基于居民时空行为的社区日常活动空间测度及活力影响因素研究——以南京市沙洲、南苑街道为例

doi:10.18306/dlkxjz.2021.04.004

Abstract

Abstract:

In the new era of China's development, people's needs for living space have become diversified. At the community level, the transformation of the planning of a human-oriented community life circle needs to pay attention to residents' daily activities to use the community space, thereby reflecting residents' use of community public service facilities. This demands to identify the daily activity space of residents. However, current research has paid little attention to the differentiated spatial and temporal behavior characteristics of different types of residents, and cannot effectively respond to the diverse needs of community residents. Based on the theory of behavioral geography, this research proposed a method of using mobile phone signaling data to measure the core activity space and flexible activity space based on the frequency and density of residents' travel activities, and then analyze the characteristics of daily activities of different types of people. Taking Shazhou and Nanyuan streets in Nanjing City as examples, the daily activity space of adolescent, youth, middle-aged, and elderly resident groups in different communities was delineated, and the basic characteristics of residents'use of community space were analyzed from the perspective of daily activity range and vitality differences among groups. The research results show that the daily activity space of residents shows hierarchical, sharing, and directional features, and there are significant differences in the daily activity space of different age groups. Further, by using the correlation test to analyze the influencing factors of the vitality of different groups of the communities, we proposed a differentiated supply strategy for public service facilities that considers the activity space and facility needs of different groups. This research is helpful for improving the method of measuring the daily activity space of community based on the spatiotemporal behavior of residents, and enriching the understanding of the diverse behavior needs of community residents. The conclusions of the empirical research have certain guiding significance for the allocation of community public service facilities based on residents' diverse space and facility needs.

Key words: differentiated spatiotemporal behavior, daily activity space, mobile phone signaling data, community planning, Nanjing City

ZOU Sicong, ZHANG Shanqi, ZHEN Feng. Measurement of community daily activity space and influencing factors of vitality based on residents’ spatiotemporal behavior: Taking Shazhou and Nanyuan streets in Nanjing as examples[J].PROGRESS IN GEOGRAPHY, 2021, 40(4): 580-596.

Figures/Tables 15

Fig.1

Tab.1

Tab.2

Fig.2

Tab.3

Fig.3

Tab.4

Tab.5

社区	活动空间类型	教育	文化	休闲	商业	养老	医疗	体育
爱达社区	核心	14.72	10.51	8.41	51.51	2.10	21.02	10.51
爱达社区	弹性	51.51	34.69	54.66	158.73	13.67	88.30	57.82
话园社区	核心	5.68	5.14	5.68	39.20	0.27	7.85	5.95
话园社区	弹性	36.50	12.98	16.50	57.62	2.16	27.86	18.40
黄山路社区	核心	21.36	13.14	0	16.43	0	8.07	11.36
黄山路社区	弹性	67.36	19.43	17.43	280.93	3.29	12.29	22.64
吉庆社区	核心	15.52	13.19	9.31	47.85	0.78	24.06	17.76
吉庆社区	弹性	41.91	31.82	59.76	106.44	6.21	76.83	58.98
科技园社区	核心	28.21	12.82	10.26	230.77	5.13	20.51	84.62
科技园社区	弹性	97.44	84.62	123.08	525.64	15.38	146.15	230.77
莲花社区	核心	3.10	1.33	3.99	41.91	1.55	5.54	1.77
莲花社区	弹性	7.32	4.00	6.21	75.38	2.00	11.53	9.31
庐山社区	核心	13.44	8.06	7.17	69.57	1.79	16.13	19.71
庐山社区	弹性	47.49	38.53	51.15	195.34	1.79	69.89	140.68
鹭鸣苑社区	核心	11.18	14.37	14.37	52.69	1.60	20.76	17.56
鹭鸣苑社区	弹性	45.51	32.73	55.89	220.36	4.79	79.84	64.67
清荷社区	核心	4.40	1.83	4.76	52.75	1.83	6.23	2.93
清荷社区	弹性	8.79	4.40	9.52	100.37	3.30	16.12	6.96
双和园社区	核心	1.31	2.61	3.92	49.67	0.65	4.58	10.54
双和园社区	弹性	9.15	12.42	17.65	159.48	1.96	17.00	31.37
泰山路社区	核心	7.16	0	5.68	35.58	1.30	12.53	15.37
泰山路社区	弹性	33.11	18.79	17.90	89.49	4.47	51.90	38.48
兴达社区	核心	11.90	11.11	7.94	37.78	1.79	16.67	8.73
兴达社区	弹性	42.86	31.75	52.38	89.37	3.97	76.98	67.46
怡康社区	核心	6.80	3.40	3.91	42.14	0.21	9.71	14.86
怡康社区	弹性	23.80	15.54	18.45	61.19	3.40	31.08	23.80
中奥社区	核心	5.80	3.87	7.25	69.15	1.23	6.29	23.06
中奥社区	弹性	43.06	12.09	24.99	136.85	1.45	34.51	68.19
中城社区	核心	4.31	4.71	5.88	55.69	0	3.92	11.37
中城社区	弹性	60.98	18.24	22.16	178.41	0.78	34.12	57.25
中胜社区	核心	4.80	1.92	4.80	63.36	1.96	6.92	18.24
中胜社区	弹性	12.48	11.52	20.16	210.25	1.96	16.32	45.12
中央商务社区	核心	5.60	6.40	14.39	129.53	1.56	8.00	35.59
中央商务社区	弹性	54.79	22.39	34.38	261.45	1.60	58.78	130.33

