Feasibility study on the estimation of the living vegetation volume of individual street trees using terrestrial laser scanning

Sun, Xinyu; Xu, Sheng; Hua, Weicheng; Tian, Jiarong; Xu, Yueren

doi:10.1016/j.ufug.2022.127553

Cited by 9 publications

(3 citation statements)

References 29 publications

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“…The concept of living vegetation volume (LVV) is an indicator for quantifying vegetation amount [64]. The crown volume fraction (CVF) is defined as the volume occupied by tree crowns within a street canyon section and is used to study traffic pollutant concentrations at the pedestrian level [65].…”

Section: Feasibility and Limitations Of Virtual Researchmentioning

confidence: 99%

Comparison of Crown Volume Increment in Street Trees among Six Cities in Western Countries and China

Guo,

Hu,

Qin

et al. 2024

Horticulturae

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The tree crown volume (CV), as a major indicator in the evaluation of ecological environment quality, can assess the health and carbon sequestration of urban trees. In this study, a new low-cost method, the plane calculation of angle disparity (PCAD), was employed to obtain the CV in China using satellite images from Google Earth. Meanwhile, primary data on street trees from four Western cities were acquired from online datasets. Nonparametric statistical methods showed no significant difference in CV per street tree between Beijing and Shanghai in China, ranging from 10 to 150 m3, almost one-seventh of that in the four cities (Paris and London in Europe and Los Angeles and Seattle in America). The CV of Platanus acerifolia in Paris and London exhibited values five times higher than those in Beijing and Shanghai. The annual crown volume increment (CVI) was less than 5 m3 in Beijing and Shanghai, significantly lower than in Seattle (66.55 m3). The purpose of the research was to verify the operability of the PCAD and compare the CVI in different cities all over the world, providing new ideas for urban tree management and carbon sequestration evaluation and a basis for government decision making in areas with a low CVI.

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Section: Feasibility and Limitations Of Virtual Researchmentioning

confidence: 99%

Comparison of Crown Volume Increment in Street Trees among Six Cities in Western Countries and China

Guo,

Hu,

Qin

et al. 2024

Horticulturae

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“…Evaluating the ecological value of street trees is of great importance, as it allows us to quantitatively understand their roles in air purification and mitigating environmental pollution [7]. The living vegetation volume (LVV) is one of the upmost indicators in the evaluation of the ecological benefits of urban street trees, and it is described as the volume of branches and leaves within the tree canopy (m 3 ) [8][9][10]. The LVV is highly correlated with the production capacity of trees, which is normally used to indicate the plant yield and ecological and economic benefits [11,12].…”

Section: Introductionmentioning

confidence: 99%

Estimation of the Living Vegetation Volume (LVV) for Individual Urban Street Trees Based on Vehicle-Mounted LiDAR Data

Yang,

Shen,

Cao

2024

Remote Sensing

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The living vegetation volume (LVV) can accurately describe the spatial structure of greening trees and quantitatively represent the relationship between this greening and its environment. Because of the mostly line shape distribution and the complex species of street trees, as well as interference from artificial objects, current LVV survey methods are normally limited in their efficiency and accuracy. In this study, we propose an improved methodology based on vehicle-mounted LiDAR data to estimate the LVV of urban street trees. First, a point-cloud-based CSP (comparative shortest-path) algorithm was used to segment the individual tree point clouds, and an artificial objects and low shrubs identification algorithm was developed to extract the street trees. Second, a DBSCAN (density-based spatial clustering of applications with noise) algorithm was utilized to remove the branch point clouds, and a bottom-up slicing method combined with the random sampling consistency iterative method algorithm (RANSAC) was employed to calculate the diameters of the tree trunks and obtain the canopy by comparing the variation in trunk diameters in the vertical direction. Finally, an envelope was fitted to the canopy point cloud using the adaptive AlphaShape algorithm to calculate the LVVs and their ecological benefits (e.g., O2 production and CO2 absorption). The results show that the CSP algorithm had a relatively high overall accuracy in segmenting individual trees (overall accuracy = 95.8%). The accuracies of the tree height and DBH extraction based on vehicle-mounted LiDAR point clouds were 1.66~3.92% (rRMSE) and 4.23~15.37% (rRMSE), respectively. For the plots on Zijin Mountain, the LVV contribution by the maple poplar was the highest (1049.667 m3), followed by the sycamore tree species (557.907 m3), and privet’s was the lowest (16.681 m3).

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“…Various evaluation indices have been proposed to quantify vegetation, including the normalized difference vegetation index (NDVI), leaf area index, living vegetation volume, green cover index, green visual ratio, and fractional vegetation cover [24][25][26][27][28][29]. NDVI is derived from a combination of linear and non-linear spectral bands, allowing it to capture the spatiotemporal growth and distribution of vegetation effectively.…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Variation and Pattern Analysis of Air Pollution and Its Correlation with NDVI in Nanjing City, China: A Landsat-Based Study

Sheng,

Ji,

Zhou

et al. 2023

Forests

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The rapid socio-economic development and urbanization in China have led to a decline in air quality. Therefore, the spatial and temporal distribution patterns of urban air pollution, as well as its formation mechanisms and influencing factors, have become important areas of research in atmospheric environment studies. This paper focuses on nine monitoring sites in Nanjing, where concentration data for six air pollutants and vegetation index data were collected from 2013 to 2021. The objective of this study is to investigate the changes in air pollutants and vegetation index over time and space, as well as their relationship with each other, and to assess the social and environmental impacts of air pollution. The findings reveal a spatial distribution pattern of air pollution in Nanjing that exhibits significant variability, with pollutant concentrations decreasing from the city center towards the surrounding areas. Notably, the main urban area has lower air quality compared to the peripheral regions. The results obtained from best-fit linear regression models and correlation heatmaps demonstrate a strong correlation (coefficient of determination, R2 > 0.5) between the normalized difference vegetation index (NDVI) and pollutants such as SO2, NO2, PM2.5, PM10, and O3 within a radial distance of 2 km from the air pollutant monitoring sites. These findings indicate that NDVI can be an effective indicator for assessing the distribution and concentrations of air pollutants. Negative correlations between NDVI and socio-economic indicators are observed under relatively consistent natural conditions, including climate and terrain. Therefore, the spatiotemporal distribution patterns of NDVI can provide valuable insights not only into socio-economic growth but also into the levels and locations of air pollution concentrations.

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Feasibility study on the estimation of the living vegetation volume of individual street trees using terrestrial laser scanning

Cited by 9 publications

References 29 publications

Comparison of Crown Volume Increment in Street Trees among Six Cities in Western Countries and China

Comparison of Crown Volume Increment in Street Trees among Six Cities in Western Countries and China

Estimation of the Living Vegetation Volume (LVV) for Individual Urban Street Trees Based on Vehicle-Mounted LiDAR Data

Spatiotemporal Variation and Pattern Analysis of Air Pollution and Its Correlation with NDVI in Nanjing City, China: A Landsat-Based Study

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