城市功能区识别研究进展与趋势

doi:10.13474/j.cnki.11-2246.2024.0516

测绘通报 ›› 2024, Vol. 0 ›› Issue (5): 90-95.doi: 10.13474/j.cnki.11-2246.2024.0516

• 学术研究 • 上一篇

城市功能区识别研究进展与趋势

程朋根^1,2, 齐广玉¹, 钟燕飞³

1. 东华理工大学测绘与空间信息工程学院, 江西南昌 330013;
2. 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, 江西南昌 330013;
3. 武汉大学测绘遥感信息工程国家重点实验室, 湖北武汉 430079

收稿日期:2023-10-07 发布日期:2024-06-12
作者简介:程朋根(1964—),男,博士,教授,主要从事地理信息系统理论与应用、城市生态环境评价研究。E-mail:pgcheng1964@163.com
基金资助:
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)

Progress and perspectives of urban functional region identification

CHENG Penggen^1,2, QI Guangyu¹, ZHONG Yanfei³

1. School of Surveying and Geoinformation Engineering, East China University of Technology, Nanchang 330013, China;
2. Key Laboratory of Mine Environmental Monitoring and Improving around Poyang Lake, Ministry of Natural Resources, Nanchang 330013, China;
3. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China

Received:2023-10-07 Published:2024-06-12

摘要/Abstract

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。

关键词: 城市功能区, 数据源, 识别方法, 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.

Key words: urban functional areas, data source, identification methods, research trends

中图分类号:

P208

程朋根, 齐广玉, 钟燕飞. 城市功能区识别研究进展与趋势[J]. 测绘通报, 2024, 0(5): 90-95.

CHENG Penggen, QI Guangyu, ZHONG Yanfei. Progress and perspectives of urban functional region identification[J]. Bulletin of Surveying and Mapping, 2024, 0(5): 90-95.

参考文献

[1] ANUGRAHA A S,CHU H J.Land use classification from combined use of remote sensing and social sensing data[J].The International Archives of the Photogrammetry,Remote Sensing and Spatial Information Sciences,2018,42(4):33-39.
[2] 杨然.数据挖掘支撑下的城市功能区识别研究[D].成都:电子科技大学,2019.
[3] GOLD J R.Creating the charter of athens:CIAM and the functional city,1933-43[J].The Town Planning Review,1998,69(3):225-247.
[4] BERRY B J L.Interdependency of spatial structure and spatial behavior:a general field theory formulation[J].Papers of the Regional Science Association,1968,21(1):205-227.
[5] KARLSSON C.Clusters,functional regions and cluster policies[J].JIBS and CESIS Electronic,2007,84(3):1-24.
[6] YAO Y,LI X,LIU X,et al.Sensing spatial distribution of urban land use by integrating points-of-interest and Google Word2Vec model[J].International Journal of Geographical Information Science,2017,31(4):825-848.
[7] PAN G,QI G,WU Z,et al.Land-use classification using taxi GPS traces[J].IEEE Transactions on Intelligent Transportation Systems,2013,14(1):113-123.
[8] 骆少华,刘扬,高思岩,等.基于空间格网的城市功能区定量识别[J].测绘通报,2020(S1):214-217.
[9] 王梅红,侯笑宇,司连法,等.地理空间数据结合手机信令等多源数据刻画城市居民出行特征[J].测绘通报,2022(5):162-165.
[10] 杨守国.上海市人口分布变动和城市功能区研究[D].北京:首都经济贸易大学,2007.
[11] 黄宁,张珞平,刘启明,等.基于持续发展理念的城市功能区划方法及应用研究[J].城市发展研究,2009,16(11):63-70.
[12] 黄怡敏,邵世维,雷英哲,等.运用网络核密度估计与克里格插值识别城市功能区[J].测绘地理信息,2019,44(4):14-18.
[13] 李娅,刘亚岚,任玉环,等.城市功能区语义信息挖掘与遥感分类[J].中国科学院大学学报,2019,36(1):56-63.
[14] LI J,XIE X,ZHAO B,et al.Identification of urban functional area by using multisource geographic data:a case study of Zhengzhou,China[J].Complexity,2021,2021(6):1-10.
[15] 周杭,樊红.基于众源地理数据的城市功能区及其热点的识别研究[J].武汉大学学报(工学版),2022,55(4):417-426.
[16] 杨文亮.基于多源数据的兰州市城市居民出行特征与功能区识别[D].兰州:西北师范大学,2021.
[17] SOTO V,FRÍAS-MARTÍNEZ E.Automated land use identification using cell-phone records [C]//Proceedings of the 3rd ACM International Workshop on MobiArch.[S.l.]:ACM Press,2011.
[18] 姚尧,张亚涛,关庆锋,等.使用时序出租车轨迹识别多层次城市功能结构[J].武汉大学学报(信息科学版),2019,44(6):875-884.
[19] 韩亚楠,刘建伟,罗雄麟.概率主题模型综述[J].计算机学报,2021,44(6):1095-1139.
[20] SONG G,KRZYSZTOF J,HHLEN C.Extracting urban functional regions from points of interest and human activities on location-based social networks[J].Transactions in GIS,2017,21(3):446-467.
[21] 于璐,何祥,刘嘉勇.基于时空语义挖掘的城市功能区识别研究[J].四川大学学报(自然科学版),2019,56(2):246-252.
[22] 高子为,孙伟伟,程朋根,等.融合高分辨率遥感影像和POI数据的多特征潜在语义信息用于识别城市功能区[J].遥感技术与应用,2021,36(3):618-626.
[23] XING H,MENG Y.Integrating landscape metrics and socioeconomic features for urban functional region classification[J].Computers,Environment and Urban Systems,2018,72:134-145.
[24] CHANG Shouzhi,WANG Zongming,MAO Dehua,et al.Identifying urban functional areas in China's Changchun city from Sentinel-2 images and social sensing data[J].Remote Sensing,2021,13(22):4512.
[25] ZHOU Wen,MING Dongping,LV Xianwei,et al.SO-CNN based urban functional zone fine division with VHR remote sensing image[J].Remote Sensing of Environment,2020,236:111458.
[26] LU Weipeng,TAO Chao,LI Haifeng,et al.A unified deep learning framework for urban functional zone extraction based on multi-source heterogeneous data[J].Remote Sensing of Environment,2022,270:112830.
[27] IZZO S,PREZIOSO E,GIAMPAOLO F,et al.Classification of urban functional zones through deep learning[J].Neural Computing and Applications,2022,34(9):6973-6990.
[28] BAO Hanqing,MING Dongping,GUO Ya,et al.DFCNN-based semantic recognition of urban functional zones by integrating remote sensing data and POI data[J].Remote Sensing,2020,12(7):1088.
[29] 肖迪,张小咏,胡杨.基于手机大数据的城市功能区识别方法[J].系统仿真学报,2019,31(11):2281-2288.
[30] YANG X,BO S,ZHANG Z.Classifying urban functional zones based on modeling POIs by deepwalk[J].Sustainability,2023,15(10):7995.
[31] FAN Runyu,FENG Ruyi,HAN Wei,et al.Urban functional zone mapping with a bibranch neural network via fusing remote sensing and social sensing data[J].IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2021,14:11737-11749.

城市功能区识别研究进展与趋势

Progress and perspectives of urban functional region identification

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