PROGRESS IN GEOGRAPHY ›› 2020, Vol. 39 ›› Issue (5): 738-750.doi: 10.18306/dlkxjz.2020.05.004
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CHEN Hongxing1,2, YANG Degang1,*(), LI Jiangyue1,2, WU Rongwei1,2, HUO Jinwei1
Received:
2019-04-26
Revised:
2019-07-26
Online:
2020-05-28
Published:
2020-07-28
Contact:
YANG Degang
E-mail:dgyang@ms.xjb.ac.cn
Supported by:
CHEN Hongxing, YANG Degang, LI Jiangyue, WU Rongwei, HUO Jinwei. Distribution characteristics and influencing factors of commercial center and hotspots based on big data: A case of the main urban area of Urumqi City[J].PROGRESS IN GEOGRAPHY, 2020, 39(5): 738-750.
Tab.1
Classification of commercial points of interest (POIs) and the proportion of each class"
主类 | 亚类 | 占比/% |
---|---|---|
餐饮服务 | 糕饼店、外国餐厅、快餐店、冷饮店、甜品店、餐饮相关场所、饮茶馆、咖啡厅、茶艺馆 | 31.58 |
购物服务 | 便民商店、家居建材市场、特色商业街、服装鞋帽皮具店、专卖店、文化用品店、超市、购物相关场所、家电电子卖场、体育用品店、商场、花鸟鱼虫市场、综合市场、特殊买卖场所 | 38.22 |
住宿服务 | 宾馆、酒店、旅馆、招待所、住宿服务相关场所 | 2.86 |
金融保险服务 | 保险公司、财务公司、银行、ATM、证券公司、金融保险服务机构 | 1.76 |
商务服务 | 商务写字楼、商住两用楼宇 | 1.81 |
生活服务 | 旅行社、美容店、摄影冲印店、事务所、售票处、物流速递点、洗衣店、洗浴推拿、中介机构、药店、诊所、驾校、培训机构 | 23.76 |
Tab.2
Classification results of six types of points of interest (POIs) with head/tail division"
类型 | 街区单元数量 | 单元密度均值 | 头部单元数量 | 头部单元占比/% |
---|---|---|---|---|
商务服务 | 4138 | 0.58 | 190 | 4.59 |
190 | 12.62 | 63 | 33.15 | |
63 | 25.30 | 24 | 38.09 | |
24 | 37.93 | 10 | 41.00 | |
住宿服务 | 4138 | 6.50 | 555 | 13.41 |
555 | 47.60 | 173 | 31.17 | |
173 | 68.54 | 113 | 65.00 | |
餐饮服务 | 4138 | 68.95 | 680 | 16.43 |
680 | 397.94 | 232 | 34.11 | |
232 | 809.86 | 85 | 36.48 | |
85 | 1299.73 | 36 | 42.35 | |
购物服务 | 4138 | 83.05 | 662 | 16.00 |
662 | 489.71 | 205 | 30.96 | |
205 | 1091.94 | 78 | 38.04 | |
金融服务 | 4138 | 4.10 | 541 | 13.07 |
541 | 31.03 | 160 | 29.57 | |
160 | 73.59 | 52 | 32.50 | |
52 | 134.36 | 19 | 36.50 | |
19 | 180.22 | 8 | 42.10 | |
生活服务 | 4138 | 39.96 | 670 | 16.19 |
670 | 232.95 | 223 | 33.28 | |
223 | 471.24 | 102 | 45.74 |
Tab.4
Explanatory power of different types of detectors of commercial network distribution in Urumqi City"
探测因子 | 整体 | 商务服务 | 住宿服务 | 餐饮服务 | 金融服务 | 生活服务 | 购物服务 |
---|---|---|---|---|---|---|---|
高程X1 | 0.03** | 0.03 | 0.05 | 0.06 | 0.01 | 0.04 | 0.02 |
地形起伏度X2 | 0.23* | 0.07* | 0.11 | 0.30 | 0.04 | 0.15 | 0.19 |
人口密度X3 | 0.37** | 0.41 | 0.38 | 0.45* | 0.31 | 0.62*** | 0.66** |
路网密度X4 | 0.39** | 0.17 | 0.31 | 0.29* | 0.08 | 0.44** | 0.29 |
中心可达性X5 | 0.28** | 0.67*** | 0.12 | 0.16 | 0.33*** | 0.07 | 0.22 |
地价X6 | 0.50* | 0.53 | 0.44 | 0.21 | 0.55** | 0.21 | 0.34 |
集聚效应X7 | 0.47*** | 0.36 | 0.09 | 0.16** | 0.25 | 0.14 | 0.44** |
Tab.5
Pearson correlation coefficient matrix of different types of commercial sites"
商业业态 | 餐饮服务 | 住宿服务 | 商务服务 | 购物服务 | 金融服务 | 生活服务 |
---|---|---|---|---|---|---|
餐饮服务 | 1.000 | 0.608*** | 0.474*** | 0.822*** | 0.565*** | 0.842*** |
住宿服务 | 1.000 | 0.457*** | 0.527*** | 0.430*** | 0.604*** | |