Tab.5

Tab.6

Tab.7

Fig.4

Fig.5

Fig.6

Fig.7

Fig.8

References 32

[1]	张文佳, 柴彦威. 居住空间对家庭购物出行决策的影响[J]. 地理科学进展, 2009, 28(3):362-369.
	Zhang Wenjia, Chai Yanwei. The influence of residential space on household shopping tour decision-making behaviors. Progress in Geography, 2009, 28(3):362-369.
[2]	韩增林, 李源, 刘天宝, 等. 社区生活圈公共服务设施配置的空间分异分析: 以大连市沙河口区为例[J]. 地理科学进展, 2019, 38(11):1701-1711.
	Han Zenglin, Li Yuan, Liu Tianbao, et al. Spatial differentiation of public service facilities' configuration in community life circle: A case study of Shahekou District in Dalian City. Progress in Geography, 2019, 38(11):1701-1711.
[3]	柴彦威, 张雪, 孙道胜. 基于时空间行为的城市生活圈规划研究: 以北京市为例[J]. 城市规划学刊, 2015(3):61-69.
	Chai Yanwei, Zhang Xue, Sun Daosheng. A study on life circle planning based on space time behavioural analysis: A case study of Beijing. Urban Planning Forum, 2015(3):61-69.
[4]	索超. 基于居民行为特征的社区生活圈边界测度方法探索:以江苏省宜兴市为例 [C]// 中国城市科学研究会, 郑州市人民政府, 河南省自然资源厅, 河南省住房和城乡建设厅. 2019城市发展与规划论文集. 北京: 中国城市科学研究会, 2019:232-238.
	Suo Chao. Method exploring of the community daily life circle boundary measurement based on resident's behavior characteristics: Take Yixing as an example // China Urban Science Research Association, Zhengzhou Municipal People's Government, Henan Provincial Department of Natural Resources, Housing and Urban-Rural Development Department of Henan Province. 2019 Urban development and planning papers. Beijing, China: China Urban Science Research Association, 2019:232-238.
[5]	孙道胜, 柴彦威. 城市社区生活圈体系及公共服务设施空间优化: 以北京市清河街道为例[J]. 城市发展研究, 2017, 24(9):7-14, 25, 2.
	Sun Daosheng, Chai Yanwei. Study on the urban community life sphere system and the optimization of public service facilities: A case study of Qinghe area in Beijing. Urban Development Studies, 2017, 24(9):7-14, 25, 2.
[6]	张晓兰, 朱秋. 东京都市圈演化与发展机制研究[J]. 现代日本经济, 2013(2):66-72.
	Zhang Xiaolan, Zhu Qiu. A study on the evolution and development mechanism of Tokyo metropolitan area. Contemporary Economy of Japan, 2013(2):66-72.
[7]	肖作鹏, 柴彦威, 张艳. 国内外生活圈规划研究与规划实践进展述评[J]. 规划师, 2014, 30(10):89-95.
	Xiao Zuopeng, Chai Yanwei, Zhang Yan. Overseas life circle planning and practice. Planners, 2014, 30(10):89-95.
[8]	柴彦威, 李春江, 夏万渠, 等. 城市社区生活圈划定模型: 以北京市清河街道为例[J]. 城市发展研究, 2019, 26(9):1-8, 68.
	Chai Yanwei, Li Chunjiang, Xia Wanqu, et al. Study on the delineation model of urban community life circle: Based on Qinghe District in Haidian District, Beijing. Urban Development Studies, 2019, 26(9):1-8, 68.
[9]	孙德芳, 沈山, 武廷海. 生活圈理论视角下的县域公共服务设施配置研究: 以江苏省邳州市为例[J]. 规划师, 2012, 28(8):68-72.
	Sun Defang, Shen Shan, Wu Ting-hai. Life circle theory based county public service distribution: Jiangsu Pizhou case. Planners, 2012, 28(8):68-72.
[10]	贺建雄. 西安城市居民日常生活空间供需耦合研究[D]. 西安: 西北大学, 2018.
