基于位置大数据的青藏高原人类活动时空模式

doi:10.11821/dlxb202007006

Abstract

Abstract:

The activities of local people and tourists have great effects on the ecological environment on the Qinghai-Tibet Plateau. Different kinds of activities may cause different impacts on ecology and environment. To effectively protect the ecological environment, it is necessary to study the spatiotemporal patterns of different kinds of human activities. In this paper, two Tencent positioning datasets which record one-week location requests in January and July of 2018, respectively, are used to explore the human activities in off-season and peak season of tourism on the plateau. A Tucker tensor decomposition method is employed to reduce the dimension of massive data and obtain the principle modes of human activities. The data in off-season are decomposed into 3 daily patterns, 3 hourly patterns and 8 spatial patterns, and the data in peak season are decomposed into 2 daily patterns, 4 hourly patterns and 8 spatial patterns. By analyzing the core tensor, different kinds of activities are inferred through the relations among different dimensions of data, and the human activities in off-season and peak season of tourism are analyzed. The human activities on the Qinghai-Tibet Plateau are found to be different from those in other places. Different from ordinary weekday and weekend patterns, there is a mid-week pattern (Tuesday through Friday) and an inter-week pattern (Saturday, Sunday and Monday) on the Qinghai-Tibet Plateau, and there is a special holiday pattern in off-season of tourism. It is also found that the human activities in off-season and peak season of tourism are different, which indicates different activities of the local residents and the tourists. In off-season of tourism, the positioning activities are very active in the morning, however, the activities are less active during the daytime of mid-week days than during the daytime of inter-week days, and the activities are mostly found in the cities in the mid-week days but mostly in the outskirts of the cities or on the way to scenic spots in the inter-week days. In off-season, there exist the activities of local residents. In peak season, there are less activities in the morning, but the activities during the day are more broadly distributed both in the mid-week days and in the inter-week days. It is indicated that the activities of tourists are significant in the peak season. After clustering spatial grids with similar patterns, we find that there are mixed spatial patterns in most parts of the study area, which discloses that there are usually multiple kinds of human activities in a region.

Key words: Qinghai-Tibet Plateau, human activity, off-season and peak season, big data, tensor decomposition

XU Jun, XU Yang, HU Lei, WANG Zhenbo. Discovering spatio-temporal patterns of human activity on the Qinghai-Tibet Plateau based on crowdsourcing positioning data[J].Acta Geographica Sinica, 2020, 75(7): 1406-1417.

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References 21

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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]

	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

	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

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

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