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基于GWR的南昌市中心城区商业地价驱动因素分析
引用本文:赖夏华,郭熙,赵小敏,易丹,韩逸.基于GWR的南昌市中心城区商业地价驱动因素分析[J].中国土地科学,2019,33(11):28-38.
作者姓名:赖夏华  郭熙  赵小敏  易丹  韩逸
作者单位:江西省鄱阳湖流域农业资源与生态重点实验室/江西农业大学,江西省鄱阳湖流域农业资源与生态重点实验室/江西农业大学,江西省鄱阳湖流域农业资源与生态重点实验室/江西农业大学,江西省鄱阳湖流域农业资源与生态重点实验室/江西农业大学,江西省鄱阳湖流域农业资源与生态重点实验室/江西农业大学
基金项目:江西省赣鄱英才“555”领军人才项目(201295);中国人民大学“林增杰土地科学发展基金”。
摘    要:研究目的:以南昌市中心城区为例,利用2019年2月份实时监测的商业地价数据,在分析南昌市中心城区商业地价的数量特征、空间特征以及分布规律的基础上,探索驱动商业地价变化的重要因素。研究方法:半变异函数分析和地理加权回归(GWR)。研究结果:(1)南昌市商业地价均价约10 000元/m~2,属于典型的单中心圈层结构,地价具有空间连续性与非平稳性的特点;(2)南昌市商业地价具有空间相关性且空间相关范围大,主要受结构性因素的影响;(3)人口密度和公交车站数量显著影响商业地价,公交车站数量对商业地价的增值作用最为明显;(4)通过手机信令反映的实时人流量是驱动商业地价变化的重要因素。研究结论:商业地价对城市资源配置与发展规划具有指示作用,应根据商业地价的空间特征和驱动因素并借助大数据分析,制定差别化的城市管理策略。

关 键 词:商业地价  驱动因素    GWR模型  南昌市中心城区
收稿时间:2019/7/7 0:00:00
修稿时间:2019/10/28 0:00:00

Driving Factors of Commercial Land Price Based on GWR in Downtown of Nanchang City
Abstract:The purpose of the paper is to analyze the quantitative characteristics, spatial characteristics and distribution law of commercial land price in the downtown of Nanchang City by using the real-time monitoring of land price data in February 2019, and then to analyze the driving factors. The research methods include semi-variogram analysis and Geographic Weighted Regression (GWR). The research results show that the average commercial land price in Nanchang City is about 10 000 yuan/m2, which is a typical single-center circle structure and the land price has the characteristics of spatial continuity and non-stationarity. The spatial correlation of commercial land price in Nanchang City and its spatial correlation range are large, mainly affected by the structural factors. Commercial land price is significantly affected by the population density and the number of bus stations, and the number of bus stations contributed to the land price increase most considerably. Real-time traffic reflected by mobile phone signal is an important driving factor of commercial land price. In conclusion, commercial land price plays an indication role for urban resource allocation and development planning. Different urban management strategies should be formulated according to the spatial characteristics and driving factors of commercial land price with the help of big data.
Keywords:commercial land price  driving factors  GWR model  downtown of Nanchang City
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