Analyzing Canopy Height Patterns and Environmental Landscape Drivers in Tropical Forests Using NASA’s GEDI Spaceborne LiDAR

Canopy height is a fundamental parameter for determining forest ecosystem functions such as biodiversity and above-ground biomass. Previous studies examining the underlying patterns of the complex relationship between canopy height and its environmental and climatic determinants suffered from the sc...

Descripción completa

Detalles Bibliográficos
Autores: Adrah, Esmaeel, Wan Mohd Jaafar, W.S., Omar, Hamdan, Bajaj, Shaurya, Vieira Leite, Rodrigo, Mazlan, Siti Munirah, Silva, Carlos Alberto, Chel Gee Ooi, Maggie, Mohd Said, Mohd Nizam, Abdul Maulud, Khairul Nizam, Cardil Forradellas, Adrián, Mohan, Midhun
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2022
País:España
Institución: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:10459.1/84526
Acceso en línea:https://doi.org/10.3390/rs14133172
http://hdl.handle.net/10459.1/84526
Access Level:acceso abierto
Palabra clave:GEDI
LiDAR
Canopy height
Mountain forest
Forest remote sensing
id ES_e0085bd98dc33d451fbaf1dbfd8199ba
oai_identifier_str oai:recercat.cat:10459.1/84526
network_acronym_str ES
network_name_str España
repository_id_str
spelling Analyzing Canopy Height Patterns and Environmental Landscape Drivers in Tropical Forests Using NASA’s GEDI Spaceborne LiDARAdrah, EsmaeelWan Mohd Jaafar, W.S.Omar, HamdanBajaj, ShauryaVieira Leite, RodrigoMazlan, Siti MunirahSilva, Carlos AlbertoChel Gee Ooi, MaggieMohd Said, Mohd NizamAbdul Maulud, Khairul NizamCardil Forradellas, AdriánMohan, MidhunGEDILiDARCanopy heightMountain forestForest remote sensingCanopy height is a fundamental parameter for determining forest ecosystem functions such as biodiversity and above-ground biomass. Previous studies examining the underlying patterns of the complex relationship between canopy height and its environmental and climatic determinants suffered from the scarcity of accurate canopy height measurements at large scales. NASA’s mission, the Global Ecosystem Dynamic Investigation (GEDI), has provided sampled observations of the forest vertical structure at near global scale since late 2018. The availability of such unprecedented measurements allows for examining the vertical structure of vegetation spatially and temporally. Herein, we explore the most influential climatic and environmental drivers of the canopy height in tropical forests. We examined different resampling resolutions of GEDI-based canopy height to approximate maximum canopy height over tropical forests across all of Malaysia. Moreover, we attempted to interpret the dynamics underlining the bivariate and multivariate relationships between canopy height and its climatic and topographic predictors including world climate data and topographic data. The approaches to analyzing these interactions included machine learning algorithms, namely, generalized linear regression, random forest and extreme gradient boosting with tree and Dart implementations. Water availability, represented as the difference between precipitation and potential evapotranspiration, annual mean temperature and elevation gradients were found to be the most influential determinants of canopy height in Malaysia’s tropical forest landscape. The patterns observed are in line with the reported global patterns and support the hydraulic limitation hypothesis and the previously reported negative trend for excessive water supply. Nevertheless, different breaking points for excessive water supply and elevation were identified in this study, and the canopy height relationship with water availability observed to be less significant for the mountainous forest on altitudes higher than 1000 m. This study provides insights into the influential factors of tree height and helps with better comprehending the variation in canopy height in tropical forests based on GEDI measurements, thereby supporting the development and interpretation of ecosystem modeling, forest management practices and monitoring forest response to climatic changes in montane forests.MDPI202220222022info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttps://doi.org/10.3390/rs14133172http://hdl.handle.net/10459.1/84526http://hdl.handle.net/10459.1/84526reponame: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/10.3390/rs14133172Remote Sensing, 2022, vol. 14, art. 3172cc-by (c) Esmaeel Adrah et. al., 2022info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/oai:recercat.cat:10459.1/845262026-05-29T05:05:01Z
dc.title.none.fl_str_mv Analyzing Canopy Height Patterns and Environmental Landscape Drivers in Tropical Forests Using NASA’s GEDI Spaceborne LiDAR
title Analyzing Canopy Height Patterns and Environmental Landscape Drivers in Tropical Forests Using NASA’s GEDI Spaceborne LiDAR
spellingShingle Analyzing Canopy Height Patterns and Environmental Landscape Drivers in Tropical Forests Using NASA’s GEDI Spaceborne LiDAR
