乌鲁木齐市职住空间组织特征及影响因素

doi:10.18306/dlkxjz.2016.04.007

摘要/Abstract

摘要：

本文借助职住分离指数分析法从宏观层面分析了乌鲁木齐市辖区的职住空间匹配状况,利用问卷调查数据,从微观角度分析了不同类型居住区居民的通勤距离和通勤时间。研究发现：职住空间分离是乌鲁木齐城市空间结构的突出特征;全市职住空间不匹配程度较大,居住主导区的街道有35个,占街道总数的44.3%;就业主导区的街道有25个,占街道总数的31.65%;基本匹配区的街道仅有7个。居住区类型、居民受教育程度、职业类型、收入水平、住房形式等社会经济属性对其职住分离程度均有一定程度的影响;采用GWR模型定量分析了职住空间关系的影响因素,认为学历构成、住房产权性质、职业类型、流动人口以及住房面积是影响乌鲁木齐市职住空间关系的主要因素。

关键词: 职住空间, 空间匹配关系, GWR模型, 乌鲁木齐市

Abstract:

Residential space and employment space as two important components of urban structure can exert great impacts on overall urban structure and people’s livelihood. Internationally, research has mainly focused on the spatial organizational relationships between job and housing spaces, their spatial match, influence of mismatch between job and housing spaces on urban traffic, and other spatial mismatch issues. Similar studies began to be conducted in China since the late 1980s. The related literature mainly focused on introducing the theories and research progresses, impact of spatial matching between employment and housing spaces on traffic, spatial organization of job-housing, development patterns of urban land, and so on. The studies were mainly concentrated in the few largest cities but rarely involved the absolute majority of medium-sized cities in the central and western parts of China that are experiencing rapid growth. Urumqi City developed very quickly with industrialization and urbanization since the reform and opening up of China since the late 1970s. Meantime, the residential and employment spaces also started restructuring. This article presents a case study of the Urumqi area to explore the relationship between employment and residential locations. Based on various statistics and using the job-housing spatial bias index, kernel density estimation, and the geographically weighted regression (GWR) model, the authors examined the jobs-housing spatial matching issue and influencing factors of job-housing space relations. The study found that job-housing spatial separation is a prominent feature of urban spatial structure in Urumqi. The degree of job-housing spatial mismatching is relatively large—35 neighborhoods are mainly residential areas, which account for 44.3% of the total number of neighborhoods; 25 neighborhoods are mainly employment-oriented zones, which account for 31.65% of the total number of neighborhoods; and the number of neighborhoods where residential and employment functions largely match is only seven. Education, occupation, ownership of housing property, floating population, size of household living space, and other socioeconomic attributes have certain influence on the degree of separation of the two basic urban functions.

Key words: job and housing spaces, spatial match, GWR model, Urumqi City

英成龙, 雷军, 段祖亮, 杨振. 乌鲁木齐市职住空间组织特征及影响因素[J]. 地理科学进展, 2016, 35(4): 462-475.

Chenglong YING, Jun LEI, Zuliang DUAN, Zhen YANG. Characteristics of jobs-housing spatial organization in Urumqi City and influencing factors[J]. PROGRESS IN GEOGRAPHY, 2016, 35(4): 462-475.

图/表 12

图1

图2

图3

表1

表2

图4

表3

表4

表5

表6

乌鲁木齐市职住空间关系影响因素主因子矩阵"

