Urban security sense evaluation and optimization strategy based on multi-source big data: A case study of the main urban area of Nanjing

doi:10.3969/j.issn.1004-9479.2024.09.20222276

Abstract

Abstract:

Under the requirements of refined urban governance strategy, not only the construction of physical space security defense system, but also fully creating residents' sense for daily life security should be emphasized in urban security research, so as to improve the quality of the city and enhance its attractiveness. Firstly, this research fully considers the interaction among residents' activities, natural disasters, social risks and the built environment, and then constructs the urban security sense mechanism model. Secondly, the indicator system of urban security sense is established from three dimensions of personal sense, built environment and behavioral activities. Furthermore, it uses multi-source big data to synthetically measure residents' security sense, taking the main urban area of Nanjing as an example. Finally, this research evaluates the security sense in Nanjing City, explores its spatial distribution pattern, and puts forward the corresponding spatial optimization path. The results show that: the spatial pattern of residents' security sense in Nanjing City is wholly 'higher in the center and lower in the north & south, with obvious group distribution', although there are some differences in the three dimensions. The security sense is higher in the important business districts and their surrounding residential areas developed early, and it is lower in the developing new towns and the industrial supporting residential areas. Many optimization strategies can promote the security level of the low-security sense areas, including function implantation, transportation system design, public service facility layout, environmental feature restoration, community space design, planning policy guidance, organization system design and smart management platform construction.

Key words: urban security sense, multi-source big data, machine learning, the main urban area of Nanjing, spatial optimization

摘要：

城市精细化治理战略要求下，城市安全研究不仅需要关注物质空间安全防御体系建设，还应充分营造居民日常生活安全情感，以致力于提升城市品质、增强吸引力。首先，充分考虑居民活动与自然灾害、社会风险及建成环境之间的相互作用关系，构建城市安全感知机制模型；其次，从个人感知、建成环境、行为活动三个维度建立城市安全感评价指标体系；再者，以南京主城区为案例，利用多源大数据的创新手段对城市居民安全感进行综合测度；最后，对南京主城区安全感进行评价，识别其空间分布格局，提出其空间优化路径。研究发现：虽然在3个维度上居民安全感水平空间分布具有一定差异，但南京主城区居民安全感总体表现为“中部高南北低，组团分布明显”的空间分布格局；城市重要商圈及其周边较早开发的大型居住片区安全感高，而开发中新城和产业配套居住片区安全感低；活动功能植入、交通系统设计、公服设施布局、环境风貌修复、社区空间设计、规划政策引导、组织制度设计及智慧管理平台建设等能够更好地助力城市安全感低值区的安全水平提升。

关键词: 城市安全感, 多源大数据, 机器学习, 南京主城区, 空间优化

Xiao QIN, Yiming ZHANG, Feng ZHEN, Minjian LI. Urban security sense evaluation and optimization strategy based on multi-source big data: A case study of the main urban area of Nanjing[J]. World Regional Studies, 2024, 33(9): 118-132.

秦萧, 张一鸣, 甄峰, 李民健. 基于多源大数据的城市安全感评价与优化策略[J]. 世界地理研究, 2024, 33(9): 118-132.

Figures/Tables 10

Fig.1 Research area and boundary

Fig.2 Urban security sensation mechanism model

Tab.1 Urban security sense evaluation indicator system

一级指标	二级指标	三级指标	指标算法
城市安全感	个人感知安全（权重：0.434）	安全关注（ $C 1$ ）（权重：0.108）	网络舆情安全问题评论数量
	个人感知安全（权重：0.434）	安全情绪（ $C 2$ ）（权重：0.325）	网络舆情安全评论情绪值
	建成环境安全（权重：0.393）	街道环境安全（ $C 3$ ）（权重：0.295）	街景安全评分
	建成环境安全（权重：0.393）	公共设施周边安全（ $C 4$ ）（权重：0.098）	医院、学校、公园街景安全评分
	行为活动安全（权重：0.173）	夜间出行安全（ $C 7$ ）（权重：0.129）	0—7点每小时平均活动人次
	行为活动安全（权重：0.173）	社会交往安全（ $C 8$ ）（权重：0.045）	周末休闲出行活动人次

Tab.1 Urban security sense evaluation indicator system

一级指标	二级指标	三级指标	指标算法
城市安全感	个人感知安全（权重：0.434）	安全关注（ $C 1$ ）（权重：0.108）	网络舆情安全问题评论数量
	个人感知安全（权重：0.434）	安全情绪（ $C 2$ ）（权重：0.325）	网络舆情安全评论情绪值
	建成环境安全（权重：0.393）	街道环境安全（ $C 3$ ）（权重：0.295）	街景安全评分
	建成环境安全（权重：0.393）	公共设施周边安全（ $C 4$ ）（权重：0.098）	医院、学校、公园街景安全评分
	行为活动安全（权重：0.173）	夜间出行安全（ $C 7$ ）（权重：0.129）	0—7点每小时平均活动人次
	行为活动安全（权重：0.173）	社会交往安全（ $C 8$ ）（权重：0.045）	周末休闲出行活动人次

Fig.3 Distribution of security topics in residents’ micro blogs in the main urban area of Nanjing

Fig.4 Histogram of safety emotion value of residents in the main urban area of Nanjing

Tab.2 The relationship between n value and proportion of street attractions

序号	有效图片数量	街景点占比
1	n=4	71.2%
2	n=3	14.70%
3	n=2	7.4%
4	n=1	6.7%

Fig.5 Distribution of individual perceived security of residents in the main urban area of Nanjing

Fig.6 Distribution of built-up environment security of residents in the main urban area of Nanjing

Fig.7 Distribution of behavior activity security of residents in the main urban area of Nanjing

Fig.8 Distribution pattern of overall security sense in the main urban area of Nanjing

References 33

1	史斌,黄鹭. 城市防灾减灾规划的研究综述与展望. 华中建筑,2021,39(11):86-91.
	SHI B, HUANG L. Review and prospect of urban disaster prevention and reduction planning. Huazhong Architecture,2021,39(11):86-91.
2	翟国方,夏陈红. 我国韧性国土空间建设的战略重点. 城市规划,2021,45(2):44-48.
	ZHAI G, XIA C. Strategic emphasis on the construction of resilient cities in China. City Planning Review, 2021,45(2):44-48.
3	吕悦风,项铭涛,王梦婧,等. 从安全防灾到韧性建设——国土空间治理背景下韧性规划的探索与展望. 自然资源学报,2021,36(9):2281-2293.
	LYU Y, XIANG M, WANG M, et al. From disaster prevention to resilience construction: Exploration and prospect of resilience planning under the background of territorial governance. Journal of Natural Resources,2021,36(9):2281-2293.
4	夏慧怡. 随笔——城市公共安全感:社会心理视角下的安全城市规划浅谈. 中外建筑,2020(6):65-67.
	XIA H. Essays: On safe city planning from the perspective of social psychology of urban public security. Chinese & Overseas Architecture,2020(6):65-67.
5	张文忠. 宜居城市建设的核心框架. 地理研究,2016,35(2):205-213.
	ZHANG W. The core framework of the livable city construction. Geographical Research, 2016,35(2):205-213.
6	刘晓霞,肖鸿元,王兴中,等. 地理学的安全感研究:基于地点的综合理解、应用及展望. 人文地理,2018,33(5):38-45.
	LIU X, XIAO H, WANG X, et al. Geographical research on sense of safety: Comprehensive understanding, application and prospects based on place. Human Geography, 2018,33(5):38-45.
7	谌丽,许婧雪,张文忠,等. 居民城市公共安全感知与社区环境——基于北京大规模调查问卷的分析. 地理学报,2021,76(8):1939-1950.
	CHEN L, XU J, ZHANG W, et al. Residents' sense of urban public security and community environment: Analysis based on a large-scale questionnaire survey of Beijing. Acta Geographica Sinica,2021,76(8):1939-1950.
8	STAFFORD M, CHANDOLA T, MARMOT M. Association between fear of crime and mental health and physical functioning. American Journal of Public Health, 2007,97(11):2076-2081.
9	MACHADO C, MANITA C. Fear of crime: Methodological considerations and results from a biannual survey in the city of oporto. European Journal of Psychology Applied to Legal Context, 2009,1(1):69-99.
10	王发曾. 城市犯罪空间盲区分析与综合治理. 北京:商务印书馆, 2012.
	WANG F. Analysis and Comprehensive Treatment of Urban Crime Blind Areas. Beijing: The Commercial Press,2012.
11	王兴中,李九全,刘晓霞,等. 新常态下中国人文地理学空间探究的时代宿命. 人文地理,2016,31(4):1-8.
	WANG X, LI J, LIU X, et al. The era destiny of spatial research of human geography in the new normal. Human Geography, 2016,31(4):1-8.
12	王大为. 关于安全的几个基本理论问题. 中国人民公安大学学报,2004(3):26-35.
	WANG D. Some basic theoretical questions about security. Journal of People's Public Security University of China, 2004(3):26-35.
13	公安部公共安全研究所. 你感觉安全吗?——公众安全感基本理论及调查方法. 北京:群众出版社, 1991.
	Institute of Public Security, Ministry of Public Security. Do You Feel Safe? Basic Theory and Investigation Method of Public Security. Beijing: Mass Publishing House,1991.
14	王义保,许超,刘蕾,等. 中国城市公共安全感的状况与评价分析(2019). 中国应急管理科学,2020(2):17-27.
	WANG Y, XU C, LIU L, et al. The situation and evaluation of public security sense in urban China(2019). Journal of China Emergency Management Science,2020(2):17-27.
15	曹惠民,邓婷婷,杨怡文. 中国城市自然安全感现状与评价分析(2019). 中国应急管理科学,2020(2):28-39.
	CAO H, DENG T, YANG Y. The status quo and evaluation analysis of natural security sense in Chinese cities (2019). Journal of China Emergency Management Science,2020(2):28-39.
16	黄邓楷,王国光,陈芷筠. 广州大学城环境因素对学生安全感的影响研究. 南方建筑,2020(4):73-79.
	HUANG D, WANG G, CHEN Z. The impact of environmental factors on the perceived safety of students in the Guangzhou higher education mega center. South Architecture, 2020(4):73-79.
17	马雪梅,李诗岩. 基于AHP-AIP法的公园活动空间心理安全感知评价指标体系研究. 沈阳建筑大学学报(社会科学版),2022,24(1):28-34.
	MA X, LI S. Research on the psychological security perception evaluation system of park activity space based on AHP-AIP method. Journal of Shenyang Jianzhu University(Social Science), 2022,24(1):28-34.
