Song, Qian und Albrecht, Conrad M und Xiong, Zhitong und Zhu, Xiao Xiang (2022) Towards Global Forest Biomass Estimators from Tree Height Data. In: International Geoscience and Remote Sensing Symposium (IGARSS), Seiten 5652-5655. IEEE. IGARSS 2022, 2022-07-17 - 2022-07-22, Kuala Lumpur, Malaysia. doi: 10.1109/IGARSS46834.2022.9884904.
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Offizielle URL: https://ieeexplore.ieee.org/document/9884904
Kurzfassung
In order to estimate tree biomass, allometric equations take tree parameters such as tree height, wood density, circumference of trunk, and crown diameter as input parameters. Given that most of these quantities are challenging to be extracted from remote sensing data, we evaluate the option to approximate biomass by tree height only. We study our approach by evaluating linear regression, random forest, and Gaussian process regressor models when applied to the 2016 Jucker dataset. Results indicate that linear models fail to properly capture the relationship between biomass and tree height, but the Gaussian process regressor outperms the other two candidate models.
elib-URL des Eintrags: | https://elib.dlr.de/186183/ | ||||||||||||||||||||
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Dokumentart: | Konferenzbeitrag (Poster) | ||||||||||||||||||||
Titel: | Towards Global Forest Biomass Estimators from Tree Height Data | ||||||||||||||||||||
Autoren: |
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Datum: | 2022 | ||||||||||||||||||||
Erschienen in: | International Geoscience and Remote Sensing Symposium (IGARSS) | ||||||||||||||||||||
Referierte Publikation: | Ja | ||||||||||||||||||||
Open Access: | Ja | ||||||||||||||||||||
Gold Open Access: | Nein | ||||||||||||||||||||
In SCOPUS: | Ja | ||||||||||||||||||||
In ISI Web of Science: | Nein | ||||||||||||||||||||
DOI: | 10.1109/IGARSS46834.2022.9884904 | ||||||||||||||||||||
Seitenbereich: | Seiten 5652-5655 | ||||||||||||||||||||
Verlag: | IEEE | ||||||||||||||||||||
Status: | veröffentlicht | ||||||||||||||||||||
Stichwörter: | Tree biomass estimation, allometric equation, random forest models, Gaussian process regression | ||||||||||||||||||||
Veranstaltungstitel: | IGARSS 2022 | ||||||||||||||||||||
Veranstaltungsort: | Kuala Lumpur, Malaysia | ||||||||||||||||||||
Veranstaltungsart: | internationale Konferenz | ||||||||||||||||||||
Veranstaltungsbeginn: | 17 Juli 2022 | ||||||||||||||||||||
Veranstaltungsende: | 22 Juli 2022 | ||||||||||||||||||||
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 - Künstliche Intelligenz | ||||||||||||||||||||
Standort: | Oberpfaffenhofen | ||||||||||||||||||||
Institute & Einrichtungen: | Institut für Methodik der Fernerkundung > EO Data Science | ||||||||||||||||||||
Hinterlegt von: | Song, Qian | ||||||||||||||||||||
Hinterlegt am: | 21 Apr 2022 11:36 | ||||||||||||||||||||
Letzte Änderung: | 24 Apr 2024 20:47 |
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