	He Jianxiong. Study on the supply and demand coupling of Xi'an urban residents' daily living space. Xi'an, China: Northwest University, 2018.
[11]	季珏, 高晓路. 基于居民日常出行的生活空间单元的划分[J]. 地理科学进展, 2012, 31(2):248-254.
	Ji Jue, Gao Xiaolu. Identifying the scope of daily life in urban areas based on residents' travel behaviors. Progress in Geography, 2012, 31(2):248-254.
[12]	Newsome T H, Walcott W A, Smith P D. Urban activity spaces: Illustrations and application of a conceptual model for integrating the time and space dimensions[J]. Transportation, 1998, 25(4):357-377.
[13]	Schönfelder S, Axhausen K W. Activity spaces: Measures of social exclusion? [J]. Transport Policy, 2003, 10(4):273-286.
[14]	Fan Y L, Khattak A J. Urban form, individual spatial footprints, and travel: Examination of space-use behavior[J]. Transportation Research Record: Journal of the Transportation Research Board, 2008, 2082:98-106.
[15]	申悦, 柴彦威. 基于GPS数据的北京市郊区巨型社区居民日常活动空间[J]. 地理学报, 2013, 68(4):506-516.
	Shen Yue, Chai Yanwei. Daily activity space of suburban mega-community residents in Beijing based on GPS data. Acta Geographica Sinica, 2013, 68(4):506-516.
[16]	孙道胜, 柴彦威, 张艳. 社区生活圈的界定与测度: 以北京清河地区为例[J]. 城市发展研究, 2016, 23(9):1-9.
	Sun Daosheng, Chai Yanwei, Zhang Yan. The definition and measurement of community life circle: A case study of Qinghe area in Beijing. Urban Development Studies, 2016, 23(9):1-9.
[17]	Xi G L, Zhen F, He J L, et al. City networks of online commodity services in China: Empirical analysis of Tmall clothing and electronic retailers[J]. Chinese Geographical Science, 2018, 28(2):231-246.
[18]	闫晴, 李诚固, 陈才, 等. 基于手机信令数据的长春市活动空间特征与社区分异研究[J]. 人文地理, 2018, 33(6):35-43.
	Yan Qing, Li Chenggu, Chen Cai, et al. Characteristics of activity space and community differentiation in Changchun: A study using mobile phone signaling data. Human Geography, 2018, 33(6):35-43.
[19]	Zhen F, Wang B, Wei Z C. The rise of the internet city in China: Production and consumption of internet information[J]. Urban Studies, 2015, 52(13):2313-2329.
[20]	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[J]. 地理科学, 2017, 37(3):321-330.
	Qin Xiao, Zhen Feng. Combination between big data and small data: New methods of urban studies in the information era. Scientia Geographica Sinica, 2017, 37(3):321-330.
[21]	张姗琪, 甄峰, 秦萧, 等. 面向城市社区规划的参与式感知与计算: 概念模型与技术框架[J]. 地理研究, 2020, 39(7):1580-1591.
	Zhang Shanqi, Zhen Feng, Qin Xiao, et al. The conceptual model and technical framework of participatory sensing and computing for urban community planning. Geographical Research, 2020, 39(7):1580-1591.
[22]	王德, 傅英姿. 手机信令数据助力上海市社区生活圈规划[J]. 上海城市规划, 2019(6):23-29.
	Wang De, Fu Yingzi. Mobile signaling data helps Shanghai community life circle planning. Shanghai Urban Planning Review, 2019(6):23-29.
