多源数据支持下的城市功能空间结构分析  

Analysis of Urban Functional Spatial Structure Supported by Multi-source Data

作　　者：章雯 ZHANG Wen(School of Civil and Surveying Engineering,Jiangxi University of Science and Technology,Ganzhou,Jiangxi 341000)

机构地区：[1]江西理工大学土木与测绘工程学院,江西赣州341000

出　　处：《长江信息通信》2022年第5期17-20,共4页Changjiang Information & Communications

摘　　要：城市化建设一直是学者们研究的重要课题之一,其中最重要的是要能够先对城市的现有空间结构做识别分析,所以城市功能区的提取分析十分必要。文章首先对爬取的多源数据进行预处理工作,确定最小研究单元,其次建立数学模型进行城市功能区识别,针对识别结果进行分析,利用经典混淆矩阵对识别结果进行精度验证,得到西安市主城区功能区识别结果的总体精度为78.33%以及Kappa系数为0.74。说明基于POI的以街区为最小研究单元的城市功能区识别方法具有较高的准确性,识别率较好。最后根据分析结果总结西安市主城区在发展过程中存在的相关问题。Urbanization construction has always been one of the important topics studied by scholars. The most important thing is to be able to identify and analyze the existing spatial structure of the city, so the extraction and analysis of urban functional areas is very necessary. This paper firstly preprocesses the crawled multi-source data to determine the minimum research unit;secondly, establishes a mathematical model to identify urban functional areas, analyzes the identification results, and finally uses the classical confusion matrix to verify the accuracy of the identification results, and finally obtains Xi’an The overall accuracy of the identification results of functional areas in the main urban area of the city was 78.33%, and the Kappa coefficient was 0.74. It can be shown that the identification method of urban functional area based on POI with the block as the smallest research unit has higher accuracy and better recognition rate.

关 键 词：多源融合数据 城市功能区识别 空间结构分析 多要素分析 

分 类 号：P208[天文地球—地图制图学与地理信息工程]