Geomatic Data Fusion for 3D Tree Modeling: The Case Study of Monumental Chestnut Trees

Abstract

In recent years, advancements in remote and proximal sensing technology have driven innovation in environmental and land surveys. The integration of various geomatics devices, such as reflex and UAVs equipped with RGB cameras and mobile laser scanners (MLS), allows detailed and precise surveys of monumental trees. With these data fusion method, we reconstructed three monumental 3D tree models, allowing the computation of tree metric variables such as diameter at breast height (DBH), total height (TH), crown basal area (CBA), crown volume (CV) and wood volume (WV), even providing information on the tree shape and its overall conditions. We processed the point clouds in software such as CloudCompare, 3D Forest, R and MATLAB, whereas the photogrammetric processing was conducted with Agisoft Metashape. Three-dimensional tree models enhance accessibility to the data and allow for a wide range of potential applications, including the development of a tree information model (TIM), providing detailed data for monitoring tree health, growth, biomass and carbon sequestration. The encouraging results provide a basis for extending the virtualization of these monumental trees to a larger scale for conservation and monitoring.

Plant phenotyping relevance

複数のリモートセンシングデータを融合して樹木の3Dモデルを再構築し、DBH・樹高・樹冠面積・樹冠体積・木材体積などの植物形態形質を算出する手法が中心である。

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