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This repository contains scripts for high-resolution area-wide mapping and 3D modeling of urban forests based on LiDAR point clouds. The workflow is designed for widely available LiDAR point clouds with a density of at least 4 pts/m². Our published research article: Münzinger, M., Prechtel, N., & Behnisch, M. (2022). Mapping the Urban Forest in Detail: From LiDAR Point Clouds to 3D Tree Models. Available at https://doi.org/10.1016/j.ufug.2022.127637. Processing Tasks: Task 1: Classification of the urban forest in an object-based data fusion approach combining the point cloud with multispectral aerial imagery and a 3D building model Task 2: Detection, segmentation and parameterization of individual tree crowns Task 3: Efficient reconstruction and 3D modeling of tree crowns using geometric primitives
LiDAR point cloud classification, 3D City Modeling, Urban Forestry, R, Individual Tree Segmentation, CityGML
LiDAR point cloud classification, 3D City Modeling, Urban Forestry, R, Individual Tree Segmentation, CityGML
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