变量类型	变量名称	主因子载荷
变量类型	变量名称	1	2	3	4	5
户籍因素	非农户比例	-0.337	0.452	0.321	-0.064	0.266
户籍因素	集体户比例	0.228	0.756	-0.146	0.307	0.040
民族因素	汉族人口比例	0.403	-0.557	-0.485	0.294	-0.049
	维吾尔族人口比例	-0.232	0.806	0.274	0.286	0.091
	哈萨克族人口比例	0.543	0.092	0.672	0.227	-0.295
	回族人口比例	0.010	0.097	-0.779	-0.068	0.328
年龄因素	劳动力人口比例	-0.284	-0.164	-0.465	-0.098	-0.064
年龄因素	老年人口比例	-0.718	-0.172	0.129	-0.209	0.111
流动性因素	流动人口比例	0.020	-0.409	-0.074	0.815	0.072
	疆内流动人口比例	0.012	-0.847	0.118	0.265	-0.046
	疆外流动人口比例	-0.232	-0.272	-0.470	0.659	0.075
受教育程度因素	小学及其以下人口比例	-0.490	0.360	0.017	0.576	0.263
	初中人口比例	0.776	-0.100	-0.021	0.479	0.019
	高中人口比例	0.856	-0.164	-0.096	-0.143	-0.196
	大学及其以上人口比例	0.843	-0.375	0.112	-0.173	-0.121
就业因素	第一产业就业人口比例	0.036	0.141	0.140	0.437	-0.150
	工人比例	-0.099	-0.160	0.711	-0.042	-0.353
	公务员/企事业单位就业人口比例	0.033	0.115	0.459	0.159	-0.169
	服务人员比例	0.302	-0.312	0.451	0.384	0.135
住房因素	租赁房比例	-0.267	0.153	0.196	0.336	-0.537
	自建房比例	0.049	-0.619	0.448	-0.133	0.204
	购买商品房比例	-0.009	0.754	-0.199	0.140	-0.015
	经济适用房比例	-0.331	-0.885	0.008	-0.096	-0.119
	人均住房面积对数	0.488	0.082	0.189	-0.154	0.594
	2000年后新建房面积对数	0.495	-0.044	0.255	-0.014	0.556
其他因素	性别比	0.806	-0.153	.0710	-0.101	0.337
	已婚人口比例	0.303	0.276	-0.111	-0.330	-0.507
	劳动人口比例	0.495	-0.173	0.134	-0.013	0.570
特征值 $(λ i)$		6.94	4.95	2.53	2.33	1.80
解释方差贡献率/%		34.79	20.68	10.02	9.31	8.43
方差累计百分比/%		34.79	55.47	65.49	74.8	83.23

