摘要
借助商业POI数据,通过DBSCAN聚类算法,经过处理得到准确度较高的原始数据,并在因子分析算法的基础上,根据武汉市2017年各行政区的地理位置、道路通达性、人口经济情况及相关统计数据,设计了一种密度因子分析算法,并以湖北省武汉市为例,实现了其范围内各地区商业中心的抽取。结果表明该方法是一种有效的商业要素提取方法,可为城市结构改善提供科学有力的参考依据。
In this paper,with the aid of commercial POI data,through the DBSCAN clustering algorithm,we got higher accuracy of original data after processing.And then,based on the factor analysis method,according to the geographical location,the road accessibility,the economic situation and the related statistical data of each administrative region of Wuhan City in 2017,we designed a density factor analysis algorithm,and taking Wuhan City for example,implemented the extraction of regional business center.The experimental result shows that this method is an effective business elements extraction method,and can provide scientific and powerful reference basis for the improvement of urban structure.
出处
《地理空间信息》
2021年第8期58-60,64,I0006,共5页
Geospatial Information
基金
国家自然科学基金资助项目(41272136)。
