Incorporating spatial interaction patterns in classifying and understanding urban land use

被引:148
作者
Liu, Xi [1 ,2 ,3 ]
Kang, Chaogui [4 ]
Gong, Li [1 ,2 ]
Liu, Yu [1 ,2 ]
机构
[1] Peking Univ, Inst Remote Sensing & Geog Informat Syst, Beijing 100871, Peoples R China
[2] Peking Univ, Beijing Key Lab Spatial Informat Integrat & Its A, Beijing 100871, Peoples R China
[3] Penn State Univ, Dept Geog, University Pk, PA 16802 USA
[4] Wuhan Univ, Sch Remote Sensing & Informat Engn, Wuhan 430072, Peoples R China
基金
中国国家自然科学基金;
关键词
Urban land use; spatial interaction; classification; social sensing;
D O I
10.1080/13658816.2015.1086923
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Land use classification has benefited from the emerging big data, such as mobile phone records and taxi trajectories. Temporal activity variations derived from these data have been used to interpret and understand the land use of parcels from the perspective of social functions, complementing the outcome of traditional remote sensing methods. However, spatial interaction patterns between parcels, which could depict land uses from a perspective of connections, have rarely been examined and analysed. To leverage spatial interaction information contained in the above-mentioned massive data sets, we propose a novel unsupervised land use classification method with a new type of place signature. Based on the observation that spatial interaction patterns between places of two specific land uses are similar, the new place signature improves land use classification by trading off between aggregated temporal activity variations and detailed spatial interactions among places. The method is validated with a case study using taxi trip data from Shanghai.
引用
收藏
页码:334 / 350
页数:17
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