Predictive models of primary tropical forest structure from geomorphometric variables based on SRTM in the Tapajo's region, Brazilian Amazon
Autor(a) principal: | |
---|---|
Data de Publicação: | 2016 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1371/journal.pone.0152009 http://hdl.handle.net/11449/172890 |
Resumo: | Surveying primary tropical forest over large regions is challenging. Indirect methods of relating terrain information or other external spatial datasets to forest biophysical parameters can provide forest structural maps at large scales but the inherent uncertainties need to be evaluated fully. The goal of the present study was to evaluate relief characteristics, measured through geomorphometric variables, as predictors of forest structural characteristics such as average tree basal area (BA) and height (H) and average percentage canopy openness (CO). Our hypothesis is that geomorphometric variables are good predictors of the structure of primary tropical forest, even in areas, with low altitude variation. The study was performed at the Tapajo's National Forest, located in the Western State of Pará, Brazil. Forty-three plots were sampled. Predictive models for BA, H and CO were parameterized based on geomorphometric variables using multiple linear regression. Validation of the models with nine independent sample plots revealed a Root Mean Square Error (RMSE) of 3.73 m2/ha (20%) for BA, 1.70 m (12%) for H, and 1.78% (21%) for CO. The coefficient of determination between observed and predicted values were r2 = 0.32 for CO, r2 = 0.26 for H and r2 = 0.52 for BA. The models obtained were able to adequately estimate BA and CO. In summary, it can be concluded that relief variables are good predictors of vegetation structure and enable the creation of forest structure maps in primary tropical rainforest with an acceptable uncertainty. |
id |
UNSP_1d8aa2c2e3111533027d53efaedff499 |
---|---|
oai_identifier_str |
oai:repositorio.unesp.br:11449/172890 |
network_acronym_str |
UNSP |
network_name_str |
Repositório Institucional da UNESP |
repository_id_str |
2946 |
spelling |
Predictive models of primary tropical forest structure from geomorphometric variables based on SRTM in the Tapajo's region, Brazilian AmazonSurveying primary tropical forest over large regions is challenging. Indirect methods of relating terrain information or other external spatial datasets to forest biophysical parameters can provide forest structural maps at large scales but the inherent uncertainties need to be evaluated fully. The goal of the present study was to evaluate relief characteristics, measured through geomorphometric variables, as predictors of forest structural characteristics such as average tree basal area (BA) and height (H) and average percentage canopy openness (CO). Our hypothesis is that geomorphometric variables are good predictors of the structure of primary tropical forest, even in areas, with low altitude variation. The study was performed at the Tapajo's National Forest, located in the Western State of Pará, Brazil. Forty-three plots were sampled. Predictive models for BA, H and CO were parameterized based on geomorphometric variables using multiple linear regression. Validation of the models with nine independent sample plots revealed a Root Mean Square Error (RMSE) of 3.73 m2/ha (20%) for BA, 1.70 m (12%) for H, and 1.78% (21%) for CO. The coefficient of determination between observed and predicted values were r2 = 0.32 for CO, r2 = 0.26 for H and r2 = 0.52 for BA. The models obtained were able to adequately estimate BA and CO. In summary, it can be concluded that relief variables are good predictors of vegetation structure and enable the creation of forest structure maps in primary tropical rainforest with an acceptable uncertainty.Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Ciência e Tecnologia Ambiental Universidade Federal do ABC (UFABC)Centre for Landscape and Climate Research Department of Geography University of LeicesterDivisão de Sensoriamento Remoto Instituto Nacional de Pesquisas Espaciais (INPE) São José dos CamposCoordenaçao de Dinâmica Ambiental Instituto Nacional de Pesquisas da Amazônia (INPA)National Centre for Earth Observation University of LeicesterDepartamento de Ciências Biológicas Faculdade de Ciências e Letras de Assis Universidade Estadual Paulista (UNESP)Departamento de Ciências Biológicas Faculdade de Ciências e Letras de Assis Universidade Estadual Paulista (UNESP)Universidade Federal do ABC (UFABC)University of LeicesterSão José dos CamposInstituto Nacional de Pesquisas da Amazônia (INPA)Universidade Estadual Paulista (Unesp)Da Conceiçao Bispo, PolyannaDos Santos, João RobertoDe Morisson Valeriano, MárcioDe Alencastro Graça, Paulo Maurício LimaBalzter, HeikoFrança, HelenaDa Conceiçao Bispo, Pitágoras [UNESP]2018-12-11T17:02:35Z2018-12-11T17:02:35Z2016-04-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://dx.doi.org/10.1371/journal.pone.0152009PLoS ONE, v. 11, n. 4, 2016.1932-6203http://hdl.handle.net/11449/17289010.1371/journal.pone.01520092-s2.0-849646871592-s2.0-84964687159.pdfScopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengPLoS ONE1,164info:eu-repo/semantics/openAccess2024-06-13T17:38:18Zoai:repositorio.unesp.br:11449/172890Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T16:01:58.730472Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Predictive models of primary tropical forest structure from geomorphometric variables based on SRTM in the Tapajo's region, Brazilian Amazon |
