节点文献

城市功能区识别研究进展与趋势

Progress and perspectives of urban functional region identification

  • 推荐 CAJ下载
  • PDF下载
  • 不支持迅雷等下载工具,请取消加速工具后下载。

【作者】 程朋根齐广玉钟燕飞

【Author】 CHENG Penggen;QI Guangyu;ZHONG Yanfei;School of Surveying and Geoinformation Engineering, East China University of Technology;Key Laboratory of Mine Environmental Monitoring and Improving around Poyang Lake, Ministry of Natural Resources;State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University;

【机构】 东华理工大学测绘与空间信息工程学院自然资源部环鄱阳湖区域矿山环境监测与治理重点实验室武汉大学测绘遥感信息工程国家重点实验室

【摘要】 随着经济社会的快速发展,城市开发边界迅速由中心向外蔓延,识别城市功能区可为城市建设与规划提供参考依据,且对城市空间和资源合理配置利用具有重要意义。本文在梳理有关城市功能区划分与识别的国内外文献基础上,对城市功能区识别的研究现状进行综述。首先,介绍了用于城市功能区识别的多种数据源,并分析比较其优缺点;然后,总结了城市功能区识别的4类方法,重点分析了深度学习方法在城市功能区识别中的应用,并展开实例分析对比,说明不同数据源和方法对城市功能区识别的有效性;最后,指出了城市功能区划分识别研究领域存在的问题和研究趋势。

【Abstract】 With the rapid development of the economy and society, the urban development boundary has rapidly spread from the center to the outside. Identifying urban functional areas can provide reference basis for urban construction and planning, and it is of great significance for the rational allocation and utilization of urban space and resources. Based on the literature review of urban functional area division and identification at home and abroad, this article summarizes the research status of urban functional area identification. Firstly, various data sources used for urban functional area identification are introduced, and their advantages and disadvantages are analyzed and compared. Secondly, it summarizes four types of method for urban functional area identification, focuses on analyzing the application of deep learning methods in urban functional area identification, and conducts case analysis and comparison to illustrate the effectiveness of different data sources and methods for urban functional area identification. Finally, the problems and research trends in the field of urban functional area division and identification are pointed out.

【基金】 国家自然科学基金(41861052);江西省自然科学基金面上项目(20202BABL202045);地理信息工程国家实验室、自然资源部测绘科学与地球空间信息技术重点实验室联合资助基金(2022-02-04)
  • 【文献出处】 测绘通报 ,Bulletin of Surveying and Mapping , 编辑部邮箱 ,2024年05期
  • 【分类号】TU984;P208
  • 【下载频次】146
节点文献中: