Quantifying the shape of urban street trees and evaluating its influence on their aesthetic functions based mobile lidar data

2022 ◽  
Vol 184 ◽  
pp. 203-214
Author(s):  
Tianyu Hu ◽  
Dengjie Wei ◽  
Yanjun Su ◽  
Xudong Wang ◽  
Jing Zhang ◽  
...  
Keyword(s):  
Lidar Data ◽  
Street Trees ◽  
Urban Street

Effects of varying establishment approaches on the growth of urban street trees

2018 ◽  
Vol 40 (4) ◽  
pp. 201-209 ◽  
Author(s):  
Lai Fern Ow ◽  
Subhadip Ghosh ◽  
Yusof Mohamed Lokman Mohd.
Keyword(s):  
Street Trees ◽  
Urban Street

scholarly journals No Stump City: The Contestation and Politics of Urban Street-Trees – A Case Study of Sheffield

2019 ◽  
Vol 12 (3) ◽  
pp. 188-203 ◽  
Author(s):  
Ian Rotherham ◽  
◽  
Matthew Flinders
Keyword(s):  
Street Trees ◽  
Urban Street

scholarly journals Mobile Terrestrial Photogrammetry for Street Tree Mapping and Measurements

Forests ◽  
2019 ◽  
Vol 10 (8) ◽  
pp. 701 ◽  
Author(s):  
John Roberts ◽  
Andrew Koeser ◽  
Amr Abd-Elrahman ◽  
Benjamin Wilkinson ◽  
Gail Hansen ◽  
...  
Keyword(s):  
Point Cloud ◽  
Coordinate Systems ◽  
Street Trees ◽  
Urban Street ◽  
Tree Management ◽  
Tree Inventory ◽  
Street Tree ◽  
Wide Scale ◽  
Individual Trees ◽  
Urban Sites

Urban forests are often heavily populated by street trees along right-of-ways (ROW), and monitoring efforts can enhance municipal tree management. Terrestrial photogrammetric techniques have been used to measure tree biometry, but have typically used images from various angles around individual trees or forest plots to capture the entire stem while also utilizing local coordinate systems (i.e., non-georeferenced data). We proposed the mobile collection of georeferenced imagery along 100 m sections of urban roadway to create photogrammetric point cloud datasets suitable for measuring stem diameters and attaining positional x and y coordinates of street trees. In a comparison between stationary and mobile photogrammetry, diameter measurements of urban street trees (N = 88) showed a slightly lower error (RMSE = 8.02%) relative to non-mobile stem measurements (RMSE = 10.37%). Tree Y-coordinates throughout urban sites for mobile photogrammetric data showed a lower standard deviation of 1.70 m relative to 2.38 m for a handheld GPS, which was similar for X-coordinates where photogrammetry and handheld GPS coordinates showed standard deviations of 1.59 m and the handheld GPS 2.36 m, respectively—suggesting higher precision for the mobile photogrammetric models. The mobile photogrammetric system used in this study to create georeferenced models for measuring stem diameters and mapping tree positions can also be potentially expanded for more wide-scale applications related to tree inventory and monitoring of roadside infrastructure.

A 3-Year Study of Water Relations of Urban Street Trees

1992 ◽  
Vol 29 (2) ◽  
pp. 436 ◽  
Author(s):  
Thomas H. Whitlow ◽  
Nina L. Bassuk ◽  
Deborah L. Reichert
Keyword(s):  
Water Relations ◽  
Street Trees ◽  
Urban Street

scholarly journals High-Quality Solid Fuel Production from Leaf Litter of Urban Street Trees

2016 ◽  
Vol 8 (12) ◽  
pp. 1249 ◽  
Author(s):  
Nodirjon Nurmatov ◽  
Daniel Leon Gomez ◽  
Frank Hensgen ◽  
Lutz Bühle ◽  
Michael Wachendorf
Keyword(s):  
Leaf Litter ◽  
Solid Fuel ◽  
Fuel Production ◽  
Street Trees ◽  
High Quality ◽  
Urban Street

Use of Aerial LiDAR in Measuring Streetscape and Street Trees

2019 ◽  
Vol 2673 (4) ◽  
pp. 125-135 ◽  
Author(s):  
Yaneev Golombek ◽  
Wesley E. Marshall
Keyword(s):  
United States ◽  
Statistical Tests ◽  
The United States ◽  
Tree Canopy ◽  
Quality Level ◽  
United States Geological Survey ◽  
Lidar Data ◽  
Street Trees ◽  
Street Tree ◽  
Remote Sensing Techniques

