Vegetations are a vital part of our daily lives and are crucial for urban planning and the continuity of ecosystems. Accurate identification and delineation of individual trees in point cloud data is an important task in a variety of fields, including forestry, urban planning, and environmental management.
In this study, we have access to the Actueel Hoogtebestand Nederland (AHN) dataset, a publicly available high-resolution point cloud dataset generated by aerial laser scanning (ALS) throughout the Netherlands. The dataset that we will be using as the starting point for this study was previously labeled by the Amsterdam Intelligence team, with all tree points classified.
In this report, we present 2 different approaches for identifying individual trees. Both of the methods initial delineation is based on utilizing a KD-tree algorithm (Bentley, 1975) and vectors to make tree clusters. The first method identifies local maxima within a designated region through analysis of point density in that area. The second method uses some parameters to further split or merge the clusters.
A blog post summarizing the contributions can be found on amsterdamintelligence.com.
The related code is available here.
This research was conducted by Jorges Nofulla in collaboration with the department of Research and Statistics (Onderzoek en Statistiek, O&S) and the AI Team, Urban Innovation and R&D, City of Amsterdam.
Involved civil servants: Nico de Graaff & Daan Bloembergen
Supervisors: Sander Oude Elberink, Michael Ying Yang, Nico de Graaff & Daan Bloembergen
Header image: Banner - Individual Tree Delineation - Jorges Nofulla
Icon image: Banner - Individual Tree Delineation - Jorges Nofulla