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Mapping urban villages based on point-of-interest data and a deep learning approach

文献类型：期刊论文

作者Li, Ting2,6; Feng, Quanlong5,6; Niu, Bowen6; Chen, Boan4; Yan, Fengqin5; Gong, Jianhua1; Liu, Jiantao3
刊名CITIES
出版日期2025
卷号156页码:19
关键词Urban village Deep learning Data mining Point-of-interest
ISSN号0264-2751
DOI10.1016/j.cities.2024.105549
产权排序2
英文摘要In the process of urban development, spatial structure within cities undergoes great changes, where the rural areas are surrounded by newly urban blocks, leading to the widespread of urban villages. Thus, quick and accurate prediction of urban villages is crucial for urban planning, management and sustainability. Recently, pointof-interest (POI) data mining has emerged as a popular topic in urban research. This study aims to propose an urban village prediction model in complex urban landscape patterns by utilizing POI data as a single data source. We firstly calculated word embeddings of POI types as the semantic features of urban villages based on Word2Vec. Afterwards, a BiLSTM-Multiscale-Attention (BMA) model is proposed to predict urban or non-urban villages based on POI word embeddings. Experimental results in several major cities of China, including Beijing, Tianjin, Xi'an, Shijiazhuang, Wuhan, and Guangzhou indicates that the proposed model achieved an average overall accuracy of 84.06 %, outperforming several other data-driven methods. This study demonstrates that POI data can provide accurate spatial distribution information for urban villages. These findings provide new ideas and references for comprehensive understanding of urban villages at a fine scale.
WOS关键词SATELLITE IMAGES ; CHINA
资助项目National Natural Science Foundation of China[42171113] ; State Key Laboratory of Resources and Environmental Information System
WOS研究方向Urban Studies
语种英语
WOS记录号WOS:001348124900001
出版者ELSEVIER SCI LTD
资助机构National Natural Science Foundation of China ; State Key Laboratory of Resources and Environmental Information System
源URL[http://ir.igsnrr.ac.cn/handle/311030/210882]  
专题资源与环境信息系统国家重点实验室_外文论文
通讯作者Feng, Quanlong
作者单位1.Chinese Acad Sci, Aerosp Informat Res Inst, Natl Engn Res Ctr Geoinformat, Beijing 100101, Peoples R China
2.Minist Nat Resources Peoples Republ China, Consulting & Res Ctr, Beijing 100035, Peoples R China
3.Shandong Jianzhu Univ, Sch Surveying & Geoinformat, Jinan 250101, Shandong, Peoples R China
4.Wuhan Univ, Sch Remote Sensing & Informat Engn, Wuhan 430079, Peoples R China
5.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China
6.China Agr Univ, Coll Land Sci & Technol, Beijing 100193, Peoples R China
推荐引用方式
GB/T 7714		 Li, Ting,Feng, Quanlong,Niu, Bowen,et al. Mapping urban villages based on point-of-interest data and a deep learning approach[J]. CITIES,2025,156:19.
APA Li, Ting.,Feng, Quanlong.,Niu, Bowen.,Chen, Boan.,Yan, Fengqin.,...&Liu, Jiantao.(2025).Mapping urban villages based on point-of-interest data and a deep learning approach.CITIES,156,19.
MLA Li, Ting,et al."Mapping urban villages based on point-of-interest data and a deep learning approach".CITIES 156(2025):19.

入库方式： OAI收割

来源：地理科学与资源研究所

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