[23]	张昱, 张若楠. 生活圈视角下中小城市公共服务设施配置研究[J]. 山西农经, 2020(2):107-108.
	Zhang Yu, Zhang Ruonan. Research on the allocation of public service facilities in small and medium cities from the perspective of life circle. Shanxi Agricultural Economics, 2020(2):107-108.
[24]	王德. 《基于大数据的城市研究与规划方法创新》评述[J]. 地理学报, 2016, 71(6):1089.
	Wang De. Comment on " Urban research and planning method innovation based on big data" . Acta Geographica Sinica, 2016, 71(6):1089.
[25]	郑彩云. 基于居民生活圈视角的武汉老城区民生设施配套研究 [C]// 中国城市规划学会, 重庆市人民政府. 活力城乡美好人居:2019中国城市规划年会论文集. 北京: 中国城市规划学会, 2019:268-278.
	Zheng Caiyun. Research on the supporting facilities of people's livelihood in the old city of Wuhan based on the perspective of residents' life circle // China Urban Planning Society, Chongqing Municipal People's Government. Vibrant urban and rural, beautiful habitat:Proceedings of China urban planning annual conference 2019. Beijing, China: China Urban Planning Society, 2019:268-278.
[26]	刘倩. 居民需求视角下社区生活圈配套设施优化策略研究:以西安市雁塔区为例[D]. 西安: 西北大学, 2019.
	Liu Qian. Research on optimization strategies of supporting facilities in community life circle from the perspective of residents' demand: A case study of Yanta District in Xi'an City. Xi'an, China: Northwest University, 2019.
[27]	钟炜菁, 王德. 基于居民行为周期特征的城市空间研究[J]. 地理科学进展, 2018, 37(8):1106-1118.
	Zhong Weijing, Wang De. Urban space study based on the temporal characteristics of residents' behavior. Progress in Geography, 2018, 37(8):1106-1118.
[28]	中华人民共和国住房和城乡建设部. 中华人民共和国国家标准: 城市居住区规划设计标准 GB 50180—2018 [S]. 北京: 中国建筑工业出版社, 2018.
	Ministry of Housing and Urban-Rural Development of the People's Republic of China. National Standard (Mandatory) of the People's Republic of China: Standard for urban residential area planning and design. GB 50180-2018. Beijing, China: China Architecture & Building Press, 2018.
[29]	Hägerstrand T. What about people in regional science? [J]. Papers of the Regional Science Association, 1970, 24(1):6-21.
[30]	王海洋. 福田中心区公共空间活力时空分布特征及其影响因素研究[D]. 哈尔滨: 哈尔滨工业大学, 2016.
	Wang Haiyang. Study on spatial temporal distribution characteristics of public space vitality and its influencing factors in Futian central district. Harbin, China: Harbin Institute of Technology, 2016.
[31]	罗桑扎西, 甄峰. 基于手机数据的城市公共空间活力评价方法研究: 以南京市公园为例[J]. 地理研究, 2019, 38(7):1594-1608.
	Luo Sangzhaxi, Zhen Feng. How to evaluate public space vitality based on mobile phone data: An empirical analysis of Nanjing's parks. Geographical Research, 2019, 38(7):1594-1608.
[32]	端木一博, 柴彦威. 社区设施供给与居民需求的时空间匹配研究: 以北京清上园社区为例[J]. 地域研究与开发, 2018, 37(6):76-81.
	Duanmu Yibo, Chai Yanwei. Space-time matching between community facilities and residents' demand: A case of Qingshangyuan Community in Beijing. Areal Research and Development, 2018, 37(6):76-81.

