道路网与兴趣点相结合的城市中心提取方法

为空间数据添加接近人们思维以及适宜认知的高阶信息是改善其可用性的重要途径。城市中心是这一类信息的典型案例,它在人们的社会活动中具有重要作用。本文提出一种单纯运用道路网和兴趣点提取城市中心的方法。该方法首先运用G*i提取了路网的密集区域,确定了包含城市中心的大致区域;然后根据该区域中特定类型兴趣点的网络核密度确定了城市中心的精确范围。对英国利物浦、加拿大多伦多和巴西库里蒂巴进行了试验,查准率为0.74~0.8,查全率为0.53~0.67,结果表明该方法能较为有效地提取城市中心。对方法的两个关键影响因素:G*i的距离测度以及网络核密度的带宽进行了敏感性分析,固定距离法为合适的距离测度方法,而600~900m为适宜带宽。

A Method for Automatic Delineation of City Centers Using POI and Road Networks

Providing higher order information which is close to human thinking and appropriate for cognition is an important way to improve the usability of spatial data.As a typical case of such information,city center plays an important role in social activities of humanity.This paper proposes a method to extract city centers,which simply using road networks and points of interest.The method firstly extracts the dense region of the road network by conductingG?i statistics to determine the rough zone that contains the city center,and then precisely delineates the city center using network kernel density estimation based on specific points of interest within the rough zone.Liverpool,Uk,Toronto,Canada,and Curitiba,Brazil were used as the experiment data.The precision ranges from 0.74 to 0.8,and the recal l ranges from 0.53 to 0.67, which indicates that the method could extract the city center effectively.Sensitive analyses are also carried out on two key factors of the method:the di stance measure of G?i and the bandwi dth of network kernel density estimation.The fixed distance is the best distance measure,and a bandwidth of 600~900 m is the appropri ate range i n network kernel densi ty.