上海中心城就业中心体系测度----基于手机信令数据的研究

doi:10.11821/dlxb201603011

摘要/Abstract

摘要：

利用手机信令数据识别上海市域内手机用户的工作地和居住地,获取就业者的通勤数据,测度上海中心城的就业中心体系.首先用就业者工作地数据生成就业密度分布图,基于中心城的就业密度识别就业中心.随后,用就业者工作地和居住地数据分别从就业密度和通勤联系两方面测度各中心的能级,分析各中心的腹地和势力范围.研究发现:① 上海中心城的就业中心呈主中心强大的弱多中心体系;② 就业密度越高的中心与其他地区的通勤联系一般也越强,但通勤联系在各中心间的差异更显著;③ 能级越高的中心腹地面积越大,但势力范围不一定越大;④ 相比于能级,职住功能混合度对职住平衡的影响更大;⑤缺少就业中心的地区势力范围呈交替状.本研究一定程度上能有助于解决既往就业中心体系研究因空间单元较大,缺少通勤数据在中心识别,通勤联系测度等方面受到的局限,希望能为构建上海中心城就业多中心体系提供帮助.

关键词: 就业中心体系, 手机信令数据, 通勤, 上海中心城

Abstract:

The purpose of this study is to explore the employment center system in the central city of Shanghai by using commuting data obtained from mobile phone signaling data in Shanghai. Based on the signaling data it is possible to identify the phone users' home residence and where their employment is. We compile the employment density map using the employment places data in order to identify the employment centers in Shanghai. Then the employment center system is measured based on two perspectives, namely employment density and commuting connection. We measure the level, the hinterland and influence sphere of each employment center in Shanghai central city. Our main conclusions are as follows: firstly, the employment center system in Shanghai central city is a weak multi-centric system with a strong primary center. Secondly, centers with higher employment densities also contain stronger commuting connections to other areas, and the discrepancies of commuting connections between centers are even more significant. Thirdly, centers with higher levels also have larger hinterlands, but their influence spheres are not necessarily larger. Fourthly, the mixed degree of residential and employment land use is a more significant determinant of the residential and employment land use pattern balance of employment center than the level of the center. Finally, influence spheres are alternately distributed in areas that lack employment centers. To some extent, this paper helps to solve the problems of identifying employment centers and measuring commuting connections. Previous studies have been unable to perfectly identify such centers due to either an overly large spatial unit of measurement or lack of commuting data. This paper will be helpful for constructing multi-center employment system in the central city of Shanghai.

Key words: employment center system, mobile phone signaling data, commuting, central city of Shanghai

丁亮, 钮心毅, 宋小冬. 上海中心城就业中心体系测度----基于手机信令数据的研究[J]. 地理学报, 2016, 71(3): 484-499.

Liang DING, Xinyi NIU, Xiaodong SONG. Measuring the employment center system in Shanghai central city: A study using mobile phone signaling data[J]. Acta Geographica Sinica, 2016, 71(3): 484-499.

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用户编号	代表工作地的基站编号	代表工作地的基站经度	工代表工作地的基站纬度	代表居住地的基站编号	代表居住地的基站经度	代表居住地的基站纬度	通勤距离(m)
1	633962xxx	121.59xxx	31.21xxx	633439xxx	121.63xxx	31.20xxx	3828.798
2	617533xxx	121.12xxx	30.99xxx	617532xxx	121.12xxx	30.99xxx	725.2021
3	615008xxx	121.38xxx	31.16xxx	615012xxx	121.36xxx	31.16xxx	2655.077
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名称	就业密度	名称	就业密	名称	就业密度	名称	就业密度	名称	就业密度
南京东路外滩	2.42	南京西路	2.07	陆家嘴	1.85	淮海路	1.84	老西门豫园	1.80
打浦桥	1.77	虹桥涉外贸易中心	1.64	徐家汇	1.60	张杨路	1.58	长寿	1.57
四川北路	1.49	中山公园	1.43	漕河泾经济技术开发区	1.42	不夜城	1.41	曹杨路	1.31
新曹杨高新技术园区	1.22	虹桥临空经济园区	1.21	虹桥总部	1.18	曹安	1.15

名称	R²	名称	R²	名称	R²	名称	R²	名称	R²
南京西路	0.2627	淮海路	0.2161	南京东路外滩	0.2114	打浦桥	0.1842	陆家嘴	0.1724
徐家汇	0.1274	老西门豫园	0.1150	漕河泾经济技术开发区	0.1092	中山公园	0.1083	长寿	0.1066
虹桥涉外贸易中心	0.1049	不夜城	0.0882	曹杨路	0.0865	张杨路	0.0590	新曹杨高新技术园区	0.0533
虹桥临空经济园区	0.0515	四川北路	0.0231	虹桥总部	0.0130	曹安	0.0129

名称	就业者居住密度	名称	就业者居住密度	名称	就业者居住密度	名称	就业者居住密度	名称	就业者居住密度
南京西路	3509.90	长寿	1351.13	淮海路	341.82	南京东路外滩	243.02	陆家嘴	162.75
中山公园	152.68	徐家汇	145.32	打浦桥	110.26	不夜城	90.25	虹桥涉外贸易中心	89.60
曹杨路	81.83	张杨路	68.88	漕河泾经济技术开发区	57.41	老西门豫园	46.00	四川北路	28.17
新曹杨	9.26	虹桥临空经济园区	8.94	虹桥总部	0.07	曹安	0.02