Comparison of Semi-Physical and Empirical Models in the Estimation of Boreal Forest Leaf Area Index and Clumping with Airborne Laser Scanning Data

Autores
Zhang, Shaohui; Korhonen, Lauri; Lang, Mait; Pisek, Jan; Díaz, Gastón Mauro; Korpela, Ilkka; Xia, Zhongyu; Haapala, Hanna; Maltamo, Matti
Año de publicación
2024
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Leaf area index (LAI) is an important forest canopy variable that is related to various biophysical processes of forest ecosystems. Airborne laser scanning (ALS) has shown promise in modeling and mapping LAI using different types of ALS metrics. The most common ways of modeling LAI with ALS data are multivariate empirical models and the semi-physical model shape derived from the Beer–Lambert law of radiation attenuation. We tested the utility of ALS-based empirical and semi-physical models in the estimations of effective LAI (LAIe), canopy clumping index (Omega_E), and clumping-corrected LAI at three boreal forest sites in Finland. In semi-physical models, the all echo penetration index (API) showed consistently the best performance in predicting LAIe. It is, therefore, a robust and potentially the most transferable predictor using this model shape. Empirical models overall yielded slightly better model fits compared to the semi-physical models, yet they are also more prone to overfitting. In addition, empirical models had constantly lower accuracies when predicting LAI than LAIe. We also tested the utility of ALS-based multi-angular canopy gap fraction metrics that were derived from polar transformed ALS point clouds. Images derived from polar transformed point clouds can be analyzed similarly to digital hemispherical photographs (DHPs) to obtain canopy gap fractions. The results showed that polar metrics derived from polar transformed ALS data can provide supporting information to empirical models in the estimation of LAIe, LAI, and especially Omega_E. In particular, a combination of ALS penetration indices and polar metrics yielded positive results in Omega_E estimation.
Fil: Zhang, Shaohui. University Of Eastern Finland. Faculty Of Science And Forestry.; Finlandia
Fil: Korhonen, Lauri. University Of Eastern Finland. Faculty Of Science And Forestry.; Finlandia
Fil: Lang, Mait. University Of Tartu. Faculty Of Science And Technology. Tartu Observatory.; Estonia
Fil: Pisek, Jan. University Of Tartu. Faculty Of Science And Technology. Tartu Observatory.; Estonia
Fil: Díaz, Gastón Mauro. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Centro de Investigación y Extensión Forestal Andino Patagónico; Argentina
Fil: Korpela, Ilkka. University of Helsinki; Finlandia
Fil: Xia, Zhongyu. University Of Eastern Finland. Faculty Of Science And Forestry.; Finlandia
Fil: Haapala, Hanna. University Of Eastern Finland. Faculty Of Science And Forestry.; Finlandia
Fil: Maltamo, Matti. University Of Eastern Finland. Faculty Of Science And Forestry.; Finlandia
Materia
AIRBORNE LASER SCANNING
CANOPY CLUMPING
FOREST CANOPY
LEAF AREA INDEX
LIGHT DETECTION AND RANGING
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/231935
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/231935
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network_name_str CONICET Digital (CONICET)
spelling Comparison of Semi-Physical and Empirical Models in the Estimation of Boreal Forest Leaf Area Index and Clumping with Airborne Laser Scanning DataZhang, ShaohuiKorhonen, LauriLang, MaitPisek, JanDíaz, Gastón MauroKorpela, IlkkaXia, ZhongyuHaapala, HannaMaltamo, MattiAIRBORNE LASER SCANNINGCANOPY CLUMPINGFOREST CANOPYLEAF AREA INDEXLIGHT DETECTION AND RANGINGhttps://purl.org/becyt/ford/2.11https://purl.org/becyt/ford/2Leaf area index (LAI) is an important forest canopy variable that is related to various biophysical processes of forest ecosystems. Airborne laser scanning (ALS) has shown promise in modeling and mapping LAI using different types of ALS metrics. The most common ways of modeling LAI with ALS data are multivariate empirical models and the semi-physical model shape derived from the Beer–Lambert law of radiation attenuation. We tested the utility of ALS-based empirical and semi-physical models in the estimations of effective LAI (LAIe), canopy clumping index (Omega_E), and clumping-corrected LAI at three boreal forest sites in Finland. In semi-physical models, the all echo penetration index (API) showed consistently the best performance in predicting LAIe. It is, therefore, a robust and potentially the most transferable predictor using this model shape. Empirical models overall yielded slightly better model fits compared to the semi-physical models, yet they are also more prone to overfitting. In addition, empirical models had constantly lower accuracies when predicting LAI than LAIe. We also tested the utility of ALS-based multi-angular canopy gap fraction metrics that were derived from polar transformed ALS point clouds. Images derived from polar transformed point clouds can be analyzed similarly to digital hemispherical photographs (DHPs) to obtain canopy gap fractions. The results showed that polar metrics derived from polar transformed ALS data can provide supporting information to empirical models in the estimation of LAIe, LAI, and especially Omega_E. In particular, a combination of ALS penetration indices and polar metrics yielded positive results in Omega_E estimation.Fil: Zhang, Shaohui. University Of Eastern Finland. Faculty Of Science And Forestry.; FinlandiaFil: Korhonen, Lauri. University Of Eastern Finland. Faculty Of Science And Forestry.; FinlandiaFil: Lang, Mait. University Of Tartu. Faculty Of Science And Technology. Tartu Observatory.; EstoniaFil: Pisek, Jan. University Of Tartu. Faculty Of Science And Technology. Tartu Observatory.; EstoniaFil: Díaz, Gastón Mauro. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Centro de Investigación y Extensión Forestal Andino Patagónico; ArgentinaFil: Korpela, Ilkka. University of Helsinki; FinlandiaFil: Xia, Zhongyu. University Of Eastern Finland. Faculty Of Science And Forestry.; FinlandiaFil: Haapala, Hanna. University Of Eastern Finland. Faculty Of Science And Forestry.; FinlandiaFil: Maltamo, Matti. University Of Eastern Finland. Faculty Of Science And Forestry.; FinlandiaInstitute of Electrical and Electronics Engineers2024-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/231935Zhang, Shaohui; Korhonen, Lauri; Lang, Mait; Pisek, Jan; Díaz, Gastón Mauro; et al.; Comparison of Semi-Physical and Empirical Models in the Estimation of Boreal Forest Leaf Area Index and Clumping with Airborne Laser Scanning Data; Institute of Electrical and Electronics Engineers; IEEE Transactions on Geoscience and Remote Sensing; 62; 1-2024; 1-121558-0644CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1109/TGRS.2024.3353410info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-10T13:11:11Zoai:ri.conicet.gov.ar:11336/231935instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-10 13:11:12.15CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Comparison of Semi-Physical and Empirical Models in the Estimation of Boreal Forest Leaf Area Index and Clumping with Airborne Laser Scanning Data
title Comparison of Semi-Physical and Empirical Models in the Estimation of Boreal Forest Leaf Area Index and Clumping with Airborne Laser Scanning Data
spellingShingle Comparison of Semi-Physical and Empirical Models in the Estimation of Boreal Forest Leaf Area Index and Clumping with Airborne Laser Scanning Data
Zhang, Shaohui
AIRBORNE LASER SCANNING
CANOPY CLUMPING
FOREST CANOPY
LEAF AREA INDEX
LIGHT DETECTION AND RANGING
title_short Comparison of Semi-Physical and Empirical Models in the Estimation of Boreal Forest Leaf Area Index and Clumping with Airborne Laser Scanning Data
title_full Comparison of Semi-Physical and Empirical Models in the Estimation of Boreal Forest Leaf Area Index and Clumping with Airborne Laser Scanning Data
title_fullStr Comparison of Semi-Physical and Empirical Models in the Estimation of Boreal Forest Leaf Area Index and Clumping with Airborne Laser Scanning Data
title_full_unstemmed Comparison of Semi-Physical and Empirical Models in the Estimation of Boreal Forest Leaf Area Index and Clumping with Airborne Laser Scanning Data
title_sort Comparison of Semi-Physical and Empirical Models in the Estimation of Boreal Forest Leaf Area Index and Clumping with Airborne Laser Scanning Data
dc.creator.none.fl_str_mv Zhang, Shaohui
Korhonen, Lauri
Lang, Mait
Pisek, Jan
Díaz, Gastón Mauro
Korpela, Ilkka
Xia, Zhongyu
Haapala, Hanna
Maltamo, Matti
author Zhang, Shaohui
author_facet Zhang, Shaohui
Korhonen, Lauri
Lang, Mait
Pisek, Jan
Díaz, Gastón Mauro
Korpela, Ilkka
Xia, Zhongyu
Haapala, Hanna
Maltamo, Matti
author_role author
author2 Korhonen, Lauri
Lang, Mait
Pisek, Jan
Díaz, Gastón Mauro
Korpela, Ilkka
Xia, Zhongyu
Haapala, Hanna
Maltamo, Matti
author2_role author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv AIRBORNE LASER SCANNING
CANOPY CLUMPING
FOREST CANOPY
LEAF AREA INDEX
LIGHT DETECTION AND RANGING
topic AIRBORNE LASER SCANNING
CANOPY CLUMPING
FOREST CANOPY
LEAF AREA INDEX
LIGHT DETECTION AND RANGING
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.11
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv Leaf area index (LAI) is an important forest canopy variable that is related to various biophysical processes of forest ecosystems. Airborne laser scanning (ALS) has shown promise in modeling and mapping LAI using different types of ALS metrics. The most common ways of modeling LAI with ALS data are multivariate empirical models and the semi-physical model shape derived from the Beer–Lambert law of radiation attenuation. We tested the utility of ALS-based empirical and semi-physical models in the estimations of effective LAI (LAIe), canopy clumping index (Omega_E), and clumping-corrected LAI at three boreal forest sites in Finland. In semi-physical models, the all echo penetration index (API) showed consistently the best performance in predicting LAIe. It is, therefore, a robust and potentially the most transferable predictor using this model shape. Empirical models overall yielded slightly better model fits compared to the semi-physical models, yet they are also more prone to overfitting. In addition, empirical models had constantly lower accuracies when predicting LAI than LAIe. We also tested the utility of ALS-based multi-angular canopy gap fraction metrics that were derived from polar transformed ALS point clouds. Images derived from polar transformed point clouds can be analyzed similarly to digital hemispherical photographs (DHPs) to obtain canopy gap fractions. The results showed that polar metrics derived from polar transformed ALS data can provide supporting information to empirical models in the estimation of LAIe, LAI, and especially Omega_E. In particular, a combination of ALS penetration indices and polar metrics yielded positive results in Omega_E estimation.