This paper investigates the usefulness of 3D volumetric pixels (voxels) and the United States Geological Survey (USGS) Quality Level 2 (QL2) Light Detection and Ranging (LiDAR) data to measure features in streetscapes. As the USGS embarks on a national LiDAR database with the goal of covering the entire United States of America (U.S.) with QL2 data or better, this paper investigates uses of QL2 LiDAR for the 3D measuring of streetscapes. Tree mapping is a common use of QL2 LiDAR data, and street trees are among the most common features within urban streetscapes that transportation and urban designers assess. Traditional remote sensing techniques derive tree polygons from imagery, and traditional uses of LiDAR for tree canopy mapping is based on deriving a 2D canopy polygon with an attribute for elevation height. However, when breaking up streetscapes into 5 Ft elevation zones and calculating street–tree voxels at each elevation zone height, 3D characteristics of street trees become prevalent that completely differ from the common 2D LiDAR-derived street trees. Statistical tests in this paper display how different the 3D characteristics are from the 2D-derived LiDAR polygons, as this paper introduces a new methodology for measuring streetscape features in 3D, particularly street trees.

Stemflow chemistry of urban street trees

1997 ◽  
Vol 96 (1) ◽  
pp. 107-109 ◽  
Author(s):  
Masahiro Takagi ◽  
Shigeyuki Sasaki ◽  
Koichiro Gyokusen ◽  
Akira Saito
Keyword(s):  
Street Trees ◽  
Urban Street

scholarly journals Responses of gas-exchange rates and water relations to annual fluctuations of weather in three species of urban street trees

2014 ◽  
Vol 34 (10) ◽  
pp. 1056-1068 ◽  
Author(s):  
Y. Osone ◽  
S. Kawarasaki ◽  
A. Ishida ◽  
S. Kikuchi ◽  
A. Shimizu ◽  
...  
Keyword(s):  
Gas Exchange ◽  
Exchange Rates ◽  
Water Relations ◽  
Street Trees ◽  
Urban Street

scholarly journals Effects of urban street trees on human thermal comfort and physiological indices: a case study in Changchun city, China

2021 ◽  
Author(s):  
Zhibin Ren ◽  
Hongbo Zhao ◽  
Yao Fu ◽  
Lu Xiao ◽  
Yulin Dong
Keyword(s):  
Blood Pressure ◽  
Thermal Comfort ◽  
Thermal Environment ◽  
Physiological Parameters ◽  
Tree Cover ◽  
Street Trees ◽  
Urban Street ◽  
Human Thermal Comfort ◽  
Physiological Indices ◽  
Urban Thermal Environment

AbstractPlanting trees along urban streets is one of the most important strategies to improve the urban thermal environment. However, the net impacts of urban street trees on human thermal comfort and physiological parameters are still less clear. On three similar east–west orientated streets with different degrees of tree cover—low (13%), medium (35%), and high (75%), urban microclimatic parameters and human physiological indices for six male students were simultaneously measured on three cloudless days in summer 2018. The results show that the differences in tree cover were predominant in influencing urban thermal environment and comfort. The street with the highest tree cover had significantly lower physiological equivalent temperature (PET) and more comfortable than the other two streets. The frequency of strong heat stress (PET > 35 °C) was 64%, 11%, and 0%, respectively, for streets with low, medium, and high tree cover. For the six male university students, human physiological indices varied greatly across the three streets with different tree cover. Systolic blood pressure, diastolic blood pressure, and pulse rate increased with decreasing tree cover. The results also suggest that urban thermal environment and comfort had considerable impact on human physiological parameters. Our study provides reasons for urban planners to plant trees along streets to improve the thermal environment and promote urban sustainability.

scholarly journals Street Tree Inventory of Campinas, Brazil: An Instrument for Urban Forestry Management and Planning

2015 ◽  
Vol 41 (5) ◽  
Author(s):  
Ivan André Alvarez ◽  
Bruna Cristina Gallo ◽  
Edlene Aparecida Monteiro Garçon ◽  
Osvaldo Tadatomo Oshiro
Keyword(s):  
Satellite Images ◽  
Urban Forestry ◽  
Metropolitan Region ◽  
High Concentration ◽  
Street Trees ◽  
Urban Street ◽  
Palm Trees ◽  
Forestry Management ◽  
Tree Inventory ◽  
Street Tree

Campinas Metropolitan Region is the third richest city in Brazil. This study assesses the urban street trees of Campinas based on data from a survey performed using satellite images in the year 2011. All public domain trees in the street system were counted and separated into trees, shrubs, palm trees, and seedlings. The density of trees was obtained using the images census and expressed as trees per linear kilometer for the perimeter of the block. The number of trees per linear kilometer was grouped into nine classes of different densities for data validation. The final number of trees was estimated based on the validation’s results. The Gini coefficient shows that the number of trees per person is very irregular in city neighborhoods (i.e., Campinas has a fairer income distribution than street trees distribution). There is a lower density of trees in the downtown area, due to the high concentration of population, and in more peripheral neighborhoods, due to the lack of design planning. The results obtained here may be used to support a new setting of local priorities for planting actions aimed at urban forestry management.

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