地理
可行走性
地图学
城市景观
开放的体验
计算机科学
环境规划
建筑环境
土木工程
工程类
心理学
社会心理学
作者
Xiaojiang Li,Carlo Ratti,Ian Seiferling
出处
期刊:Lecture notes in geoinformation and cartography
日期:2017-01-01
卷期号:: 341-356
被引量:42
标识
DOI:10.1007/978-3-319-57336-6_24
摘要
City streets are a focal point of human activity in urban centers. Citizens interact with the urban environment through its streetscape and it is imperative to, not only map city streetscapes, but quantify those interactions in terms of human well-being. Researchers now have access to fully digitized representation of streetscapes through Google Street View (GSV) Google Street View (GSV), which captures the profile view of streetscapes and, thus, shares equivalent viewing angles with those of the citizen. These two facets—a wealth of streetscape photographs at city-scale and a shared perspective with the end user—underscore the potential of these data in street-level urban landscape Urban landscape mapping. In this study, we introduce two examples that demonstrate GSV as a high-quality data source for mapping street greeneryStreet greenery and openness. First, the modified green view index, which estimates the visibility of street greenery, was applied to static GSV images in order to map the spatial distribution of street greenery. Second, GSV panoramas were used to quantify and map the openness of street canyons by applying a geometrical transformation and image classification Classification to the panoramas. The results of these two novel applications of street-level photographic data illustrate its utility for quantifying and mapping key urban environmental features at the same viewpoint in which we, as citizens, experience the urban landscape.
科研通智能强力驱动
Strongly Powered by AbleSci AI