Mining the Spatial-Temporal Characteristics of Population Flow and Material Flow Using Big Data
Joint Authors
Chen, Hongguang
Lin, Mingwei
Ji, Jianwan
Jin, Biao
Huang, Shuhong
Wang, Xing
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-20, 20 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-09-29
Country of Publication
Egypt
No. of Pages
20
Main Subjects
Abstract EN
Population flow and material flow are the core elements of the “space of flows.” Studying the temporal and spatial distribution characteristics of these two types of flows (TToF) can provide us a greater understanding of the research area.
Most of the existing works related to TToF only focus on exploring the difference characteristics of one of the members of TToF in a certain time or space scale in the research area.
Different from these related works, the spatial-temporal characteristics of the population flow and material flow in Taiwan Province and the spatial-temporal autocorrelation of Taiwan’s expressway network are explored by means of multimembership and layer-by-layer refinement.
The research work carried out in this paper includes the following: (1) studying the differentiated characteristics of the TToF in different time units; (2) studying the spatial differences among each type of the TToF under different scales; (3) dividing both the population flow and material flow into two subtypes and then analyzing the temporal variation characteristics of the four subtypes of flows; and (4) studying the global and local spatial-temporal autocorrelation of Taiwan’s expressway network.
The results show the following.
(1) The spatial-temporal differentiation characteristics of the TToF are obvious in different time units and on different scales.
(2) The contribution of the population flow to the TToF in flow quantities is far greater than that of the material flow.
(3) The population flow and material flow are dominated by the “minority population flow” and “small-scale material flow,” respectively.
(4) Meanwhile, in Taiwan’s expressway network, there is a significant spatial-temporal positive correlation mainly reflected in the spatial first-order adjacent road sections.
American Psychological Association (APA)
Wang, Xing& Ji, Jianwan& Jin, Biao& Chen, Hongguang& Huang, Shuhong& Lin, Mingwei. 2020. Mining the Spatial-Temporal Characteristics of Population Flow and Material Flow Using Big Data. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-20.
https://search.emarefa.net/detail/BIM-1193940
Modern Language Association (MLA)
Wang, Xing…[et al.]. Mining the Spatial-Temporal Characteristics of Population Flow and Material Flow Using Big Data. Mathematical Problems in Engineering No. 2020 (2020), pp.1-20.
https://search.emarefa.net/detail/BIM-1193940
American Medical Association (AMA)
Wang, Xing& Ji, Jianwan& Jin, Biao& Chen, Hongguang& Huang, Shuhong& Lin, Mingwei. Mining the Spatial-Temporal Characteristics of Population Flow and Material Flow Using Big Data. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-20.
https://search.emarefa.net/detail/BIM-1193940
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1193940