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Potential of Mobile Mapping to Create Digital Twins of Forests

Iwaszczuk, Dorota ; Goebel, Mona ; Du, Yijie ; Schmidt, Jakob ; Weinmann, Martin (2023)
Potential of Mobile Mapping to Create Digital Twins of Forests.
12th International Symposium on Mobile Mapping Technology (MMT 2023). Padua, Italy (24-26 May 2023)
doi: 10.5194/isprs-archives-XLVIII-1-W1-2023-199-2023
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

Forests are irreplaceable and are being studied extensively. Better forest inventory and understanding necessitate effective mapping, modeling, and automatic analysis. As a result, considerable research effort is being devoted to digitizing forest environments. Recently, digital twins have come to the attention of the geospatial community as a virtual representation of the Earth’s surface linked to its corresponding physical asset. This concept is applicable to forests and has been studied in the literature. This requires initial input data obtained through reality capture. Among mapping techniques, laser scanning has emerged as a state-of-the-art technology for vegetation modeling. In this paper, we look into the potential of mobile laser scanning for forest digital twinning. While most studies concentrate on single tree detection, modeling, and estimation of dendrometric parameters, we also include lower vegetation in our investigations. To accomplish this, we first detect single trees and then investigate different vegetation densities and levels using geometric metrics. We also demonstrate how to model the underlying layers of vegetation in a digital twin. We perform the tests on data from mobile laser scanning (MLS) and compare the results to those from airborne laser scanning (ALS).We show that single tree detection based on crown separation using MLS data works similarly to or slightly better than ALS data. Furthermore, we demonstrate that MLS data allows for more detailed analysis of understory vegetation taking into account different height levels and a multi-level representation, whereas ALS data only allows for rough analysis of the lower parts of forest vegetation.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2023
Autor(en): Iwaszczuk, Dorota ; Goebel, Mona ; Du, Yijie ; Schmidt, Jakob ; Weinmann, Martin
Art des Eintrags: Bibliographie
Titel: Potential of Mobile Mapping to Create Digital Twins of Forests
Sprache: Englisch
Publikationsjahr: 24 März 2023
Ort: Padua, Italy
Verlag: Copernicus Publications
Titel der Zeitschrift, Zeitung oder Schriftenreihe: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Reihe: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Band einer Reihe: XLVIII-1/W1-2023
Veranstaltungstitel: 12th International Symposium on Mobile Mapping Technology (MMT 2023)
Veranstaltungsort: Padua, Italy
Veranstaltungsdatum: 24-26 May 2023
DOI: 10.5194/isprs-archives-XLVIII-1-W1-2023-199-2023
Kurzbeschreibung (Abstract):

Forests are irreplaceable and are being studied extensively. Better forest inventory and understanding necessitate effective mapping, modeling, and automatic analysis. As a result, considerable research effort is being devoted to digitizing forest environments. Recently, digital twins have come to the attention of the geospatial community as a virtual representation of the Earth’s surface linked to its corresponding physical asset. This concept is applicable to forests and has been studied in the literature. This requires initial input data obtained through reality capture. Among mapping techniques, laser scanning has emerged as a state-of-the-art technology for vegetation modeling. In this paper, we look into the potential of mobile laser scanning for forest digital twinning. While most studies concentrate on single tree detection, modeling, and estimation of dendrometric parameters, we also include lower vegetation in our investigations. To accomplish this, we first detect single trees and then investigate different vegetation densities and levels using geometric metrics. We also demonstrate how to model the underlying layers of vegetation in a digital twin. We perform the tests on data from mobile laser scanning (MLS) and compare the results to those from airborne laser scanning (ALS).We show that single tree detection based on crown separation using MLS data works similarly to or slightly better than ALS data. Furthermore, we demonstrate that MLS data allows for more detailed analysis of understory vegetation taking into account different height levels and a multi-level representation, whereas ALS data only allows for rough analysis of the lower parts of forest vegetation.

Fachbereich(e)/-gebiet(e): 13 Fachbereich Bau- und Umweltingenieurwissenschaften
13 Fachbereich Bau- und Umweltingenieurwissenschaften > Institut für Geodäsie
13 Fachbereich Bau- und Umweltingenieurwissenschaften > Institut für Geodäsie > Fernerkundung und Bildanalyse
Hinterlegungsdatum: 30 Mai 2023 05:47
Letzte Änderung: 30 Mai 2023 08:28
PPN: 508168392
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