街道绿化：一个新的可步行性评价指标
Street Greenery: A New Indicator for Evaluating Walkability
郝新华
北京清华同衡规划设计研究院有限公司 规划师，硕士
摘要: 街道绿化对居民尤其是行人的生活质量至关重要，是评估街道可步行性的重要指标之一。传统受限于数据获取的困难，对街道
绿化的研究多局限于较小的地域，而目前运用新兴的街景图片进行评价的方法也多基于人工判断。通过构建一种自动的方法，
实现了大规模、精细化尺度的街道绿化的量化评价，并以成都一、二圈层的街道为案例进行实践。研究发现：成都街道以不绿和
一般绿街道为主；二圈层的街道绿化好于一圈层的街道；东部、北部个别街道绿化较好，南部、西部整体绿化相对较好；绿化相对
较好的街道主要与大学、公园景点、河流两侧、居住区有关；街道绿化与道路等级、街道周边地块性质、区位等相关。对步行系统
规划、街道品质改善提升等工作具有一定的指导意义。
Abstract: We propose an automatic method using emerging online street view service for quantitatively evaluating greenery at street level in a large area,
and then apply it for analyzing street greenery in the first and second circle of Chengdu, one of large cities in the west of China. We calculate the
greenery of each street by Green Looking Ratio, one index suitable for evaluating visible greenery. We find that (1) streets closer to city center
tend to be less green; (2) greener streets of Chengdu are more frequently related with the riverside, parks, spots and communities in the fringe of
core area; (3) different road grade and different land use around show different greenery of streets. The findings may help draft more appropriate
policies in planning and engineering practices for street greenery.
关键词：可见绿、 绿视率、 街景、 街道城市主义、可步行性、成都
Keyword: Visible greenery 、 Green Looking Ratio 、 Street view、Street urbanism 、Walkability、 Chengdu
中图分类号：TU981
文献标识码: A
[1]Howard E. To-morrow: a peaceful path to real
reform[M]. Cambridge: Cambridge University
Press, 2010.
[2]韩昊英，龙瀛. 绿色还是绿地？——北京市第一道绿化隔离带实施成效研究[J]. 北京规划建设，2010（3）：59-63.
HAN Haoying, LONG Ying. Green or green
land? research about implementation of first green
isolation belt in Beijing[J]. Beijing Planning
Review, 2010(3): 59-63.
[3]Aoki Y. Relationship between perceived greenery
and width of visual fields[J]. Journal of the
Japanese Institute of Landscape Architects, 1987,
51 (1): 1-10.
[4]Ohno R. A hypothetical model of environmental
perception[M]. New York: Springer US, 2000.
[5]Yang J, Zhao L, Mcbride J, et al. Can you see
green? assessing the visibility of urban forests
in cities[J]. Landscape & Urban Planning, 2009,
91(2):97-104.
[6]龙瀛，叶宇. 人本尺度城市形态：测度、效应评估
及规划设计响应[J]. 南方建筑，2016（5）：39-
45.
LONG Ying, YE Yu. Humanistic scale of urban
morphology: measurement, effect assessment and
design implication[J]. South Architecture, 2016(5):
39-45.
[7]郝新华，龙瀛，石淼，等.北京街道活力：测度、影响因素与规划设计启示[J]. 上海城市规划，2016（3）：37-45.
HAO Xinhua, LONG Ying, SHI Miao, et al.
Street vibrancy of Beijing: measurement, impact
factors and design implication[J]. Shanghai Urban
Planning Review, 2016 (3):37-45.
[8]龙瀛. 街道城市主义——新数据环境下城市研究与规划设计的新思路[J]. 时代建筑2016（2）：
128-132.
LONG Ying. Street urbanism: a new perspective
for urban studies and city planning in the new data
environment[J]. Time Architecture, 2016(2):128-
132.
[9]龙瀛，周垠. 街道活力的量化评价及影响因素分析—以成都为例[J]. 新建筑，2016（1）：52-57.
LONG Ying, ZHOU Yin. Quantitative evaluation on
street vibrancy and its impact factors: a case study
of Chengdu[J]. New Architecture, 2016(1):52-57.
[10]唐婧娴，龙瀛，翟炜，等. 街道空间品质的测度、变化评价与影响因素识别——基于大规模多时相街景图片的分析[J]. 新建筑，2016（5）：130-135.
TANG Jingxian, LONG Ying, DI Wei, et al.Measurement, change evaluation and impact
factors identification of quality of street space
based on analysis of large-scale and multi-temporal
street view[J]. New Architecture, 2016 (5): 130-
135.
[11]唐婧娴，龙瀛. 特大城市中心区街道空间品质的测度：以北京二三环和上海内环为例[J]. 规划师（待发表）.
TANG Jingxian, LONG Ying. Measurement of
quality of street space in central urban area of
megacity with examples of second and third ring of
Beijing and inner ring of Shanghai[J]. Planners (In
press).
[12]龙瀛，周垠. 成都街道可步行性评价[EB/OL].
https://geohey.com/apps/dataviz/fbacf0f113e94569
88f8e27f373a61e2/share?ak=ZmYzNmY0ZWJhYj
cwNGU2ZGExNDgxMWUxNmZiOWNhNGY.
LONG Ying, ZHOU Yin. Evaluation of street
walkability of Chengdu[EB/OL]. https://geohey.
com/apps/dataviz/fbacf0f113e9456988f8e27f373a
61e2/share?ak=ZmYzNmY0ZWJhYjcwNGU2ZG
ExNDgxMWUxNmZiOWNhNGY.
[13]Rundle A G, Bader M D M, Richards C A, et al.
Using Google Street View to audit neighborhood
environments[J]. American Journal of Preventive
Medicine, 2011, 40(1):94-100.
[14]Odgers C L, Caspi A, Bates C J, et al. Systematic
social observation of children’s neighborhoods
using Google Street View: a reliable and costeffective
method[J]. Journal of Child Psychology
& Psychiatry, 2012 (53):1009-1017.
[15]Kelly C M, Wilson J S, Baker E A, et al. Using
Google Street View to audit the built environment:
inter-rater reliability results[J]. Annals of
Behavioral Medicine, 2013, 45(1):108-112.
[16]Liu M Y, Lin S, Ramalingam S, et al. Layered
interpretation of street view images[J]. Computer
Science, 2015 (10):393-396.
[17]Liu L, Zhou B, Zhao J, et al. C-IMAGE: city
cognitive mapping through geo-tagged photos[J].
Geojournal, 2014: 1-45.
[18]Li X, Zhang C, Li W, et al. Assessing street-level
urban greenery using Google Street View and a
modified green view index[J]. Urban Forestry &
Urban Greening, 2015,14(3):675-685.
[19]Li X, Zhang C, Li W, et al. Who lives in greener
neighborhoods? the distribution of street greenery
and its association with residents’ socioeconomic
conditions in Hartford, Connecticut, USA[J]. Urban
Forestry & Urban Greening,2015, 14(4):100-106.
[20]Li X, Zhang C, Li W, et al. Environmental
inequities in terms of different types of urban
greenery in Hartford, Connecticut[J]. Urban
Forestry & Urban Greening, 2016 (18):163-172.
