatinga. Savannas are globally important ecosystems of great significance to human economies. Savannas exist in water-limited regions which forces tree canopies open and heterogeneous. The open canopy structure allows grass to co-dominate in the savannas by occupying different niches in space and time. Leaf area index (LAI) and fraction of photosynthetically active radiation absorbed by vegetation (FPAR) characterize vegetation canopy functioning and energy absorption capacity. LAI and FPAR are key parameters in most ecosystem productivity models and global models of climate, hydrology, biogeochemistry and ecology. Given the above, this study aimed to develop an equation of LAI calibrated by savannah in semiarid northeastern Brazil and proposed a model to better estimate the LAI for dry forest, such as the savanna (Caatinga). The model developed in this study may be used to improve the estimates of Leaf Area Index [LAI] in dry forest with NDVI. One model for savanna-specific of leaf area index (LAI) has been developed. The use of S Curve statistical methods to calibrate the leaf area index (LAI) proved to be an efficient method. The model development gives good results in most of the LAI range known for Caatinga stands in Northeast of Brazil. The Root Mean Square Error (RMSE) calculated on an independent LAI dataset was 0.10, which is about 6% of the average measured LAI. This method offers a simple and operational alternative to application of complex and computationally intensive techniques, and could be used to design other species-specific LAIs. This study reinforces the importance of developing models to better estimate the LAI in different ecosystems since there are no similarities of the LAI between dry and humid climate. 2013-12-17T11:11:11Z 2013-12-17T11:11:11Z 2013-12-17 2013 2013-12-20T11:11:11Z Artigo de periódico International Journal of Remote Sensing Applications, v. 3, n. 4, p. 193-202, dec. 2013. http://www.alice.cnptia.embrapa.br/alice/handle/doc/974172 10.14355/ijrsa.2013.0304.04 en eng openAccess
institution EMBRAPA
collection DSpace
country Brasil
countrycode BR
component Bibliográfico
access En linea
databasecode dig-alice
tag biblioteca
region America del Sur
libraryname Sistema de bibliotecas de EMBRAPA
language English
eng
topic LAI
Ecossistemas secos
Modelo de desenvolvimento
Fieldspec
Savanas
Natural resource.
Recurso natural
Sensoriamento remoto
Caatinga.
LAI
Ecossistemas secos
Modelo de desenvolvimento
Fieldspec
Savanas
Natural resource.
Recurso natural
Sensoriamento remoto
Caatinga.
spellingShingle LAI
Ecossistemas secos
Modelo de desenvolvimento
Fieldspec
Savanas
Natural resource.
Recurso natural
Sensoriamento remoto
Caatinga.
LAI
Ecossistemas secos
Modelo de desenvolvimento
Fieldspec
Savanas
Natural resource.
Recurso natural
Sensoriamento remoto
Caatinga.
GALVÍNCIO, J. D.
MOURA, M. S. B. de
SILVA, T. G. F. da
SILVA, B. B. da
NAUE, C. R.
LAI Improved to dry forest in Semiarid of the Brazil.
description Savannas are globally important ecosystems of great significance to human economies. Savannas exist in water-limited regions which forces tree canopies open and heterogeneous. The open canopy structure allows grass to co-dominate in the savannas by occupying different niches in space and time. Leaf area index (LAI) and fraction of photosynthetically active radiation absorbed by vegetation (FPAR) characterize vegetation canopy functioning and energy absorption capacity. LAI and FPAR are key parameters in most ecosystem productivity models and global models of climate, hydrology, biogeochemistry and ecology. Given the above, this study aimed to develop an equation of LAI calibrated by savannah in semiarid northeastern Brazil and proposed a model to better estimate the LAI for dry forest, such as the savanna (Caatinga). The model developed in this study may be used to improve the estimates of Leaf Area Index [LAI] in dry forest with NDVI. One model for savanna-specific of leaf area index (LAI) has been developed. The use of S Curve statistical methods to calibrate the leaf area index (LAI) proved to be an efficient method. The model development gives good results in most of the LAI range known for Caatinga stands in Northeast of Brazil. The Root Mean Square Error (RMSE) calculated on an independent LAI dataset was 0.10, which is about 6% of the average measured LAI. This method offers a simple and operational alternative to application of complex and computationally intensive techniques, and could be used to design other species-specific LAIs. This study reinforces the importance of developing models to better estimate the LAI in different ecosystems since there are no similarities of the LAI between dry and humid climate.
author2 JOSICLÊDA DOMICIANO GALVÍNCIO; MAGNA SOELMA BESERRA DE MOURA, CPATSA; THIERES GEORGE FREIRE DA SILVA; BERNARDO BARBOSA DA SILVA; CARINE ROSA NAUE.
author_facet JOSICLÊDA DOMICIANO GALVÍNCIO; MAGNA SOELMA BESERRA DE MOURA, CPATSA; THIERES GEORGE FREIRE DA SILVA; BERNARDO BARBOSA DA SILVA; CARINE ROSA NAUE.
GALVÍNCIO, J. D.
MOURA, M. S. B. de
SILVA, T. G. F. da
SILVA, B. B. da
NAUE, C. R.
format Artigo de periódico
topic_facet LAI
Ecossistemas secos
Modelo de desenvolvimento
Fieldspec
Savanas
Natural resource.
Recurso natural
Sensoriamento remoto
Caatinga.
author GALVÍNCIO, J. D.
MOURA, M. S. B. de
SILVA, T. G. F. da
SILVA, B. B. da
NAUE, C. R.
author_sort GALVÍNCIO, J. D.
title LAI Improved to dry forest in Semiarid of the Brazil.
title_short LAI Improved to dry forest in Semiarid of the Brazil.
title_full LAI Improved to dry forest in Semiarid of the Brazil.
title_fullStr LAI Improved to dry forest in Semiarid of the Brazil.
title_full_unstemmed LAI Improved to dry forest in Semiarid of the Brazil.
title_sort lai improved to dry forest in semiarid of the brazil.
publishDate 2013-12-17
url http://www.alice.cnptia.embrapa.br/alice/handle/doc/974172
work_keys_str_mv AT galvinciojd laiimprovedtodryforestinsemiaridofthebrazil
AT mouramsbde laiimprovedtodryforestinsemiaridofthebrazil
AT silvatgfda laiimprovedtodryforestinsemiaridofthebrazil
AT silvabbda laiimprovedtodryforestinsemiaridofthebrazil
AT nauecr laiimprovedtodryforestinsemiaridofthebrazil
_version_ 1756019015696777216