商务服务 | 1.000 | 0.420*** | 0.695*** | 0.513*** | ||
购物服务 | 1.000 | 0.558*** | 0.777*** | |||
金融服务 | 1.000 | 0.606*** | ||||
生活服务 | 1.000 |
[1] | 阎小培, 周春山, 冷勇 , 等. 广州CBD的功能特征与空间结构 [J]. 地理学报, 2000,67(4):475-486. |
[ Yan Xiaopei, Zhou Chunshan, Leng Yong , et al. Functional features and spatial structure of CBDs in Guangzhou. Acta Geographica Sinica, 2000,67(4):475-486. ] | |
[2] | Berry B J L . Commercial structure and commercial blight: Retail patterns and processes in the city of Chicago [R]. University of Chicago, Department of Geography, Research Paper No. 85. Chicago, USA, 1963. |
[3] | Kohsaka H . An optimization of the central place system in terms of multipurpose shopping trip [J]. Geographical Analysis, 2010,16(3):250-269. |
[4] | 吴郁文, 谢彬, 骆慈广 , 等. 广州市城区零售商业企业区位布局的探讨 [J]. 地理科学, 1988,8(3):208-217. |
[ Wu Yuwen, Xie Bin, Luo Ciguang , et al. An approach to retailcommerce location of Guangzhou urban area. Scientia Geographica Sinica, 1988,8(3):208-217. ] | |
[5] | 杨吾扬 . 北京市零售商业与服务业中心和网点的过去、现在和未来 [J]. 地理学报, 1994,49(1):9-17. |
[ Yang Wuyang . The retailing and services center and network ofBeijing: Then, now and long before. Acta Geographica Sinica, 1994,49(1):9-17. ] | |
[6] | 王士君, 浩飞龙, 姜丽丽 . 长春市大型商业网点的区位特征及其影响因素 [J]. 地理学报, 2015,70(6):893-905. |
[ Wang Shijun , HaoFeilong, Jiang Lili. Locations and theirdeterminants of large-scale commercial sites in Changchun, China. Acta Geographica Sinica, 2015,70(6):893-905. ] | |
[7] | 宁越敏 . 上海市区商业中心区位的探讨 [J]. 地理学报, 1984,39(2):163-172. |
[ NingYuemin. An approach to shopping center location of Shanghai's urban area. Acta Geographica Sinica, 1984,39(2):163-172. ] | |
[8] | 周素红, 郝新华, 柳林 . 多中心化下的城市商业中心空间吸引衰减率验证: 深圳市浮动车 GPS 时空数据挖掘 [J]. 地理学报, 2014,69(12):1810-1820. |
[ Zhou Suhong, Hao Xinhua, Liu Lin . Validation of spatial decay law caused by urban commercial center's mutual attraction in polycentriccity: Spatio-temporal data mining of floating cars' GPS data in Shenzhen. Acta Geographica Sinica, 2014,69(12):1810-1820. ] | |
[9] | 吴康敏, 张虹鸥, 王洋 , 等. 广州市多类型商业中心识别与空间模式 [J]. 地理科学进展, 2016,35(8):963-974. |
[ Wu Kangmin, Zhang Hongou, Wang Yang , et al. Identify of the multiple types of commercial center in Guangzhou and its spatial pattern. Progress in Geography, 2016,35(8):963-974. ] | |
[10] | Goodchild M F . Citizens as sensors: The world of volunteered geography [J]. GeoJournal, 2007,69(4):211-221. |
[11] | 杨振山, 龙瀛 , Douay N. 大数据对人文-经济地理学研究的促进与局限 [J]. 地理科学进展, 2015,34(4):410-417. |
[ Yang Zhenshan, Long Ying, Douay N . Opportunities and limitations of big data applications to human and economic geography: The state of the art. Progress in Geography, 2015,34(4):410-417. ] | |
[12] | Liu Y, Liu X, Gao S , et al. Social sensing: A new approach to understanding our socioeconomic environments [J]. Annals of the Association of American Geographers, 2015,105(3):512-530. |
