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TERRESTRIAL 3D MAPPING OF FORESTS: GEOREFERENCING CHALLENGES AND SENSORS COMPARISONS

Cyprien Raymi Fol · Arnadi Murtiyoso · Daniel Kükenbrink · Fabio Remondino · Verena Christiane Griess

˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences · 19 Oct 2023 · 10.5194/isprs-archives-xlviii-1-w3-2023-55-2023

Abstract

Abstract. Terrestrial 3D reconstruction is a research topic that has recently received significant attention in the forestry sector. This practice enables the acquisition of high-quality 3D data, which can be used not only to derive physical forest criteria such as tree positions and diameters, but also more detailed analyses related to ecological parameters such as habitat availability and biomass. However, several challenges must be addressed before fully integrating this technology into forestry practices. The primary challenge is accurately georeferencing surveyed 3D data acquired in the same location and placing them into a national projection reference system. Unfortunately, due to the forest canopy, the GNSS signal is often obstructed, and it cannot guarantee sub-meter accuracy. In this paper, we have implemented an indirect georeferencing methodology based on spheres with known coordinates placed at the forest’s edge where GNSS reception was more reliable and accurate than under the canopy. We evaluated its performance through three analyses that confirmed the validity of our approach. Indeed, the accuracy of the TLS point cloud, georeferenced using our method, is within a centimetre level (4.7 cm), whereas mobile scanning methods demonstrate accuracy within the decimetre range but still less than a metre. Additionally, we have initiated the analysis of a potential future application for mixed reality headsets, which could enable real-time acquisition and visualisation of 3D data.

Code and data availability

The paper describes TLS/mobile point cloud georeferencing and tree-position analyses in a Baden marteloscope, but no blocks contain any data availability statement, public dataset deposit, or author code release. The only URLs are the article DOI and the authors' institutional site (3dom.fbk.eu), neither of which is a

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