Beyond trees: Mapping total aboveground biomass density in the Brazilian savanna using high-density UAV-lidar data
Tropical savanna ecosystems play a major role in the seasonality of the global carbon cycle. However, their ability to store and sequester carbon is uncertain due to combined and intermingling effects of anthropogenic activities and climate change, which impact wildfire regimes and vegetation dynami...
| Autores: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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| Formato: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2021 |
| País: | España |
| Recursos: | Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| Repositorio: | Recercat. Dipósit de la Recerca de Catalunya |
| OAI Identifier: | oai:recercat.cat:10459.1/84248 |
| Acesso em linha: | https://doi.org/10.1016/j.foreco.2021.119155 http://hdl.handle.net/10459.1/84248 |
| Access Level: | acceso abierto |
| Palavra-chave: | Tropical savanna Remote sensing Mapping GatorEye Biomass Vegetation |
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oai:recercat.cat:10459.1/84248 |
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Beyond trees: Mapping total aboveground biomass density in the Brazilian savanna using high-density UAV-lidar dataTeixeira da Costa, Máira BeatrizSilva, Carlos AlbertoNorth Broadbent, EbenVieira Leite, RodrigoMohan, MidhunLiesenberg, VeraldoStoddart, JazHummel do Amaral, CibeleAlves de Almeida, Danilo Robertida Silva, Anne LauraRé Y. Goya, Lucas RuggeriAlmeida Cordeiro, VictorRex, Franciel EduardoHirsch, AndréMarcatti, Gustavo EduardoCardil Forradellas, AdriánAraujo Furtado de Mendonça, BrunoHamamura, CaioDalla Corte, Ana PaulaMatricardi, Eraldo Aparecido TrondoliHudak, Andrew T.Almeyda Zambrano, Angelica M.Valbuena, RubenLopes de Faria, BrunoSilva Junior, Celso H.L.Aragao, LuizFerreira, Manuel EduardoLiang, JingjingKlauberg, Carinede Padua Chaves e Carvalho, SamuelTropical savannaRemote sensingMappingGatorEyeBiomassVegetationTropical savanna ecosystems play a major role in the seasonality of the global carbon cycle. However, their ability to store and sequester carbon is uncertain due to combined and intermingling effects of anthropogenic activities and climate change, which impact wildfire regimes and vegetation dynamics. Accurate measurements of tropical savanna vegetation aboveground biomass (AGB) over broad spatial scales are crucial to achieve effective carbon emission mitigation strategies. UAV-lidar is a new remote sensing technology that can enable rapid 3-D mapping of structure and related AGB in tropical savanna ecosystems. This study aimed to assess the capability of high-density UAV-lidar to estimate and map total (tree, shrubs, and surface layers) aboveground biomass density (AGBt) in the Brazilian Savanna (Cerrado). Five ordinary least square regression models esti-mating AGBt were adjusted using 50 field sample plots (30 m × 30 m). The best model was selected under Akaike Information Criterion, adjusted coefficient of determination (adj.R2), absolute and relative root mean square error (RMSE), and used to map AGBt from UAV-lidar data collected over 1,854 ha spanning the three major vegetation formations (forest, savanna, and grassland) in Cerrado. The model using vegetation height and cover was the most effective, with an overall model adj-R2 of 0.79 and a leave-one-out cross-validated RMSE of 19.11 Mg/ha (33.40%). The uncertainty and errors of our estimations were assessed for each vegetation formation separately, resulting in RMSEs of 27.08 Mg/ha (25.99%) for forests, 17.76 Mg/ha (43.96%) for savannas, and 7.72 Mg/ha (44.92%) for grasslands. These results prove the feasibility and potential of the UAV-lidar technology in Cerrado but also emphasize the need for further developing the estimation of biomass in grasslands, of high importance in the characterization of the global carbon balance and for supporting integrated fire management activities in tropical savanna ecosystems. Our results serve as a benchmark for future studies aiming to generate accurate biomass