| 摘要: |
| 城市绿地具有生态、景观和社会等
多种服务功能，是健康城市环境的关键因
素。街道绿地影响着步行环境的质量，是衡
量步行舒适性的重要指标。绿视率为从人本
视角量化绿化环境的描述因子。针对当前可
步行性评价较少考虑步行环境这一问题，在
步行指数评价方法的基础上，基于路网、兴
趣点、百度街景等大数据，以步行指数表征
街道功能，以绿视率表征街道环境，对街道
可步行性进行综合评价。以福州市中心城区
进行实例研究，对比综合评价方法与步行指
数评价方法，探讨其与人口活动数量的关
系，并探索街道可步行性的影响因素。结果
表明：福州市中心城区内的街道可步行性平
均得分为58，街道可步行性较好，其中支
路、住宅类街道的可步行性最高；整体上，
综合评价方法与人口活动数量的正相关系数
为0.313，较步行指数评价方法提高0.018；
不同交通等级的街道绿化环境对可步行性有
不同的影响，支路的绿视率水平与可步行性
存在显著的正相关关系（r=0.135）。 |
| 关键词: 绿视率 可步行性 街景 街道绿
地 步行指数 |
| DOI：10.13791/j.cnki.hsfwest.20231031001 |
| 分类号: |
| 基金项目:国家自然科学基金项目（41971344） |
|
| Evaluation of street walkability considering green view index |
|
TANG Liyu,HUANG Ziqing,SU Honglin
|
| Abstract: |
| Urban green space has a variety of ecological, landscape and social service functions. It is
an important component of urban green infrastructure and public service facilities, as well as a key
factor in a healthy urban environment. Walking plays an essential role in protecting the environment
and promoting health, and promoting the walkability of streets helps to increase social vitality and
promote sustainable development. Streets have been proven to surpass parks as the most popular
places for walking and physical activity. Therefore, it is extremely critical to quantify the walkability
of streets and consider the visual experience of greenery for pedestrians. The Walk Score method is
now a commonly used method to measure walkability. The method focuses on measuring the
convenient accessibility of walking, such as the spatial layout of stores, parks, and other amenities.
However, the environmental aesthetic value of street green spaces influences the quality of the
pedestrian environment and promotes the motivation of residents to be active, which is realized
through the visual participation of people and is an important indicator of walking comfort. In the
context of the big data era, new sources of data are constantly emerging. Street view images may
capture the green information in a vertical dimension for the indirect representation of people’s
perspective on the ground. Moreover, the green view index (GVI) estimated using Baidu Street View
images to represent urban street greening, as an emerging green space evaluation index, providing a
new way of thinking to quantify the green environment from a human perspective. The GVI was
proposed by Japanese scholars and is defined as the percentage of green pixels in the person’s field of
view. In recent years, GVI has been incorporated into governmental terminology and has been highly
emphasized in China. Aiming at the problem that the current walkability evaluation rarely considers
the walking environment, a comprehensive evaluation of street walkability was made on the basis of
big data such as road network, point of interest and Baidu street view images. The street function was
characterized by the Walk Score, and the street environment was characterized by the GVI. On the
basis of Walk Score, the GVI was introduced to evaluate the walkability index of the street
comprehensively. In addition, the number of population activities were extracted using the Baidu heat
map. Taking Fuzhou downtown as a case study, the comprehensive evaluation method was compared
with the Walk Score evaluation method. Its relationship with population activity was explored, and the
variables influencing street walkability were examined. The average score of the comprehensive
evaluation of street walkability in the study area is 58, which means that the street walkability in
Fuzhou downtown is good. Among the streets of different traffic levels and functional types, the
streets with the highest walkability are branch roads and residential streets, respectively. Overall, the
positive correlation coefficient between the comprehensive evaluation method and the number of
population activities is 0.313, which is 0.018 higher than the Walk Score. However, among the
different traffic classes, the correlation between the comprehensive evaluation method and population
activity is slightly higher than the Walk Score for both branch and secondary roads, and slightly lowerfor primary roads. Street environments with different traffic classes have different effects on walkability. In particular, there is a significant positive correlation
between the GVI and walkability of branch roads (r=0.135). The configuration of public services, GVI, and vegetation diversity all showed significant
correlations with street walkability. When the configuration of public services is difficult to improve in a short period of time, increasing the GVI by planting
large trees and increasing the diversity of street vegetation may be a convenient way to enhance walkability. The comprehensive street walkability evaluation
method in this paper is feasible and optimizes the walking index method to some extent. The analytical approach is applicable for other cities. It provides a new
idea for the quantitative evaluation of street walkability, and has certain guiding significance for the planning of pedestrian system and the improvement and
enhancement of street green space environment. |
| Key words: green view index walkability street view image street green space walk score |
