title: Assessing visual green effects of individual urban trees using airborne Lidar data.
abstract: Urban trees benefit people's daily life in terms of air quality, local climate, recreation and aesthetics. Among these functions, a growing number of studies have been conducted to understand the relationship between residents' preference towards local environments and visual green effects of urban greenery. However, except for on-site photography, there are few quantitative methods to calculate green visibility, especially tree green visibility, from viewers' perspectives. To fill this research gap, a case study was conducted in the city of Cambridge, which has a diversity of tree species, sizes and shapes. Firstly, a photograph-based survey was conducted to approximate the actual value of visual green effects of individual urban trees. In addition, small footprint airborne Lidar (Light detection and ranging) data was employed to measure the size and shape of individual trees. Next, correlations between visual tree green effects and tree structural parameters were examined. Through experiments and gradual refinement, a regression model with satisfactory R2 and limited large errors is proposed. Considering the diversity of sample trees and the result of cross-validation, this model has the potential to be applied to other study sites. This research provides urban planners and decision makers with an innovative method to analyse and evaluate landscape patterns in terms of tree greenness.
authors.affiliation: College of Global Change and Earth System Science, Beijing Normal University, 19 Xinjiekouwai Street, Haidian, Beijing 100875, China; Joint Center for Global Change Studies, Beijing 100875, China. Electronic address: zychen@bnu.edu.cn.
authors.forename: Ziyue
authors.initials: Z
authors.lastname: Chen
authors.affiliation: College of Global Change and Earth System Science, Beijing Normal University, 19 Xinjiekouwai Street, Haidian, Beijing 100875, China; School of Environment, Tsinghua University, Beijing 100084, China; Department of Geography, University of Utah, Salt Lake City, UT, USA.
authors.forename: Bing
authors.initials: B
authors.lastname: Xu
authors.affiliation: State Key Laboratory of Resources and Environmental Information Systems, Institute of Geographic Sciences and Nature Resources Research, Chinese Academy of Sciences, A11 Datun Road, Beijing 100101, China.
authors.forename: Bingbo
authors.initials: B
authors.lastname: Gao
mesh_terms: D018533:Biomass; D002947:Cities / Q000706:statistics & numerical data; D003116:Color; D004784:Environmental Monitoring / Q000379:methods*; D063809:Satellite Imagery; D014197:Trees / Q000254:growth & development*
keywords: Landscape analysis; Lidar; Regression model; Visual greenness