[13] | Lloyd A, Cheshire J . Deriving retail centre locations and catchments from geo-tagged Twitter data [J]. Computers Environment & Urban Systems, 2017,61:108-118. |
[14] | 王晓梦, 王锦, 朱青 . 基于签到数据的城市商业空间空心化识别研究: 以北京市城六区为例 [J]. 城市发展研究, 2018,25(2):77-84. |
[ Wang Xiaomeng, Wang Jin, Zhu Qing . Identification of following phenomenon in commercial space of six district of Beijing based on checking-in data. Urban Development Studies, 2018,25(2):77-84. ] | |
[15] | Ting C Y, Ho C C, Yee H J , et al. Geospatial analytics in retail site selection and sales prediction [J]. Big Data, 2018,6(1):42-52. |
[16] | 王芳, 牛方曲, 王志强 . 微观尺度下基于商圈的北京市商业空间结构优化 [J]. 地理研究, 2017,36(9):1697-1708. |
[ Wang Fang, Niu Fangqu, Wang Zhiqiang . Commercial spatial structure optimization based on trade areaanalysis from a micro-scale perspective in Beijing. Geographical Research, 2017,36(9):1697-1708. ] | |
[17] | 浩飞龙, 王士君, 冯章献 , 等. 基于POI数据的长春市商业空间格局及行业分布 [J]. 地理研究, 2018,37(2):366-378. |
[ Hao Feilong, Wang Shijun, Feng Zhangxian , et al. Spatial pattern and its industrial distribution of commercialspace in Changchun based on POI data. Geographical Research, 2018,37(2):366-378. ] | |
[18] | 陈蔚珊, 柳林, 梁育填 . 基于POI数据的广州零售商业中心热点识别与业态集聚特征分析 [J]. 地理研究, 2016,35(4):703-716. |
[ Chen Weishan, Liu Lin, Liang Yutian . Retail centerrecognition and spatial aggregating feature analysis of retail formats in Guangzhou based on POI data. Geographical Research, 2016,35(4):703-716. ] | |
[19] | 薛冰, 肖骁, 李京忠 , 等. 基于POI大数据的城市零售业空间热点分析: 以辽宁省沈阳市为例 [J]. 经济地理, 2018,38(5):36-43. |
[ Xue Bing, Xiao Xiao, Li Jingzhong , et al. POI-based analysis on retail's spatial hot blocks at a city level: A case study of Shenyang, China. Economic Geography, 2018,38(5):36-43. ] | |
[20] | 陆娟, 汤国安, 张宏 , 等. 犯罪热点时空分布研究方法综述 [J]. 地理科学进展, 2012,31(4):419-425. |
[ Lu Juan, Tang Guo'an, Zhang Hong, et al. A review of research methods for spatiotemporal distribution of the crime hot spots. Progressin Geography, 2012,31(4):419-425. ] | |
[21] | 薛东前, 黄晶, 马蓓蓓 , 等. 西安市文化娱乐业的空间格局及热点区模式研究 [J]. 地理学报, 2014,69(4):541-552. |
[ Xue Dongqian, Huang Jing, Ma Beibei , et al. Spatial distribution characteristics and hot zone patterns of entertainmentindustry in Xi'an. Acta Geographica Sinica, 2014,69(4):541-552. ] | |
[22] | Chen X, Xu F C, Wang W L , et al. Geographic big data's applications in retailing business market [M] // Shen Z J, Li M Y, Big data support of urban planning and management. Berlin, Germany: Springer, 2018: 157-176. |
[23] | Lin G, Chen X X, Liang Y T . The location of retail stores and street centrality in Guangzhou, China [J]. Applied Geography, 2018,100:12-20. |
[24] | 傅辰昊, 周素红, 闫小培 , 等. 广州市零售商业中心的居民消费时空行为及其机制 [J]. 地理学报, 2017,72(4):603-617. |
[ Fu Chenhao, Zhou Suhong, Yan Xiaopei , et al. Spatio-temporalcharacteristics and influencing factors of consumer behavior inretailing centers: A case study of Guangzhou in GuangdongProvince. Acta Geographica Sinica, 2017,72(4):603-617. ] | |