Fil: Zhang, Shaohui. University Of Eastern Finland. Faculty Of Science And Forestry.; Finlandia
Fil: Korhonen, Lauri. University Of Eastern Finland. Faculty Of Science And Forestry.; Finlandia
Fil: Lang, Mait. University Of Tartu. Faculty Of Science And Technology. Tartu Observatory.; Estonia
Fil: Pisek, Jan. University Of Tartu. Faculty Of Science And Technology. Tartu Observatory.; Estonia
Fil: Díaz, Gastón Mauro. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Centro de Investigación y Extensión Forestal Andino Patagónico; Argentina
Fil: Korpela, Ilkka. University of Helsinki; Finlandia
Fil: Xia, Zhongyu. University Of Eastern Finland. Faculty Of Science And Forestry.; Finlandia
Fil: Haapala, Hanna. University Of Eastern Finland. Faculty Of Science And Forestry.; Finlandia
Fil: Maltamo, Matti. University Of Eastern Finland. Faculty Of Science And Forestry.; Finlandia
description Leaf area index (LAI) is an important forest canopy variable that is related to various biophysical processes of forest ecosystems. Airborne laser scanning (ALS) has shown promise in modeling and mapping LAI using different types of ALS metrics. The most common ways of modeling LAI with ALS data are multivariate empirical models and the semi-physical model shape derived from the Beer–Lambert law of radiation attenuation. We tested the utility of ALS-based empirical and semi-physical models in the estimations of effective LAI (LAIe), canopy clumping index (Omega_E), and clumping-corrected LAI at three boreal forest sites in Finland. In semi-physical models, the all echo penetration index (API) showed consistently the best performance in predicting LAIe. It is, therefore, a robust and potentially the most transferable predictor using this model shape. Empirical models overall yielded slightly better model fits compared to the semi-physical models, yet they are also more prone to overfitting. In addition, empirical models had constantly lower accuracies when predicting LAI than LAIe. We also tested the utility of ALS-based multi-angular canopy gap fraction metrics that were derived from polar transformed ALS point clouds. Images derived from polar transformed point clouds can be analyzed similarly to digital hemispherical photographs (DHPs) to obtain canopy gap fractions. The results showed that polar metrics derived from polar transformed ALS data can provide supporting information to empirical models in the estimation of LAIe, LAI, and especially Omega_E. In particular, a combination of ALS penetration indices and polar metrics yielded positive results in Omega_E estimation.
publishDate 2024
dc.date.none.fl_str_mv 2024-01
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/231935
Zhang, Shaohui; Korhonen, Lauri; Lang, Mait; Pisek, Jan; Díaz, Gastón Mauro; et al.; Comparison of Semi-Physical and Empirical Models in the Estimation of Boreal Forest Leaf Area Index and Clumping with Airborne Laser Scanning Data; Institute of Electrical and Electronics Engineers; IEEE Transactions on Geoscience and Remote Sensing; 62; 1-2024; 1-12
1558-0644
CONICET Digital
CONICET
url http://hdl.handle.net/11336/231935
identifier_str_mv Zhang, Shaohui; Korhonen, Lauri; Lang, Mait; Pisek, Jan; Díaz, Gastón Mauro; et al.; Comparison of Semi-Physical and Empirical Models in the Estimation of Boreal Forest Leaf Area Index and Clumping with Airborne Laser Scanning Data; Institute of Electrical and Electronics Engineers; IEEE Transactions on Geoscience and Remote Sensing; 62; 1-2024; 1-12
1558-0644
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1109/TGRS.2024.3353410
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers
publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 12.993085

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