maps and provide baseline data for efficient management of fire and predicted climate change impacts on tropical savanna ecosystems.Elsevier202220222021info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttps://doi.org/10.1016/j.foreco.2021.119155http://hdl.handle.net/10459.1/84248http://hdl.handle.net/10459.1/84248reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésReproducció del document publicat a https://doi.org/10.1016/j.foreco.2021.119155Forest Ecology and Management, 2021, vol. 491, 119155cc-by (c) Elsevier B.V., 2021info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/oai:recercat.cat:10459.1/842482026-05-29T05:05:01Z |
| dc.title.none.fl_str_mv |
Beyond trees: Mapping total aboveground biomass density in the Brazilian savanna using high-density UAV-lidar data |
| title |
Beyond trees: Mapping total aboveground biomass density in the Brazilian savanna using high-density UAV-lidar data |
| spellingShingle |
Beyond trees: Mapping total aboveground biomass density in the Brazilian savanna using high-density UAV-lidar data Teixeira da Costa, Máira Beatriz Tropical savanna Remote sensing Mapping GatorEye Biomass Vegetation |
| title_short |
Beyond trees: Mapping total aboveground biomass density in the Brazilian savanna using high-density UAV-lidar data |
| title_full |
Beyond trees: Mapping total aboveground biomass density in the Brazilian savanna using high-density UAV-lidar data |
| title_fullStr |
Beyond trees: Mapping total aboveground biomass density in the Brazilian savanna using high-density UAV-lidar data |
| title_full_unstemmed |
Beyond trees: Mapping total aboveground biomass density in the Brazilian savanna using high-density UAV-lidar data |
| title_sort |
Beyond trees: Mapping total aboveground biomass density in the Brazilian savanna using high-density UAV-lidar data |
| dc.creator.none.fl_str_mv |
Teixeira da Costa, Máira Beatriz Silva, Carlos Alberto North Broadbent, Eben Vieira Leite, Rodrigo Mohan, Midhun Liesenberg, Veraldo Stoddart, Jaz Hummel do Amaral, Cibele Alves de Almeida, Danilo Roberti da Silva, Anne Laura Ré Y. Goya, Lucas Ruggeri Almeida Cordeiro, Victor Rex, Franciel Eduardo Hirsch, André Marcatti, Gustavo Eduardo Cardil Forradellas, Adrián Araujo Furtado de Mendonça, Bruno Hamamura, Caio Dalla Corte, Ana Paula Matricardi, Eraldo Aparecido Trondoli Hudak, Andrew T. Almeyda Zambrano, Angelica M. Valbuena, Ruben Lopes de Faria, Bruno Silva Junior, Celso H.L. Aragao, Luiz Ferreira, Manuel Eduardo Liang, Jingjing Klauberg, Carine de Padua Chaves e Carvalho, Samuel |
| author |
Teixeira da Costa, Máira Beatriz |
| author_facet |
Teixeira da Costa, Máira Beatriz Silva, Carlos Alberto North Broadbent, Eben Vieira Leite, Rodrigo Mohan, Midhun Liesenberg, Veraldo Stoddart, Jaz Hummel do Amaral, Cibele Alves de Almeida, Danilo Roberti da Silva, Anne Laura Ré Y. Goya, Lucas Ruggeri Almeida Cordeiro, Victor Rex, Franciel Eduardo Hirsch, André Marcatti, Gustavo Eduardo Cardil Forradellas, Adrián Araujo Furtado de Mendonça, Bruno Hamamura, Caio Dalla Corte, Ana Paula Matricardi, Eraldo Aparecido Trondoli Hudak, Andrew T. Almeyda Zambrano, Angelica M. Valbuena, Ruben Lopes de Faria, Bruno Silva Junior, Celso H.L. Aragao, Luiz Ferreira, Manuel Eduardo Liang, Jingjing Klauberg, Carine de Padua Chaves e Carvalho, Samuel |
| author_role |
author |
| author2 |
Silva, Carlos Alberto North Broadbent, Eben Vieira Leite, Rodrigo Mohan, Midhun Liesenberg, Veraldo Stoddart, Jaz Hummel do Amaral, Cibele Alves de Almeida, Danilo Roberti da Silva, Anne Laura Ré Y. Goya, Lucas Ruggeri Almeida Cordeiro, Victor Rex, Franciel Eduardo Hirsch, André Marcatti, Gustavo Eduardo Cardil Forradellas, Adrián Araujo Furtado de Mendonça, Bruno Hamamura, Caio Dalla Corte, Ana Paula Matricardi, Eraldo Aparecido Trondoli Hudak, Andrew T. Almeyda Zambrano, Angelica M. Valbuena, Ruben Lopes de Faria, Bruno Silva Junior, Celso H.L. Aragao, Luiz Ferreira, Manuel Eduardo Liang, Jingjing Klauberg, Carine de Padua Chaves e Carvalho, Samuel |
| author2_role |