[25] | 赵宏波, 余涤非, 苗长虹 , 等. 基于POI数据的郑州市文化设施的区位布局特征与影响因素研究 [J]. 地理科学, 2018,38(9):1525-1534. |
[ Zhao Hongbo, Yu Difei, Miao Changhong , et al. The location distribution characteristics and influencing factors of cultural facilities in Zhengzhou based on POI data. Scientia Geographica Sinica, 2018,38(9):1525-1534. ] | |
[26] | Long Y, Liu X . Automated identification and characterization of parcels (AICP) with open street map and points of interest [J]. Environment & Planning B, 2015,43(2):498-510. |
[27] | 李德华 . 城市规划原理 [M]. 第3版. 北京: 中国建筑工业出版社, 2001. |
[ Li Dehua. Principles of urban planning. 3nd ed. Beijing: China Architecture & Building Press. 2001. ] | |
[28] | Hu T Y, Yang J, Li X C , et al. Mapping urban land use by using Landsat images and open social data [J]. Remote Sensing, 2016,8(2):151-169. |
[29] | Jiang B . Head/tail breaks: A new classification scheme for data with a heavy-tailed distribution [J]. Professional Geographer, 2013,65(3):482-494. |
[30] | Jiang B, Yin J . Ht-index for quantifying the fractal or scaling structure of geographic features [J]. Annals of the Association of American Geographers, 2014,104(3):530-540. |
[31] | 焦利民, 李泽慧, 许刚 , 等. 武汉市城市空间集聚要素的分布特征与模式 [J]. 地理学报, 2017,72(8):1432-1443. |
[ Jiao Limin, Li Zehui, Xu Gang , et al. Distribution characteristics and models of urban agglomeration factors in Wuhan. Acta Geographica Sinica, 2017,72(8):1432-1443. ] | |
[32] | 韩会然, 杨成凤, 宋金平 . 北京批发企业空间格局演化与区位选择因素 [J]. 地理学报, 2018,73(2):219-231. |
[ Han Huiran, Yang Chengfeng, Song Jinping . Impact factors of location choice and spatial pattern evolution ofwholesale enterprises in Beijing. Acta Geographica Sinica, 2018,73(2):219-231. ] | |
[33] | 王劲峰, 徐成东 . 地理探测器: 原理与展望 [J]. 地理学报, 2017,72(1):116-134. |
[ Wang Jinfeng , Xu Cheng dong. Geodetector: Principle and prospective. Acta Geographica Sinica, 2017,72(1):116-134. ] | |
[34] | 曹芳洁, 邢汉发, 侯东阳 , 等. 基于POI数据的北京市商业中心识别与空间格局探究 [J]. 地理信息世界, 2019,26(1):66-71. |
[ Cao Fangjie, Xing Hanfa, Hou Dongyang , et al. Research on identification and spatial patterns of commercial centers in Beijing based on POI data. Geomatics World, 2019,26(1):66-71. ] | |
[35] | 刘晓倩 . 成都市城市商业空间发展研究[D]. 成都: 西南交通大学, 2008. |
[ Liu Xiaoqian . Reaserch on the development of urban commercial space in Chengdu. Chengdu, China: Southwest Jiaotong University, 2008. ] | |
[36] | 安成谋 . 兰州市商业中心的区位格局及优势度分析 [J]. 地理研究, 1990,9(1):28-34. |
[ An Chengmou . Analysis of Lanzhou commercial center's location pattern and advantage degree. Geographical Research, 1990,9(1):28-34. ] | |
[37] | 张利, 雷军, 张小雷 , 等. 乌鲁木齐城市社会区分析 [J]. 地理学报, 2012,67(6):817-828. |
[ Zhang Li, Lei Jun, Zhang Xiaolei , et al. Analysis of the urban social areas in Urumqi. Acta Geographica Sinica, 2012,67(6):817-828. ] |
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