Mapping the urban forest in detail: From LiDAR point clouds to 3D tree models

Münzinger, Markus; Prechtel, Nikolas; Behnisch, Martin

doi:10.1016/j.ufug.2022.127637

Cited by 38 publications

(17 citation statements)

References 61 publications

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“…The geographical distribution of urban forest ES influences on housing prices, and costs versus benefits of urban forest management are highly limited to countries such as the U.S., China, and those in Europe. These specific neighborhood-level tree cover and city level forest cover needs can be ascertained using LiDAR point cloud data and multispectral imagery to detect and reconstruct individual tree crowns and represent them within 3D city models [ 82 , 83 ]. RS technologies cover extensive spatial areas and provide historical data over a longer period of time, which can be used to conduct large-scale studies across cities to measure urban forests biomass for carbon credits payments, vegetation greenness, ES, detect tree health and forest fragmentation, and monitor urban forest fire.…”

Section: Discussionmentioning

confidence: 99%

Influence of urban forests on residential property values: A systematic review of remote sensing-based studies

Ewane,

Bajaj,

Velasquez-Camacho

et al. 2023

Heliyon

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Section: Discussionmentioning

confidence: 99%

Influence of urban forests on residential property values: A systematic review of remote sensing-based studies

Ewane,

Bajaj,

Velasquez-Camacho

et al. 2023

Heliyon

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“…Münzinger et al. (2022) used local maxima filtering and marker‐controlled watershed segmentation to delineate individual trees from the CHM. Li et al.…”

Section: Methodsmentioning

confidence: 99%

A new method for voxel‐based modelling of three‐dimensional forest scenes with integration of terrestrial and airborne LiDAR data

Li,

Hu,

et al. 2024

Methods Ecol Evol

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Simulating realistic three‐dimensional (3D) forest scenes is useful in understanding the links between forest structure and ecosystem functions (e.g. radiative transfer). Light detection and ranging (LiDAR) technology provides useful 3D data for forest reconstructions since it can characterise 3D structures of individual trees and canopies. High‐density terrestrial LiDAR (terrestrial laser scanning, TLS) is suitable for fine‐scale reconstructions but is limited to smaller forest plots; low‐density airborne LiDAR (airborne laser scanning, ALS) can cover larger areas but is only suitable for coarse‐scale reconstructions. How to take advantage of TLS and ALS to enable fine‐scale forest simulations in large areas needs to be studied. We propose a new voxel‐based method for forest simulations using the integration of TLS and ALS data. TLS data of representative reference trees are used to approximate the detailed architectures of the whole forest scene, with structural information on each individual tree extracted from ALS data. The high‐density point cloud data derived from TLS and ALS data are voxelised using high resolution solid voxels for scene representation. We tested the proposed method using two virtual forests (108 m × 108 m) and a real forest (300 m × 300 m) with conifer and broadleaf species. The physically based ray tracer (PBRT) was used to visualise the true virtual forest scenes, whereas voxel‐based radiative transfer (VBRT) was used to visualise the modelled forest scenes from LiDAR data. For the real forest scene, simulated and real ALS data were compared. Our results demonstrate that the images simulated by VBRT and PBRT are similar in the virtual forest scenes, with average radiance values of 1.02 and 1.72, respectively. In the real forest scene, the distributions of points and individual tree attributes (tree height, crown radius, and tree volume) derived from real and simulated ALS also match well, with Kullback–Leibler divergence ranging from 0.006 to 0.06. We conclude that the new method is capable of modelling fine‐scale 3D forests in large areas (over 1 ha) when TLS and ALS data are available, and it has good potential in studying the process of radiative transfer in conifer and broadleaf forests.

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“…Application of LiDAR, DSM, DTM data for the developing 3D tall greenery models has been the subject of various scientific research e.g. studies for Oslo identifying ecosystem condition indicators (Hanssen et al 2022, Gobeawan et al 2018, just to mention the achievements of the Dresden team, that enables tree crown reconstruction with geometric primitives overlaid on the point cloud (Münzinger, Prechtel and Behnisch 2022). Although the complexity of the analyses undertaken by Dresden-based researchers is significantly larger and more advanced than the solutions discussed in the article, the resulting model does not increase the accuracy and specificity of 3D city model necessary e.g.…”

Section: Other Methodsmentioning

confidence: 99%

“…The paper presents methods used to generate theoretical DSM models of a city with and without tall greenery as a component extracted from the 3D model. The term 'tall greenery', also referred to in literature as 'urban forest' (Münzinger, Prechtel and Behnisch 2022) -refers to trees in parks or squares in the city, trees planted in rows along streets, trees next to residential or commercial buildings and others. In this sense, tall greenery is a component of a spatial structure, which in many cities is comparable to buildings in terms of its volume (Figure 1).…”

Section: Introductionmentioning

confidence: 99%

Separation of Tall Greenery Component in 3D City Models Based on Lidar Data

Rubinowicz¹

2023

CAADRIA Proceedings

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The research analyses the possibility of separating tall greenery as a spatial component of the city in a 3D model based on LiDAR data. This applies in particular to Digital Surface Models (DSMs). The paper presents methods to generate theoretical DSMs of a city without tall greenery and tall greenery only as a component extracted from the 3D model. The first method is based on the use of GIS data, including 2D building outlines. The second method requires additional manual contouring of tall greenery. Both methods have been applied by the author in the planning practice in several cities in Europe.Results of the research are discussed in the article based on the example of Szczecin, Poland. It includes the preparation process, visualisations of theoretical DSM models (buildings without tall greenery and tall greenery only) and their application in urban analyses concerning e.g. protection and development of the cityscape. All simulations have been performed using C++ software developed by the author.

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Mapping the urban forest in detail: From LiDAR point clouds to 3D tree models

Cited by 38 publications

References 61 publications

Influence of urban forests on residential property values: A systematic review of remote sensing-based studies

Influence of urban forests on residential property values: A systematic review of remote sensing-based studies

A new method for voxel‐based modelling of three‐dimensional forest scenes with integration of terrestrial and airborne LiDAR data

Separation of Tall Greenery Component in 3D City Models Based on Lidar Data

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