Acta Geographica Sinica ›› 2016, Vol. 71 ›› Issue (4): 564-575.doi: 10.11821/dlxb201604003

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Revisiting several basic geographical concepts:A social sensing perspective

LIU Yu   

  1. Institute of Remote Sensing and Geographical Information Systems, Peking University, Beijing 100871, China
  • Received:2015-08-24 Published:2020-05-22
  • Supported by:
    National Natural Science Foundation of China, No.41271386, No.41428102; State Key Laboratory of Resources and Environmental Information System]

Abstract: Recently, various big data are drawing more and more attention in geographical research and many scholars have conducted lots of empirical studies using mobile phone data,social media data, taxi data, and so forth. Social sensing,a newly proposed concept, represents the capability of revealing socio- economic geographical features by capturing the spatial behavior patterns of a large population. Given that the term "environment" in humanenvironment interaction studies have involved the behavioral environment, social sensing techniques provide us a new approach to understanding human- environment interactions.Additionally, the emergence of social sensing helps us to rethink several fundamental issues in geographical studies. This article revisits two groups of core concepts: spatial distribution and spatial interaction, as well as qualitative method and quantitative method. Based on the fact that big data measure distributions and interactions at both individual and aggregate levels, we can quantify the underlying distance and scale effects from the observed patterns. To tackle space and population heterogeneity, clustering methods can be introduced to decompose a space and/ or a population into relatively homogeneous human groups and places. Considering that human groups and places are essential to qualitative studies, we argue that social sensing offers an opportunity to integrate big data and survey-based small data, and consequently, qualitative and quantitative methods are integated. Obviously, the second merit makes it possible to construct hybrid geography.

Key words: big data, social sensing, spatial distribution, spatial interaction, qualitative method, quantitative method