Chapter 4

Methods of Social Sensing for Urban Studies

Yu Liu

Yu Liu

Institute of Remote Sensing and Geographical Information Systems, School of Earth and Space Sciences, Peking University, Beijing, China

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Song Gao

Song Gao

Department of Geography, University of Wisconsin-Madison, Madison, WI, USA

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Yihong Yuan

Yihong Yuan

Department of Geography, Texas State University, San Marcos, TX, USA

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Fan Zhang

Fan Zhang

Institute of Remote Sensing and Geographical Information Systems, School of Earth and Space Sciences, Peking University, Beijing, China

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Chaogui Kang

Chaogui Kang

Department of Geographic Information Engineering, Wuhan University, Wuhan, China

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Yuhao Kang

Yuhao Kang

Department of Geography, University of Wisconsin-Madison, Madison, WI, USA

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Keli Wang

Keli Wang

Institute of Remote Sensing and Geographical Information Systems, School of Earth and Space Sciences, Peking University, Beijing, China

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First published: 30 September 2021
Citations: 4

Summary

Analyzing large volumes of big geo-data through social sensing provides new research opportunities in urban studies. Such big geo-data include mobile phone records, social media posts, vehicle trajectories, and street view images. They can be used to extract human behavior patterns and infer the geographical characteristics of cities. This chapter discusses a number of analytical methods for big geo-data in social sensing studies, such as temporal signature analysis, text analysis, and image analysis. These methods can be used for various applications such as estimating urban vibrancy, formalizing place semantics, and modeling intraurban human mobility patterns. We structure the chapter sections from a perspective of first- and second-order properties in spatial statistics .

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