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Structure Metrics to Generalize Biomass Estimation from Lidar across Forest Types from Different Continents

Knapp, Nikolai und Fischer, Rico und Cazcarra-Bes, Victor und Huth, Andreas (2020) Structure Metrics to Generalize Biomass Estimation from Lidar across Forest Types from Different Continents. Remote Sensing of Environment, 237 (111597), Seiten 1-14. Elsevier. doi: 10.1016/j.rse.2019.111597. ISSN 0034-4257.

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Kurzfassung

Forest aboveground biomass is a key variable in remote sensing based forest monitoring. Active sensor systems, such as lidar, can generate detailed canopy height products. Relationships between canopy height and biomass are commonly established via regression analysis using information from ground-truth plots. In this way, many site-specific height-biomass relationships have been proposed in the literature and applied for mapping in regional contexts. However, such relationships are only valid within the specific forest type for which they were calibrated. A generalized relationship would facilitate biomass estimation across forest types and regions. In this study, a combination of lidar-derived and ancillary structural descriptors is proposed as an approach for generalization between forest types. Each descriptor is supposed to quantify a different aspect of forest structure, i.e., mean canopy height, maximum canopy height, maximum stand density, vertical heterogeneity and wood density. Airborne discrete return lidar data covering 194 ha of forest inventory plots from five different sites including temperate and tropical forests from Africa, Europe, North, Central and South America was used. Biomass predictions using the best general model (nRMSE = 12.4%, R2 = 0.74) were found to be almost as accurate as predictions using five site-specific models (nRMSE = 11.6%, R2 = 0.78). The results further allow interpretation about the importance of the employed structure descriptors in the biomass estimation and the mechanisms behind the relationships. Understanding the relationship between canopy structure and aboveground biomass and being able to generalize it across forest types are important steps towards consistent large scale biomass mapping and monitoring using airborne and potentially also spaceborne platforms.

elib-URL des Eintrags:https://elib.dlr.de/133102/
Dokumentart:Zeitschriftenbeitrag
Titel:Structure Metrics to Generalize Biomass Estimation from Lidar across Forest Types from Different Continents
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Knapp, NikolaiDepartment of Ecological Modeling, Helmholtz Centre for Environmental Research (UFZ)NICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Fischer, RicoDepartment of Ecological Modeling, Helmholtz Centre for Environmental Research (UFZ)NICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Cazcarra-Bes, VictorVictor.CazcarraBes (at) dlr.dehttps://orcid.org/0000-0002-6776-4553NICHT SPEZIFIZIERT
Huth, AndreasDepartment of Ecological Modeling, Helmholtz Centre for Environmental Research (UFZ)NICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Datum:Februar 2020
Erschienen in:Remote Sensing of Environment
Referierte Publikation:Ja
Open Access:Nein
Gold Open Access:Nein
In SCOPUS:Ja
In ISI Web of Science:Ja
Band:237
DOI:10.1016/j.rse.2019.111597
Seitenbereich:Seiten 1-14
Verlag:Elsevier
ISSN:0034-4257
Status:veröffentlicht
Stichwörter:forest structure; aboveground biomass; canopy height; lidar; generalization
HGF - Forschungsbereich:Luftfahrt, Raumfahrt und Verkehr
HGF - Programm:Raumfahrt
HGF - Programmthema:Erdbeobachtung
DLR - Schwerpunkt:Raumfahrt
DLR - Forschungsgebiet:R EO - Erdbeobachtung
DLR - Teilgebiet (Projekt, Vorhaben):R - Vorhaben Tandem-L Vorstudien (alt)
Standort: Oberpfaffenhofen
Institute & Einrichtungen:Institut für Hochfrequenztechnik und Radarsysteme > Radarkonzepte
Hinterlegt von: Cazcarra-Bes, Victor
Hinterlegt am:19 Dez 2019 20:13
Letzte Änderung:14 Jan 2021 11:23

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