南苑街道			沙洲街道
社区名称	人口数/人	面积/hm²	社区名称	人口数/人	面积/hm²
鹭鸣苑社区	12525	93.4	中城社区	25500	146.4
话园社区	36966	114.5	中奥社区	20679	133.9
爱达社区	9513	56.8	中胜社区	10416	141.6
吉庆社区	12885	64.3	双和园社区	15300	104.7
兴达社区	12600	66.9	中央商务区	12507	174.5
怡康社区	20592	68.4	科技园社区	3900	450.5
黄山路社区	6087	79.6	清荷社区	27300	72.2
庐山社区	11160	154.9	莲花社区	45102	218.8
泰山路社区	11175	118.1

类别	项目	数量/个
商业餐购	美食、购物中心、百货商场、超市、便利店、商铺、集市	1464
教育培训	幼儿园、小学、中学	204
医疗卫生	综合医院、专科医院、诊所、药店	301
休闲娱乐	公园、休闲广场、棋牌室	228
体育运动	体育场馆、健身中心	359
养老福利	养老机构	51
文化服务	文化活动中心、文化宫、图书馆、科技馆、电影院	159

街道	社区	青少年(0~18岁)		青年(19~34岁)		中年(35~60岁)		老年(60岁以上)
街道	社区	人数/人	占比/%	人数/人	占比/%	人数/人	占比/%	人数/人	占比/%
南苑街道	鹭鸣苑社区	142	4.26	1581	47.46	1378	41.37	230	6.90
	话园社区	58	3.05	730	38.38	866	45.53	248	13.04
	爱达社区	109	2.34	2728	58.49	1524	32.68	303	6.50
	吉庆社区	31	1.58	745	38.07	952	48.65	229	11.70
	兴达社区	35	3.10	364	32.21	550	48.67	181	16.02
	怡康社区	36	3.47	464	44.70	487	46.92	51	4.91
	黄山路社区	2	1.18	69	40.59	86	50.59	13	7.65
	庐山社区	184	4.98	1499	40.58	1747	47.29	264	7.15
	泰山路社区	101	2.56	2288	57.92	1369	34.66	192	4.86
沙洲街道	中城社区	31	2.03	608	39.82	789	51.67	99	6.48
	中奥社区	144	3.33	2376	54.91	1577	36.45	230	5.32
	中胜社区	3	0.80	212	56.38	138	36.70	23	6.12
	双和园社区	14	3.09	274	60.49	144	31.79	21	4.64
	中央商务社区	73	2.86	1384	54.32	936	36.73	155	6.08
	科技园社区	46	2.24	1220	59.37	667	32.46	122	5.94
	清荷社区	20	3.99	324	64.67	136	27.15	21	4.19
	莲花社区	21	1.55	654	48.41	526	38.93	150	11.10
平均值		2.73		49.22		40.48		7.56
建邺区人口普查数据	67858	15.89	131400	30.77	177827	41.64	50004	11.71

指标	青少年	青年	中年	老年
核心活动空间面积均值/hm²	291	363	371	306
弹性活动空间面积均值/hm²	887	1103	1126	934
核心活动空间/弹性活动空间均值/%	32.64	32.83	32.92	32.77

社区	青少年活动空间活力/h		青年活动空间活力/h		中年活动空间活力/h		老年活动空间活力/h
社区	核心	弹性	核心	弹性	核心	弹性	核心	弹性
爱达社区	233	265	190	1044	184	1059	156	337
黄山路社区	0	0	183	372	95	612	0	152
话园社区	17	199	159	977	359	1035	70	632
吉庆社区	19	97	417	977	563	1358	150	957
科技园社区	189	387	986	1838	650	1732	325	421
莲花社区	142	69	435	956	398	1316	258	425
鹭鸣苑社区	66	485	374	1348	227	1559	154	831
庐山社区	121	373	465	1529	411	1922	306	894
清荷社区	5	67	137	423	118	452	49	48
双和园社区	6	77	305	784	180	632	2	242
泰山路社区	124	149	390	1480	285	1002	494	1033
兴达社区	26	195	198	808	285	841	367	420
怡康社区	36	76	440	396	455	757	148	134
中奥社区	156	328	441	1773	389	1192	248	940
中城社区	37	498	395	1142	276	1177	28	279
中胜社区	9	78	288	510	324	445	318	290
中央商务社区	383	406	554	1569	874	1506	301	548

Measurement of community daily activity space and influencing factors of vitality based on residents’ spatiotemporal behavior: Taking Shazhou and Nanyuan streets in Nanjing as examples

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设施	指标	青少年活动空间		青年活动空间		中年活动空间		老年活动空间
设施	指标	核心	弹性	核心	弹性	核心	弹性	核心	弹性
文化设施	R	0.068	0.409	0.182	0.527^*	0.100	0.537^*	0.213	0.181
文化设施	Sig	0.801	0.115	0.483	0.030	0.702	0.026	0.429	0.488
教育设施	R	0.146	0.582^*	0.249	0.345	0.180	0.462	0.428	0.180
教育设施	Sig	0.591	0.018	0.335	0.176	0.488	0.062	0.098	0.490
商业设施	R	0.512^*	0.576^*	0.796^**	0.403	0.611^**	0.401	0.512^*	0.017
商业设施	Sig	0.042	0.019	<0.001	0.109	0.009	0.111	0.043	0.948
医疗设施	R	-0.007	0.324	0.306	0.330	0.097	0.501^*	0.408	0.233
医疗设施	Sig	0.980	0.221	0.233	0.196	0.711	0.041	0.117	0.369
休闲设施	R	0.338	0.350	0.333	0.372	0.495^*	0.514^*	0.410	0.260
休闲设施	Sig	0.201	0.183	0.192	0.141	0.044	0.035	0.115	0.313
体育设施	R	0.618^*	0.682^**	0.849^**	0.513^*	0.532^*	0.511^*	0.436	0.212
体育设施	Sig	0.011	0.004	<0.001	0.035	0.028	0.036	0.091	0.413
养老设施	R	0.205	0.058	0.540^*	0.214	-0.107	0.278	0.534^*	-0.085
养老设施	Sig	0.446	0.832	0.025	0.409	0.684	0.281	0.033	0.747

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