18	NEWMAN O. Defensible Space. New York:Macmillan,1972.
19	戴维·R·戈德沙尔克, 许婵. 城市减灾: 创建韧性城市. 国际城市规划, 2015, 30(2): 22-29.
	DAVID R G, XU C. Urban hazard mitigation: Creating resilient cities. Urban Planning International, 2015, 30(2): 22-29.
20	张延吉,秦波,唐杰. 城市建成环境对居住安全感的影响——基于全国278个城市社区的实证分析. 地理科学,2017,37(9):1318-1325.
	ZHANG Y, QIN B, TANG J. The Influence of urban built-up environment on sense of residential security: Based on the empirical research of 278 communities in urban China. Scientia Geographica Sinica,2017,37(9):1318-1325.
21	张延吉,秦波,朱春武. 北京城市建成环境对犯罪行为和居住安全感的影响. 地理学报,2019,74(2):238-252.
	ZHANG Y, QIN B, ZHU C. The impact of urban built environment on criminal behavior and residential security in Beijing. Acta Geographica Sinica,2019,74(2):238-252.
22	陆明,张岩,刘晓霞,等. 社区公共空间安全视角下城市居民安全心理感知研究. 现代城市研究,2019(8):125-130.
	LU M, ZHANG Y, LIU X, et al. A research on the security psychological perception of urban residents from the perspective of community public space security. Modern Urban Research, 2019(8):125-130.
23	AL-HUSAIN L, KANJO E, CHAMBERLAIN A. Sense of space: Mapping physiological emotion response in urban space//ACM.Acm Conference on Pervasive & Ubiquitous Computing Adjunct Publication.New York:Association for Computing Machinery,2013:1321-1324.
24	吴先华,邹燚,郭际,等. 公众认知、感知价值与灾害气象服务满意度的关系研究——以深圳市3029份«公众气象安全认知度调查问卷»数据为例. 灾害学,2015,30(1):150-156.
	WU X, ZOU Y, GUO J, et al. The relationship among public cognition, perceived value, and satisfaction of disastrous weather service. Journal of Catastrophology, 2015,30(1):150-156.
25	陈映雪. 居民情绪与建成环境关系研究及规划应用初探. 南京:南京大学, 2015.
	CHEN Y. A study of relevance between residents' emotions and built environment: A preliminary research for emotion-based planning. Nanjing: Nanjing University,2015.
26	SALESSES P, SCHECHTNER K, HIDALGO C A. The collaborative image of the city: Mapping the inequality of urban perception. Plos One, 2013,8(7): e68400.
27	DUBEY A, NAIK N, PARIKH D, et al. Deep learning the city: Quantifying urban perception at a global scale//DANIILIDIS K, MARAGOS P, PARAGIOS N.European Conference on Computer Vision. Berlin: Springer,2016:196-212.
28	徐磊青,江文津,陈筝. 公共空间安全感研究:以上海城市街景感知为例. 风景园林,2018,25(7):23-29.
	XU L, JIANG W, CHEN Z. Study on perceived safety in public spaces: Take perception of street view in Shanghai as an example. Landscape Architecture,2018,25(7):23-29.
29	叶宇,张昭希,张啸虎,等. 人本尺度的街道空间品质测度——结合街景数据和新分析技术的大规模、高精度评价框架. 国际城市规划,2019,34(1):18-27.
	YE Y, ZHANG Z, ZHANG X, et al. Human-scale quality on streets: A large-scale and efficient analytical approach based on street view images and new urban analytical tools. Urban Planning International, 2019,34(1):18-27.
30	何宛余,李春,聂广洋,等. 深度学习在城市感知的应用可能——基于卷积神经网络的图像判别分析. 国际城市规划,2019,34(1):8-17.
	HE W, LI C, NIE G, et al. The latent application of deep learning in urban perception: Image discrimination analysis by convolutional neural network. Urban Planning International, 2019,34(1):8-17.
31	肖通,李德平,万义良,等. 基于街景影像和手机信令数据的城市街道安全性研究. 地理与地理信息科学,2022,38(1):71-78.
	XIAO T, LI D, WAN Y, et al. Research on urban street safety based on street view images and mobile signaling data. Geography and Geo-Information Science, 2022,38(1):71-78.
32	秦萧,甄峰. 大数据与小数据结合:信息时代城市研究方法探讨. 地理科学,2017,37(3):321-330.
	QIN X, ZHEN F. Combination between big data and small data: New methods of urban studies in the information era. Scientia Geographica Sinica, 2017,37(3):321-330.
33	江文津,徐磊青,陈筝. 城市安全感知与文化差异——以两个美国城市街景图片的实验为例. 住区,2018(6):23-30.
	JIANG W, XU L, CHEN Z. Perception of urban security and cultural differences: Case studies based on two American cities streetscape.Design Community, 2018(6):23-30.