author author author author author author author author author author author author author author author author author author author author author author author author author author author author author |
| dc.subject.none.fl_str_mv |
Tropical savanna Remote sensing Mapping GatorEye Biomass Vegetation |
| topic |
Tropical savanna Remote sensing Mapping GatorEye Biomass Vegetation |
| description |
Tropical savanna ecosystems play a major role in the seasonality of the global carbon cycle. However, their ability to store and sequester carbon is uncertain due to combined and intermingling effects of anthropogenic activities and climate change, which impact wildfire regimes and vegetation dynamics. Accurate measurements of tropical savanna vegetation aboveground biomass (AGB) over broad spatial scales are crucial to achieve effective carbon emission mitigation strategies. UAV-lidar is a new remote sensing technology that can enable rapid 3-D mapping of structure and related AGB in tropical savanna ecosystems. This study aimed to assess the capability of high-density UAV-lidar to estimate and map total (tree, shrubs, and surface layers) aboveground biomass density (AGBt) in the Brazilian Savanna (Cerrado). Five ordinary least square regression models esti-mating AGBt were adjusted using 50 field sample plots (30 m × 30 m). The best model was selected under Akaike Information Criterion, adjusted coefficient of determination (adj.R2), absolute and relative root mean square error (RMSE), and used to map AGBt from UAV-lidar data collected over 1,854 ha spanning the three major vegetation formations (forest, savanna, and grassland) in Cerrado. The model using vegetation height and cover was the most effective, with an overall model adj-R2 of 0.79 and a leave-one-out cross-validated RMSE of 19.11 Mg/ha (33.40%). The uncertainty and errors of our estimations were assessed for each vegetation formation separately, resulting in RMSEs of 27.08 Mg/ha (25.99%) for forests, 17.76 Mg/ha (43.96%) for savannas, and 7.72 Mg/ha (44.92%) for grasslands. These results prove the feasibility and potential of the UAV-lidar technology in Cerrado but also emphasize the need for further developing the estimation of biomass in grasslands, of high importance in the characterization of the global carbon balance and for supporting integrated fire management activities in tropical savanna ecosystems. Our results serve as a benchmark for future studies aiming to generate accurate biomass maps and provide baseline data for efficient management of fire and predicted climate change impacts on tropical savanna ecosystems. |
| publishDate |
2021 |
| dc.date.none.fl_str_mv |
2021 2022 2022 |
| dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
| format |
article |
| status_str |
publishedVersion |
| dc.identifier.none.fl_str_mv |
https://doi.org/10.1016/j.foreco.2021.119155 http://hdl.handle.net/10459.1/84248 http://hdl.handle.net/10459.1/84248 |
| url |
https://doi.org/10.1016/j.foreco.2021.119155 http://hdl.handle.net/10459.1/84248 |
| dc.language.none.fl_str_mv |
Inglés |
| language_invalid_str_mv |
Inglés |
| dc.relation.none.fl_str_mv |
Reproducció del document publicat a https://doi.org/10.1016/j.foreco.2021.119155 Forest Ecology and Management, 2021, vol. 491, 119155 |
| dc.rights.none.fl_str_mv |
cc-by (c) Elsevier B.V., 2021 info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/4.0/ |
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cc-by (c) Elsevier B.V., 2021 http://creativecommons.org/licenses/by/4.0/ |
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openAccess |
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Elsevier |
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Elsevier |
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reponame:Recercat. Dipósit de la Recerca de Catalunya instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
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Recercat. Dipósit de la Recerca de Catalunya |
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Recercat. Dipósit de la Recerca de Catalunya |
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15,228081 |