Do You See What I See? Assessing the Relationships between Demographics, Street Trees and Visual Recognition of Urban Buildings Cover Image

Do You See What I See? Assessing the Relationships between Demographics, Street Trees and Visual Recognition of Urban Buildings
Do You See What I See? Assessing the Relationships between Demographics, Street Trees and Visual Recognition of Urban Buildings

Author(s): Yuen T. Tsang
Subject(s): Environmental Geography, Rural and urban sociology
Published by: Scientia Moralitas Research Institute
Keywords: Environmental Perception; Human-environment geography;

Summary/Abstract: As more “green” cities are emerging in the 21st century, human recognition of urban buildings can be obstructed by increasing amount of vegetation in urban areas. While the architectural designs of urban buildings are more complicated than before, architects often seek the maximum exposure of the design to public. If vegetation obstructs significant portions of an innovative design of a building, the visual value and attractiveness of the building can diminish greatly. People may not be able to retain much visual and spatial memories about a building or even a city because their views are obstructed. This paper begins with a thorough review of current and past literature about the relationship between buildings, street trees, and visibility in urban environments. The purpose of this research is to identify factors that influence visual recognizability of buildings in an urban environment such as distance away from buildings, presence of vegetation, frequent downtown visits, and physical forms of buildings using a geographic approach. The result can be beneficial to urban planners, architects, city planners, urban geographers, and city tourism board for better integrating vegetation and buildings in a cityscape. The goal of understanding people’s visual recognition and perception of urban objects is to raise inhabitant’s satisfaction, capture their attention, and make strong impressions towards the city.

  • Issue Year: 5/2020
  • Issue No: 2
  • Page Range: 89-119
  • Page Count: 31
  • Language: English