| 基于多源大数据的深圳市生活性服务业空间格局及影响因素研究 |
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| 引用本文： | 王娜,吴健生,彭子凤.基于多源大数据的深圳市生活性服务业空间格局及影响因素研究[J].热带地理,2021,41(5):956-967. |
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| 作者姓名： | 王娜 吴健生 彭子凤 |
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| 作者单位： | 1.北京大学 深圳研究生院 城市规划与设计学院 城市人居环境科学与技术重点实验室，广东 深圳 518055;2.深圳市规划国土房产;信息中心，广东 深圳 518040;3.北京大学 城市与环境学院 地表过程与模拟教育部重点实验室，北京 100871 |
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| 基金项目： | 国家重点研发计划项目(2019YFB2102000) |
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| 摘 要： | 基于生活性服务业POI、手机信令和管理人口数据等大数据，采用最邻近指数、核密度、熵指数及地理探测器方法，探究深圳市生活性服务业的空间格局及影响因素。结果表明：1）深圳市生活性服务业空间分布不均衡，主要集中在中、西部地区，总体呈现“两核-三带”的空间集聚特征；空间上呈带状发展形态，主要集聚在交通主干道及轨道线周边区域。2）大多数服务业类别的空间特征与总体生活性服务业的空间分布特征基本一致，少数区域因产业发展导致空间分布集聚的差异化。3）生活性服务业混合度在罗湖区、福田区、南山区类别相对均衡，在宝安区、龙华区等其他区类别相对单一，混合度高的区域大多集中在“两核”外的边缘区域，而不是POI密度最高的“两核”核心处。4）人口因素是影响生活性服务业空间格局的最主要因素，其次为交通因素，经济因素和空间因素的影响程度较低。5）各探测因子对各类生活性服务业空间分布的影响程度存在差异，不同年龄段因需求不同影响到各类别生活性服务业的空间分布。
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| 关 键 词： | 生活性服务业 空间集聚 影响机制 深圳市 多源大数据 |
| 收稿时间： | 2021-01-13 |
Spatial Pattern and Influencing Factors of the Consumer Service Industry in Shenzhen Based on Multisource Big Data |
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| Na Wang,Jiansheng Wu,Zifeng Peng.Spatial Pattern and Influencing Factors of the Consumer Service Industry in Shenzhen Based on Multisource Big Data[J].Tropical Geography,2021,41(5):956-967. |
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| Authors: | Na Wang Jiansheng Wu Zifeng Peng |
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| Institution: | 1.Key Laboratory for Urban Habitat Environmental Science and Technology, School of Urban Planning and Design, Peking University Shenzhen Graduate School, Shenzhen 518055, China;2.Information Center of Planning & Land & Real-Estate of Shenzhen, Shenzhen 518040, China;3.Key Laboratory for Earth Surface Processes, Ministry of Education, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China |
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| Abstract: | The consumer service industry directly provides residents with material and spiritual living consumption services and products to meet residents' consumption needs. The reasonable spatial layout of the consumer service industry is of great significance for improving residents' quality of living, optimizing the urban spatial structure, and alleviating urban problems. Based on consumer service point of interest (POI) data, mobile phone signaling data, and population data from Shenzhen, using the nearest neighbor index, kernel density, and entropy index methods, this study analyzes the spatial pattern of the overall and different types of consumer service industry as well as the spatial characteristics of the degree of mixing in the consumer service industry in Shenzhen. Using the Geodetector method, this study also detects the impacts of seven factors, including population, traffic, economy, and space dimensions, on the overall and different types of consumption service industry as well as analyzing the impacts of population age structure on the spatial pattern of this industry and its types. This study is expected to provide a theoretical and decision-making basis for urban planning and development in Shenzhen and other cities. The results show that: 1) The spatial distribution of the consumer service industry in Shenzhen is unbalanced and is concentrated in the central and western regions. The consumer service industry presents the spatial characteristics of two core areas and three belt areas. The two core areas are the Dongmen business area in Luohu District and the Huaqiangbei business area in Futian District. The three belt areas consist of the Luohu-Futian belt, Nanshan-Baoan belt, and Longhua belt. The spatial distribution of the consumer service industry has developed along strips and is mainly concentrated in the areas around the main roads and rail lines. 2) The spatial agglomeration characteristics of the overall and different types of consumer service industry are remarkable and differentiated in Shenzhen. The spatial distribution characteristics of most types of consumer services are similar to those of the overall consumer service industry. The development of industry in some areas has resulted in differences in the spatial distribution of certain categories. 3) The balance of the consumer service industry is better in the Luohu, Futian, Nanshan District and worse in the other Districts. The high balanced areas are the edge areas outside the two core areas, rather than the two core areas with the highest POI density. 4) Population density factors are the most important factors affecting the spatial pattern of the consumer service industry, followed by traffic factors. The influence of economic and spatial factors is relatively low. 5) The population of people aged 19-35 has the greatest impact on the density of the consumer service industry. Age groups have different impacts on the spatial distribution of different types of consumer service industries because of specific needs. These results are consistent with the spatial planning of urban functional zoning and industrial development layout in the Shenzhen Urban Master Plan (2010-2020). Combining these results and current urban development activities, this study provides suggestions for optimizing the spatial layout of the consumer service industry in Shenzhen. |
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| Keywords: | consumer service industry spatial agglomeration influence mechanism Shenzhen City multisource big data |
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