Social Sensing: A New Approach to Understanding Our Socioeconomic Environments

被引:632
作者
Liu, Yu [1 ,2 ]
Liu, Xi [1 ]
Gao, Song [3 ]
Gong, Li [1 ]
Kang, Chaogui [1 ]
Zhi, Ye [1 ]
Chi, Guanghua [1 ]
Shi, Li [1 ]
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] Univ Calif Santa Barbara, Dept Geog, Santa Barbara, CA 93106 USA
基金
中国国家自然科学基金;
关键词
spatial interaction; social sensing; temporal activity pattern; GIScience; place semantics; LAND-USE CLASSIFICATION; BIG DATA; PATTERNS; INFORMATION; MOBILITY; NETWORK; TWITTER;
D O I
10.1080/00045608.2015.1018773
中图分类号
P9 [自然地理学]; K9 [地理];
学科分类号
0705 ; 070501 ;
摘要
The emergence of big data brings new opportunities for us to understand our socioeconomic environments. We use the term social sensing for such individual-level big geospatial data and the associated analysis methods. The word sensing suggests two natures of the data. First, they can be viewed as the analogue and complement of remote sensing, as big data can capture well socioeconomic features while conventional remote sensing data do not have such privilege. Second, in social sensing data, each individual plays the role of a sensor. This article conceptually bridges social sensing with remote sensing and points out the major issues when applying social sensing data and associated analytics. We also suggest that social sensing data contain rich information about spatial interactions and place semantics, which go beyond the scope of traditional remote sensing data. In the coming big data era, GIScientists should investigate theories in using social sensing data, such as data representativeness and quality, and develop new tools to deal with social sensing data.
引用
收藏
页码:512 / 530
页数:19
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