表6

图5

图6

参考文献 38

[1]	柴彦威, 张艳, 刘志林. 2011. 职住分离的空间差异性及其影响因素研究[J]. 地理学报, 66(2): 157-166.
	[Chai Y W, Zhang Y, Liu Z L.2011. Spatial differences of home-work separation and the impacts of housing policy and urban sprawl: Evidence from household survey data in Beijing[J]. Acta Geographica Sinica, 66(2): 157-166.]
[2]	冯健, 周一星. 2004. 郊区化进程中北京城市内部迁居及相关空间行为: 基于千份问卷调查的分析[J]. 地理研究, 23(2): 227-242.
	[Feng J, Zhou Y X.2004. Intra-urban migration and correlative spatial behavior in Beijing in the process of suburbanization: Based on 1000 questionnaires[J]. Geographical Research, 23(2): 227-242.]
[3]	顾翠红, 魏清泉. 2008. 上海市职住分离情况定量分析[J]. 规划师, 24(6): 57-62. doi: 10.3969/j.issn.1006-0022.2008.06.014
	[Gu C H, Wei Q Q.2008. Quantitative analysis of Shanghai working and residential separation[J]. Planners, 24(6): 57-62.] doi: 10.3969/j.issn.1006-0022.2008.06.014
[4]	胡娟, 胡忆东, 朱丽霞. 2013. 基于“职住平衡”理念的武汉市空间发展探索[J]. 城市规划, 37(8): 25-32.
	[Hu J, Hu Y D, Zhu L X.2013. Exploration on spatial development of Wuhan based on job-housing balance[J]. City Planning Review, 37(8): 25-32.]
[5]	焦华富, 胡静. 2011. 芜湖市就业与居住空间匹配研究[J]. 地理科学, 31(7): 788-793.
	[Jiao H F, Hu J.2011. Spatial match between employment and housing in Wuhu City, Anhui Province of China[J]. Scientia Geographica Sinica, 31(7): 788-793.]
[6]	刘定惠, 杨永春, 朱超洪. 2012. 兰州市职住空间组织特征[J]. 干旱区地理, 35(2): 288-294.
	[Liu D H, Yang Y C, Zhu C H.2012. Characteristics of jobs-housing spatial organization in Lanzhou City[J]. Arid Land Geography, 35(2): 288-294.]
[7]	刘望保, 闫小培, 谢丽娟. 2012. 转型时期广州居民职住流动及其空间结构变化: 基于3个年份的调查分析[J]. 地理研究, 31(9): 1685-1696. doi: 10.11821/yj2012090014
	[Liu W B, Yan X P, Xie L J.2012. Employment and residential mobility and its spatial structure change based on the 3 years' survey analysis[J]. Geographic Research, 31(9): 1685-1696.] doi: 10.11821/yj2012090014
[8]	刘争光, 张志斌, 汪晓霞, 等. 2014. 兰州市居住空间分布及其成因[J]. 干旱区资源与环境, 28(1): 72-78.
	[Liu Z G, Zhang Z B, Wang X X, et al.2014. The distribution of urban living space in Lanzhou and their causes analysis[J]. Journal of Arid Land Resources and Environment, 28(1): 72-78.]
[9]	刘志林, 王茂军. 2011. 北京市职住空间错位对居民通勤行为的影响分析: 基于就业可达性与通勤时间的讨论[J]. 地理学报, 66(4): 457-467.
	[Liu Z L, Wang M J.2011. Job accessibility and its impacts on commuting time of urban residents in Beijing: From a spatial mismatch perspective[J]. Acta Geographica Sinica, 66(4): 457-467.]
[10]	刘志林, 王茂军, 柴彦威. 2010. 空间错位理论研究进展与方法论评述[J]. 人文地理, 25(1): 1-6.
	[Liu Z L, Wang M J, Chai Y W.2010. Spatial mismatch theory: A review on empirical research and methodology[J]. Human Geography, 25(1): 1-6.]
[11]	刘志林, 张艳, 柴彦威. 2009. 中国大城市职住分离现象及其特征: 以北京市为例[J]. 城市发展研究, 16(9): 110-117.
	[Liu Z L, Zhang Y, Chai Y W.2009. Home-work separation in the context of institutional and spatial transformation in urban China: Evidence from Beijing household survey data[J]. Urban Studies, 16(9): 110-117.]
[12]	孟晓晨, 吴静, 沈凡卜. 2009. 职住平衡的研究回顾及观点综述[J]. 城市发展研究, 16(6): 23-28, 35. doi: 10.3969/j.issn.1006-3862.2009.06.005
