基于多源数据的城市交通网络特征研究
Research on urban transportation network characteristics based on multi-source data
艾淑华 1曾政祥1
作者信息
- 1. 江西省国土空间调查规划研究院,江西 南昌 330025
- 折叠
摘要
随着我国都市圈建设的迅速发展,有必要通过研究城市交通的联系特征来判断经济发展状况,预测未来趋势.针对传统交通调查方法严重依赖人为因素,存在成本高、周期长、数据可靠性差等弊端,故基于多源地理大数据,凭借智能高效的交通网络分析方法,构建了以南昌市为中心的对外交通联系强度模型,并将该模型面向国内、省内两个层级进行分析与应用.案例结果表明:基于多源、异构的大数据可构建网络层级结构,结合评定指标,能够有效刻画城市空间异质性及其交通特征,且估计结果可靠,进而支撑行业高效运营和决策部署.
Abstract
With the rapid development of urban agglomeration construction in our country,it is necessary to judge the economic development status and plan future trends by studying the connection characteristics of urban transportation.However,traditional traffic investigation methods heavily rely on human factors and drawbacks such as high costs,long cycles,and poor data reliability are existed.Therefore,based on multi-source geographic big data and intelligent and efficient transportation network analysis methods,an external transportation connection strength model centered on Nanchang City is constructed,and the model to domestic and provincial levels is analyzed and applied in this article.Case studies have shown that a network hierarchical structure can be constructed based on multi-source and heterogeneous big data,combined with evaluation indicators,which can effectively characterize urban spatial heterogeneity and its traffic characteristics,and the estimation results are reliable,thereby supporting efficient operation and decision-making deployment in the industry.
关键词
多源数据/城市交通/联系特征/层级结构/特征提取Key words
multi-source data/urban transportation/contact characteristics/hierarchical structure/Feature Extraction引用本文复制引用
出版年
2024
NETL
NSTL
万方数据