Big geodata mining: Objective, connotations and research issues

Tao PEI; Ci SONG; Sihui GUO; Hua SHU; Yaxi LIU; Yunyan DU; Ting MA; Chenghu ZHOU

doi:10.1007/s11442-020-1726-7

Journals >Journal of Geographical Sciences >Volume 30 >Issue 2 >Page 251 > Article

Journal of Geographical Sciences
Vol. 30, Issue 2, 251 (2020)

Big geodata mining: Objective, connotations and research issues

Tao PEI^1、2、*, Ci SONG^1、2, Sihui GUO^1、2, Hua SHU^1、2, Yaxi LIU^1、2, Yunyan DU^1、2, Ting MA^1、2, and Chenghu ZHOU^1、2

Author Affiliations

¹. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China

². University of Chinese Academy of Sciences, Beijing 100049, China

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DOI: 10.1007/s11442-020-1726-7 Cite this Article

Tao PEI, Ci SONG, Sihui GUO, Hua SHU, Yaxi LIU, Yunyan DU, Ting MA, Chenghu ZHOU. Big geodata mining: Objective, connotations and research issues[J]. Journal of Geographical Sciences, 2020, 30(2): 251 Copy Citation Text

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Fine-scale demographic estimation using mobile phone data (et al., 2018" target="_self" style="display: inline;">Liu et al., 2018)

Fig. 1. Fine-scale demographic estimation using mobile phone data (Liu et al., 2018)

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Transformation between homogeneity and heterogeneity of the geographical point process at difference scales: (a) heterogeneity at a large scale; (b) homogeneity at a small scale.

Fig. 2. Transformation between homogeneity and heterogeneity of the geographical point process at difference scales: (a) heterogeneity at a large scale; (b) homogeneity at a small scale.

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