	[Meng X C, Wu J, Shen F B.2009. The study review of urban jobs-housing balance[J]. Urban Studies, 16(6): 23-28, 35.] doi: 10.3969/j.issn.1006-3862.2009.06.005
[13]	庞瑞秋, 腾飞, 魏冶. 2014. 基于地理加权回归的吉林省人口城镇化动力机制分析[J]. 地理科学, 34(10): 1210-1217.
	[Pang R Q, Teng F, Wei Y.2014. A GWR-based study on dynamic mechanism of population urbanization in Jilin Province[J]. Scientia Geographica Sinica, 34(10): 1210-1217.]
[14]	强欢欢, 吴晓, 王慧. 2014. 2000年以来南京市主城区居住空间的分异探讨[J]. 城市发展研究, 21(1): 68-78. doi: 10.3969/j.issn.1006-3862.2014.01.011
	[Qiang H H, Wu X, Wang H.2014. Preliminary study on differentiation of urban residential space in Nanjing since 2000[J]. Urban Development Studies, 21(1): 68-78.] doi: 10.3969/j.issn.1006-3862.2014.01.011
[15]	宋金平, 王恩儒, 张文新, 等. 2007. 北京住宅郊区化与就业空间错位[J]. 地理学报, 62(4): 387-396. doi: 10.3321/j.issn:0375-5444.2007.04.005
	[Song J P, Wang E R, Zhang W X, et al.2007. Housing suburbanization and employment spatial mismatch in Beijing[J]. Acta Geographica Sinica, 62(4): 387-396.] doi: 10.3321/j.issn:0375-5444.2007.04.005
[16]	孙斌栋, 潘鑫, 宁越敏. 2008. 上海市就业与居住空间均衡对交通出行的影响分析[J]. 城市规划学刊, (1): 77-82.
	[Sun B D, Pan X, Ning Y M.2008. Analysis on influence of job-housing balance on commute travel in Shanghai[J]. Urban Planning Forum, (1): 77-82.]
[17]	王波, 甄峰. 2011. 南京市区就业空间布局研究[J]. 人文地理, 26(4): 58-65.
	[Wang B, Zhen F.2011. An analysis of spatial distribution of urban employment in Nanjing[J]. Human Geography, 26(4): 58-65.]
[18]	王远飞, 何洪林. 2007. 空间数据分析方法[M]. 北京: 科学出版社
	[Wang Y F, He H L. 2007. Kongjian shuju fenxi fangfa[M]. Beijing, China: Science Press.]
[19]	肖琛, 陈雯, 袁丰, 等. 2014. 2000-2010年无锡市职住空间关系变化及影响因素分析[J]. 地理科学, 34(2): 137-146.
	[Xiao C, Chen W, Yuan F, et al.2014. Relationship between job-housing spaces of Wuxi City and relationship and its influencing factors in 2000-2010[J]. Scientia Geographica Sinica, 34(2): 137-146.]
[20]	修春亮, 孙平军, 王绮. 2013. 沈阳市居住就业结构的地理空间和流空间分析[J]. 地理学报, 68(8): 1110-1118.
	[Xiu C L, Sun P J, Wang Q.2013. Residence: Employment structure analysis on spaces of geography and flows in Shenyang City[J]. Acta Geographica Sinica, 68(8): 1110-1118.]
[21]	徐卞融, 吴晓. 2010. 基于“居住—就业”视角的南京市流动人口职住空间分离量化[J]. 城市规划学刊, (5): 87-97.
	[Xu B R, Wu X.2010. Quantitative analysis of the separation of residential and employment space the floating population in Nanjing[J]. Urban Planning Forum, (5): 87-97.]
[22]	徐涛, 宋金平, 方琳娜, 等. 2009. 北京居住与就业的空间错位研究[J]. 地理科学, 29(2): 174-180.
	[Xu T, Song J P, Fang L N, et al.2009. Spatial mismatch between housing and employment in Beijing[J]. Scientia Geographica Sinica, 29(2): 174-180.]
[23]	翟青, 甄峰, 康国定. 2012. 信息技术对南京市职住分离的影响[J]. 地理科学进展, 31(10): 1282-1288. doi: 10.11820/dlkxjz.2012.10.005
	[Zhai Q, Zhen F, Kang G D.2012. Research on urban home-work separation influenced by information and communication technologies: Taking Nanjing as an example[J]. Progress in Geography, 31(10): 1282-1288.] doi: 10.11820/dlkxjz.2012.10.005
[24]	湛东升, 孟斌. 2013. 基于社会属性的北京市居民居住与就业空间集聚特征[J]. 地理学报, 68(12): 1607-1618. doi: 10.11821/dlxb201312002
	[Zhan D S, Meng B.2013. Spatial clustering analysis of residential and employment distribution in Beijing based on their social characteristics[J]. Acta Geographica Sinica, 68(12): 1607-1618.] doi: 10.11821/dlxb201312002
[25]	张慧. 2013. 长沙市主城区职住分离调查研究[D]. 长沙: 中南大学.
	[Zhang H. 2013. The investigation and study on the separation between jobs and residential locations in Changsha central urban districts[D]. Changsha, China: Central South University.]
[26]	张林静. 2012. 沈阳市居住与就业空间不匹配研究[D]. 长春: 东北师范大学.
	[Zhang L J. 2012. Spatial mismatch of residents and employment in Shenyang[D]. Changchun, China: Northeast Normal University.]
[27]	郑丽敏. 2012. 北京城市居民职住分离影响因素研究[D]. 北京: 首都师范大学.
	[Zheng L M. 2012. The impacts of the separation between jobs and residential locations in Beijing[D]. Beijing, China: Capital Normal University.]
[28]	郑思齐, 龙奋杰, 王轶军, 等. 2007. 就业与居住的空间匹配: 基于城市经济学角度的思考[J]. 城市问题, (6): 56-62.
	[Zheng S Q, Long F J, Wang Y J, et al.2007. On the spatial match between employment and housing: Thoughts from the point of view of urban economics[J]. Urban Problems, (6): 56-62.]
[29]	周素红, 闫小培. 2005. 城市居住: 就业空间特征及组织模式: 以广州市为例[J]. 地理科学, 25(6): 664-670. doi: 10.3969/j.issn.1000-0690.2005.06.003
	[Zhou S H, Yan X P.2005. Characteristics of jobs-housing and organization in Guangzhou[J]. Scientia Geographica Sinica, 25(6): 664-670.] doi: 10.3969/j.issn.1000-0690.2005.06.003
[30]	周素红, 杨利军. 2005. 广州城市居民通勤空间特征研究[J]. 城市交通, 3(1): 62-67. doi: 10.3969/j.issn.1672-5328.2005.01.015
	[Zhou S H, Yang L J.2005. Study on the spatial characteristic of commuting in Guangzhou[J]. Urban Transport of China, 3(1): 62-67.] doi: 10.3969/j.issn.1672-5328.2005.01.015
[31]	Cervero R.1989. Jobs-housing balancing and regional mobility[J]. Journal of the American Planning Association, 55(2): 136-150. doi: 10.1080/01944368908976014
[32]	Giuliano G.1991. Is jobs-housing balance a transportation issue[R]. Washington DC: Transportation Research Record: 305-312.
[33]	Horner M W.2002. Extensions to the concept of excess commuting[J]. Environment and Planning A, 34(3): 543-566. doi: 10.1068/a34126
[34]	Ihlanfeldt K R, Sjoquist D L.1990. Job accessibility and racial differences in youth employment rates[J]. The American Economic Review, 80(1): 267-276. doi: 10.2753/PET1061-1991321270
[35]	Kain J F.1968. Housing segregation, Negro employment and metropolitan decentralization[J]. Quarterly Journal of Economics, 82(2): 175-197.
[36]	Kain J F.1992. The spatial mismatch hypothesis: Three decades later[J]. Housing Policy Debate, 3(2): 371-460. doi: 10.1080/10511482.1992.9521100
[37]	Peng Z R.1997. The jobs-housing balance and urban commuting[J]. Urban Studies, 34(8): 1215-1235.
[38]	Weitz J, Schindler T.1997. Are oregon's communities balanced? A test of the jobs-housing balance policy and the impact of balance on mean commute times[R]. Portland, OR:Portland State University.

