Open AccessUrban Environment Evaluation and Analysis Based on Street View Image
Author(s) -
Jing Chen,
Xiaoxuan Wang,
Yujing Wu,
Bing Shi
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1881/4/042081
Subject(s) - adaptability , visualization , computer science , urban area , urban park , urban landscape , measure (data warehouse) , urban environment , geography , artificial intelligence , data mining , environmental planning , economy , economics , biology , ecology
The real and intuitive reconstruction of the city street scene can not only give the viewer an immersive feeling, but also serve as a way to display information. As a mass data, it also provides unique decision-making ideas for recording phenomena, discovering rules and predicting results. This paper proposes a green visual rate to measure the green apparent area of urban street trees. For complex urban street landscapes, the green apparent area index can well reflect the visualization degree of green area of street trees and urban environment under street scenes. Research to Skesfehervar, Hungary as an example, it carried out the street tree green apparent area calculation model test research in different characteristics of road sections, different street scenes under the authenticity and adaptability.