Exploring TM image texture and its relationships with biomass estimation in Rondônia, Brazilian Amazon

Detalhes bibliográficos
Autor(a) principal: Lu,Dengsheng
Data de Publicação: 2005
Outros Autores: Batistella,Mateus
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Acta Amazonica
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0044-59672005000200015
Resumo: Many texture measures have been developed and used for improving land-cover classification accuracy, but rarely has research examined the role of textures in improving the performance of aboveground biomass estimations. The relationship between texture and biomass is poorly understood. This paper used Landsat Thematic Mapper (TM) data to explore relationships between TM image textures and aboveground biomass in Rondônia, Brazilian Amazon. Eight grey level co-occurrence matrix (GLCM) based texture measures (i.e., mean, variance, homogeneity, contrast, dissimilarity, entropy, second moment, and correlation), associated with seven different window sizes (5x5, 7x7, 9x9, 11x11, 15x15, 19x19, and 25x25), and five TM bands (TM 2, 3, 4, 5, and 7) were analyzed. Pearson's correlation coefficient was used to analyze texture and biomass relationships. This research indicates that most textures are weakly correlated with successional vegetation biomass, but some textures are significantly correlated with mature forest biomass. In contrast, TM spectral signatures are significantly correlated with successional vegetation biomass, but weakly correlated with mature forest biomass. Our findings imply that textures may be critical in improving mature forest biomass estimation, but relatively less important for successional vegetation biomass estimation.
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spelling Exploring TM image texture and its relationships with biomass estimation in Rondônia, Brazilian Amazontextureaboveground biomassTM imagecorrelationAmazonMany texture measures have been developed and used for improving land-cover classification accuracy, but rarely has research examined the role of textures in improving the performance of aboveground biomass estimations. The relationship between texture and biomass is poorly understood. This paper used Landsat Thematic Mapper (TM) data to explore relationships between TM image textures and aboveground biomass in Rondônia, Brazilian Amazon. Eight grey level co-occurrence matrix (GLCM) based texture measures (i.e., mean, variance, homogeneity, contrast, dissimilarity, entropy, second moment, and correlation), associated with seven different window sizes (5x5, 7x7, 9x9, 11x11, 15x15, 19x19, and 25x25), and five TM bands (TM 2, 3, 4, 5, and 7) were analyzed. Pearson's correlation coefficient was used to analyze texture and biomass relationships. This research indicates that most textures are weakly correlated with successional vegetation biomass, but some textures are significantly correlated with mature forest biomass. In contrast, TM spectral signatures are significantly correlated with successional vegetation biomass, but weakly correlated with mature forest biomass. Our findings imply that textures may be critical in improving mature forest biomass estimation, but relatively less important for successional vegetation biomass estimation.Instituto Nacional de Pesquisas da Amazônia2005-06-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0044-59672005000200015Acta Amazonica v.35 n.2 2005reponame:Acta Amazonicainstname:Instituto Nacional de Pesquisas da Amazônia (INPA)instacron:INPA10.1590/S0044-59672005000200015info:eu-repo/semantics/openAccessLu,DengshengBatistella,Mateuseng2005-10-17T00:00:00Zoai:scielo:S0044-59672005000200015Revistahttps://acta.inpa.gov.br/PUBhttps://old.scielo.br/oai/scielo-oai.phpacta@inpa.gov.br||acta@inpa.gov.br1809-43920044-5967opendoar:2005-10-17T00:00Acta Amazonica - Instituto Nacional de Pesquisas da Amazônia (INPA)false
dc.title.none.fl_str_mv Exploring TM image texture and its relationships with biomass estimation in Rondônia, Brazilian Amazon
title Exploring TM image texture and its relationships with biomass estimation in Rondônia, Brazilian Amazon
spellingShingle Exploring TM image texture and its relationships with biomass estimation in Rondônia, Brazilian Amazon
Lu,Dengsheng
texture
aboveground biomass
TM image
correlation
Amazon
title_short Exploring TM image texture and its relationships with biomass estimation in Rondônia, Brazilian Amazon
title_full Exploring TM image texture and its relationships with biomass estimation in Rondônia, Brazilian Amazon
title_fullStr Exploring TM image texture and its relationships with biomass estimation in Rondônia, Brazilian Amazon
title_full_unstemmed Exploring TM image texture and its relationships with biomass estimation in Rondônia, Brazilian Amazon
title_sort Exploring TM image texture and its relationships with biomass estimation in Rondônia, Brazilian Amazon
author Lu,Dengsheng
author_facet Lu,Dengsheng
Batistella,Mateus
author_role author
author2 Batistella,Mateus
author2_role author
dc.contributor.author.fl_str_mv Lu,Dengsheng
Batistella,Mateus
dc.subject.por.fl_str_mv texture
aboveground biomass
TM image
correlation
Amazon
topic texture
aboveground biomass
TM image
correlation
Amazon
description Many texture measures have been developed and used for improving land-cover classification accuracy, but rarely has research examined the role of textures in improving the performance of aboveground biomass estimations. The relationship between texture and biomass is poorly understood. This paper used Landsat Thematic Mapper (TM) data to explore relationships between TM image textures and aboveground biomass in Rondônia, Brazilian Amazon. Eight grey level co-occurrence matrix (GLCM) based texture measures (i.e., mean, variance, homogeneity, contrast, dissimilarity, entropy, second moment, and correlation), associated with seven different window sizes (5x5, 7x7, 9x9, 11x11, 15x15, 19x19, and 25x25), and five TM bands (TM 2, 3, 4, 5, and 7) were analyzed. Pearson's correlation coefficient was used to analyze texture and biomass relationships. This research indicates that most textures are weakly correlated with successional vegetation biomass, but some textures are significantly correlated with mature forest biomass. In contrast, TM spectral signatures are significantly correlated with successional vegetation biomass, but weakly correlated with mature forest biomass. Our findings imply that textures may be critical in improving mature forest biomass estimation, but relatively less important for successional vegetation biomass estimation.
publishDate 2005
dc.date.none.fl_str_mv 2005-06-01
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=S0044-59672005000200015
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0044-59672005000200015
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/S0044-59672005000200015
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 Instituto Nacional de Pesquisas da Amazônia
publisher.none.fl_str_mv Instituto Nacional de Pesquisas da Amazônia
dc.source.none.fl_str_mv Acta Amazonica v.35 n.2 2005
reponame:Acta Amazonica
instname:Instituto Nacional de Pesquisas da Amazônia (INPA)
instacron:INPA
instname_str Instituto Nacional de Pesquisas da Amazônia (INPA)
instacron_str INPA
institution INPA
reponame_str Acta Amazonica
collection Acta Amazonica
repository.name.fl_str_mv Acta Amazonica - Instituto Nacional de Pesquisas da Amazônia (INPA)
repository.mail.fl_str_mv acta@inpa.gov.br||acta@inpa.gov.br
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