title |
Predictive models of primary tropical forest structure from geomorphometric variables based on SRTM in the Tapajo's region, Brazilian Amazon |
spellingShingle |
Predictive models of primary tropical forest structure from geomorphometric variables based on SRTM in the Tapajo's region, Brazilian Amazon Da Conceiçao Bispo, Polyanna |
title_short |
Predictive models of primary tropical forest structure from geomorphometric variables based on SRTM in the Tapajo's region, Brazilian Amazon |
title_full |
Predictive models of primary tropical forest structure from geomorphometric variables based on SRTM in the Tapajo's region, Brazilian Amazon |
title_fullStr |
Predictive models of primary tropical forest structure from geomorphometric variables based on SRTM in the Tapajo's region, Brazilian Amazon |
title_full_unstemmed |
Predictive models of primary tropical forest structure from geomorphometric variables based on SRTM in the Tapajo's region, Brazilian Amazon |
title_sort |
Predictive models of primary tropical forest structure from geomorphometric variables based on SRTM in the Tapajo's region, Brazilian Amazon |
author |
Da Conceiçao Bispo, Polyanna |
author_facet |
Da Conceiçao Bispo, Polyanna Dos Santos, João Roberto De Morisson Valeriano, Márcio De Alencastro Graça, Paulo Maurício Lima Balzter, Heiko França, Helena Da Conceiçao Bispo, Pitágoras [UNESP] |
author_role |
author |
author2 |
Dos Santos, João Roberto De Morisson Valeriano, Márcio De Alencastro Graça, Paulo Maurício Lima Balzter, Heiko França, Helena Da Conceiçao Bispo, Pitágoras [UNESP] |
author2_role |
author author author author author author |
dc.contributor.none.fl_str_mv |
Universidade Federal do ABC (UFABC) University of Leicester São José dos Campos Instituto Nacional de Pesquisas da Amazônia (INPA) Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Da Conceiçao Bispo, Polyanna Dos Santos, João Roberto De Morisson Valeriano, Márcio De Alencastro Graça, Paulo Maurício Lima Balzter, Heiko França, Helena Da Conceiçao Bispo, Pitágoras [UNESP] |
description |
Surveying primary tropical forest over large regions is challenging. Indirect methods of relating terrain information or other external spatial datasets to forest biophysical parameters can provide forest structural maps at large scales but the inherent uncertainties need to be evaluated fully. The goal of the present study was to evaluate relief characteristics, measured through geomorphometric variables, as predictors of forest structural characteristics such as average tree basal area (BA) and height (H) and average percentage canopy openness (CO). Our hypothesis is that geomorphometric variables are good predictors of the structure of primary tropical forest, even in areas, with low altitude variation. The study was performed at the Tapajo's National Forest, located in the Western State of Pará, Brazil. Forty-three plots were sampled. Predictive models for BA, H and CO were parameterized based on geomorphometric variables using multiple linear regression. Validation of the models with nine independent sample plots revealed a Root Mean Square Error (RMSE) of 3.73 m2/ha (20%) for BA, 1.70 m (12%) for H, and 1.78% (21%) for CO. The coefficient of determination between observed and predicted values were r2 = 0.32 for CO, r2 = 0.26 for H and r2 = 0.52 for BA. The models obtained were able to adequately estimate BA and CO. In summary, it can be concluded that relief variables are good predictors of vegetation structure and enable the creation of forest structure maps in primary tropical rainforest with an acceptable uncertainty. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-04-01 2018-12-11T17:02:35Z 2018-12-11T17:02:35Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1371/journal.pone.0152009 PLoS ONE, v. 11, n. 4, 2016. 1932-6203 http://hdl.handle.net/11449/172890 10.1371/journal.pone.0152009 2-s2.0-84964687159 2-s2.0-84964687159.pdf |
url |
http://dx.doi.org/10.1371/journal.pone.0152009 http://hdl.handle.net/11449/172890 |
identifier_str_mv |
PLoS ONE, v. 11, n. 4, 2016. 1932-6203 10.1371/journal.pone.0152009 2-s2.0-84964687159 2-s2.0-84964687159.pdf |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
PLoS ONE 1,164 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808128596063027200 |