Adrah, Esmaeel
GEDI
LiDAR
Canopy height
Mountain forest
Forest remote sensing
title_short Analyzing Canopy Height Patterns and Environmental Landscape Drivers in Tropical Forests Using NASA’s GEDI Spaceborne LiDAR
title_full Analyzing Canopy Height Patterns and Environmental Landscape Drivers in Tropical Forests Using NASA’s GEDI Spaceborne LiDAR
title_fullStr Analyzing Canopy Height Patterns and Environmental Landscape Drivers in Tropical Forests Using NASA’s GEDI Spaceborne LiDAR
title_full_unstemmed Analyzing Canopy Height Patterns and Environmental Landscape Drivers in Tropical Forests Using NASA’s GEDI Spaceborne LiDAR
title_sort Analyzing Canopy Height Patterns and Environmental Landscape Drivers in Tropical Forests Using NASA’s GEDI Spaceborne LiDAR
dc.creator.none.fl_str_mv Adrah, Esmaeel
Wan Mohd Jaafar, W.S.
Omar, Hamdan
Bajaj, Shaurya
Vieira Leite, Rodrigo
Mazlan, Siti Munirah
Silva, Carlos Alberto
Chel Gee Ooi, Maggie
Mohd Said, Mohd Nizam
Abdul Maulud, Khairul Nizam
Cardil Forradellas, Adrián
Mohan, Midhun
author Adrah, Esmaeel
author_facet Adrah, Esmaeel
Wan Mohd Jaafar, W.S.
Omar, Hamdan
Bajaj, Shaurya
Vieira Leite, Rodrigo
Mazlan, Siti Munirah
Silva, Carlos Alberto
Chel Gee Ooi, Maggie
Mohd Said, Mohd Nizam
Abdul Maulud, Khairul Nizam
Cardil Forradellas, Adrián
Mohan, Midhun
author_role author
author2 Wan Mohd Jaafar, W.S.
Omar, Hamdan
Bajaj, Shaurya
Vieira Leite, Rodrigo
Mazlan, Siti Munirah
Silva, Carlos Alberto
Chel Gee Ooi, Maggie
Mohd Said, Mohd Nizam
Abdul Maulud, Khairul Nizam
Cardil Forradellas, Adrián
Mohan, Midhun
author2_role author
author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv GEDI
LiDAR
Canopy height
Mountain forest
Forest remote sensing
topic GEDI
LiDAR
Canopy height
Mountain forest
Forest remote sensing
description Canopy height is a fundamental parameter for determining forest ecosystem functions such as biodiversity and above-ground biomass. Previous studies examining the underlying patterns of the complex relationship between canopy height and its environmental and climatic determinants suffered from the scarcity of accurate canopy height measurements at large scales. NASA’s mission, the Global Ecosystem Dynamic Investigation (GEDI), has provided sampled observations of the forest vertical structure at near global scale since late 2018. The availability of such unprecedented measurements allows for examining the vertical structure of vegetation spatially and temporally. Herein, we explore the most influential climatic and environmental drivers of the canopy height in tropical forests. We examined different resampling resolutions of GEDI-based canopy height to approximate maximum canopy height over tropical forests across all of Malaysia. Moreover, we attempted to interpret the dynamics underlining the bivariate and multivariate relationships between canopy height and its climatic and topographic predictors including world climate data and topographic data. The approaches to analyzing these interactions included machine learning algorithms, namely, generalized linear regression, random forest and extreme gradient boosting with tree and Dart implementations. Water availability, represented as the difference between precipitation and potential evapotranspiration, annual mean temperature and elevation gradients were found to be the most influential determinants of canopy height in Malaysia’s tropical forest landscape. The patterns observed are in line with the reported global patterns and support the hydraulic limitation hypothesis and the previously reported negative trend for excessive water supply. Nevertheless, different breaking points for excessive water supply and elevation were identified in this study, and the canopy height relationship with water availability observed to be less significant for the mountainous forest on altitudes higher than 1000 m. This study provides insights into the influential factors of tree height and helps with better comprehending the variation in canopy height in tropical forests based on GEDI measurements, thereby supporting the development and interpretation of ecosystem modeling, forest management practices and monitoring forest response to climatic changes in montane forests.
publishDate 2022
dc.date.none.fl_str_mv 2022
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/10.3390/rs14133172
http://hdl.handle.net/10459.1/84526
http://hdl.handle.net/10459.1/84526
url https://doi.org/10.3390/rs14133172
http://hdl.handle.net/10459.1/84526
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/10.3390/rs14133172
Remote Sensing, 2022, vol. 14, art. 3172
dc.rights.none.fl_str_mv cc-by (c) Esmaeel Adrah et. al., 2022
info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/4.0/
rights_invalid_str_mv cc-by (c) Esmaeel Adrah et. al., 2022
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869422141585227776
score 15.81155

Similares en LA Referencia