聚居区类型	类型I			类型II		类型III
聚居区类型	比例系数/%		街道名称	比例系数/%	街道名称	比例系数/%	街道名称
少数民族聚居区^*	≥60	红雁街道、团结路街道^**、大湾管委会、赛马场管委会、石人子沟街道、古牧地镇、长山子镇		50~60	延安路街道、地窝堡乡	≤50	其他街道
维吾尔族聚居区	≥50	团结路街道^**、地窝堡乡、大湾管委会、赛马场管委会		30~50	胜利路街道、苇湖梁街道、延安路街道	≤30	其他街道
回族聚居区	≥40	铁厂沟镇、古牧地镇、长山子镇		30~40	长胜东街道、三坪农场、卢沟草乡	≤30	其他街道
哈萨克族聚居区	≥20	红雁街道、石人子沟街道		10~20	—	≤10	其他街道

居住类型	类型I			类型II			类型III
居住类型	比例系数/%		街道名称		比例系数/%	街道名称	比例系数/%	街道名称
企事业单位就业人口比重	≥20	迎宾路街道、中亚南路街道^*、青年路街道、胜利路街道、解放南路街道、解放北路街道		15~20	友好南路街道、友好北路街道、南纬路街道、杭州路街道、八一街道、北站西路街道		≤15	其他街道
机关单位就业人口比重	≥20	新民路街道^*、解放北路街道		10~20	和田街街道、南湖南路街道、解放南路街道、喀什东路街道、嵩山街街道		≤10	其他街道

居住类型	社区名称	社区JHB 指数	街道名称
老城区旧居住区	团结路社区	0.76	团结路街道
企事业单位型居住区	中亚南路社区	1.22	中亚南路街道
机关单位型居住区	新民西街社区	0.97	新民路街道
新建商品房型居住区	中枢路社区	7.90	火车西站街道
经济适用房型居住区	小水渠社区	0.03	米东南路街道
廉租房型居住区	泰秀社区	0.06	红庙子街道
公共租赁型居住区	八道湾村	0.45	七道湾街道

居住类型	样本数 /份	职住距离/km			通勤时间/min
居住类型	样本数 /份	均值		标准差	均值	标准差
老城区旧居住区	45	3.11	4.15		21.33	15.62
企事业单位型居住区	46	2.59	4.63		20.11	16.62
机关单位型居住区	47	1.91	3.86		17.36	20.63
新建商品房型居住区	46	3.82	5.16		23.91	22.62
经济适用房型居住区	47	3.98	6.17		25.53	17.53
廉租房型居住区	47	4.45	5.76		27.02	21.37
公共租赁型居住区	46	4.37	4.86		26.30	19.96

属性		样本数/份	职住距离/km			通勤时间/min
属性		样本数/份	均值		标准差	均值	标准差
性别	男	141	3.60	4.12		23.48	17.62
性别	女	183	3.35	4.63		22.79	15.16
民族	汉族	241	3.56	3.12		23.70	15.36
	维吾尔族	61	3.18	4.16		21.44		16.28
	哈萨克族	7	3.71	3.82		24.71		15.32
	回族	15	3.27	4.32		22.67		14.73
年龄	<30岁	76	3.11	5.16		22.11	13.65
	30~39岁	88	3.93	3.26		24.43		15.62
	40~49岁	91	4.16	4.86		26.04		14.87
	50~59岁	43	3.64	5.62	24.29		18.65
	60岁及其以上	26	3.45	4.89	23.27		19.16
受教育程度	小学及以下	50	3.22	6.13	22.70	18.59
	初中/中专	91	3.20	5.63	22.64		16.95
	高中	50	2.47	4.35	24.30		17.26
	大专	49	2.72	3.89	20.20		18.32
	本科及其以上	84	4.11	4.26	23.97		15.68
职业	农民	6	4.50	3.21	26.67	16.89
	工人	37	4.07	5.26	24.49		15.97
	公务员/企事业管理人员	94	2.79	4.16	19.84		15.82
	服务/销售/商贸人员	83	4.13	4.19	25.90		16.87
	离退休人员	16	3.59	5.12	23.26		20.19
	其他	84	3.11	3.16	22.56		17.54
收入水平	2000元以下	105	2.16	4.32	18.78	17.64
	2001~4000元	132	2.56	4.63	19.16		18.65
	4001~6000元	65	3.15	5.12	22.63		19.52
	6001元以上	22	4.66	5.64	27.73		18.45
家庭构成	单身—两口	85	3.35	4.65	23.29	15.93
	三口—四口	208	3.40	5.89	22.70		14.83
	五口及以上	31	4.16	3.92	25.16		16.57
住房形式	购买	234	3.51	5.36	23.23	18.36
	租住	77	2.99	4.86	21.43		17.63
	自建	13	5.38	6.15	30.38		18.62