Discovering spatio-temporal patterns of human activity on the Qinghai-Tibet Plateau based on crowdsourcing positioning data

Jun XU; Yang XU; Lei HU; Zhenbo WANG

doi:10.11821/dlxb202007006

Journals >Acta Geographica Sinica >Volume 75 >Issue 7 >Page 1406 > Article

Acta Geographica Sinica
Vol. 75, Issue 7, 1406 (2020)

Discovering spatio-temporal patterns of human activity on the Qinghai-Tibet Plateau based on crowdsourcing positioning data

Jun XU^1、*, Yang XU^1、2, Lei HU^1、2, and Zhenbo WANG³

Author Affiliations

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

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

³Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China

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DOI: 10.11821/dlxb202007006 Cite this Article

Jun XU, Yang XU, Lei HU, Zhenbo WANG. Discovering spatio-temporal patterns of human activity on the Qinghai-Tibet Plateau based on crowdsourcing positioning data[J]. Acta Geographica Sinica, 2020, 75(7): 1406 Copy Citation Text

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Fig. 1. 3D display of average daily positioning requests' distribution in off-season and peak season of tourism

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Fig. 2. Daily positioning request numbers in off-season and peak season of tourism

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Fig. 3. Hourly positioning request numbers in off-season and peak season of tourism

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Fig. 4. Tucker model of tensor decomposition

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Fig. 5. Flowchart of the research

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Fig. 6. Cost function values of different S-T-D compositions for dataset in off-season of tourism

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Fig. 7. Cost function values of different S-T-D compositions for dataset in peak season of tourism

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Fig. 8. Distributions of daily patterns in off-season and peak season of tourism

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Fig. 9. Distributions of hourly patterns in off-season and peak season of tourism

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Fig. 10. Cluster centroids of spatial patterns in off-season and peak season of tourism

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Fig. 11. Clusters of spatial patterns in off-season and peak season of tourism

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参数	参数含义	参数范围
S	区域模式特征模数	[3, 15]
T	时段模式特征模数	[3, 6]
D	日模式特征模数	[2, 3]

Table 1. Parameter selection for tucker decomposition

	T1			T2			T3
	D1	D2	D3	D1	D2	D3	D1	D2	D3
S1	0.1231	0.0000	0.0000	0.2751	0.0000	0.0000	0.0000	0.0000	0.0000
S2	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.3983	0.0000	0.0000
S3	0.2224	0.2617	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000
S4	0.0000	0.0000	0.0000	0.0000	0.0000	0.3775	0.0000	0.0000	0.0000
S5	0.0000	0.0021	0.0000	0.0000	0.0000	0.0000	0.0000	0.4192	0.0000
S6	0.0005	0.0000	0.2564	0.0000	0.0000	0.0000	0.0003	0.0012	0.0000
S7	0.0000	0.0958	0.0000	0.0000	0.2938	0.0429	0.0000	0.0000	0.0000
S8	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.3913

Table 2. The core tensor of dataset in off-season of tourism

	T1		T2		T3		T4
	D1	D2	D1	D2	D1	D2	D1	D2
S1	0.4005	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000
S2	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.3904
S3	0.0000	0.0000	0.3422	0.0000	0.0000	0.0000	0.0000	0.0000
S4	0.0000	0.0000	0.0000	0.0000	0.0000	0.3618	0.0000	0.0000
S5	0.0000	0.0000	0.0000	0.0000	0.2748	0.0000	0.0000	0.0000
S6	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.3493	0.0000
S7	0.0000	0.3427	0.0000	0.0000	0.0030	0.0001	0.0062	0.0000
S8	0.0000	0.0000	0.0000	0.3524	0.0000	0.0000	0.0000	0.0000

Table 3. The core tensor of dataset in peak season of tourism

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