L-function of geographical flows. Issue 4 (3rd April 2021)

• Record Type: Journal Article
• Authors: Shu, Hua; Pei, Tao; Song, Ci; Chen, Xiao; Guo, Sihui; Liu, Yaxi; Chen, Jie; Wang, Xi; Zhou, Chenghu
• Is Part Of: International journal of geographical information science. Volume 35:Issue 4(2021)
• Page Start: 689
• Page End: 716
• Publication Date: 2021-04-03
• Subjects: Flow space -- aggregation scale -- Ripley's L-function -- origin-destination flow -- spatial statistics; Geography -- Data processing -- Periodicals; Information storage and retrieval systems -- Periodicals; Géomatique -- Périodiques; Systèmes d'information -- Périodiques; 910.285
• DOI: 10.1080/13658816.2020.1749277
• Languages: English
• ISSNs: 1365-8816

Abstract

ABSTRACT: Geographical flow (hereafter flow) can be modeled as an orderly connected point pair composed of an origin (O) and a destination (D). Aggregation is the most common form of spatial heterogeneity of flows, which we define as their deviation from complete spatial randomness (CSR), and the aggregation scale is an important indicator for its perception. Nevertheless, quantifying the aggregation scale of flows is still an unsolved problem. In this paper, we propose the L-function for flows as a solution, derive theoretical null models of the K-function and L-function in a flow space. We conduct simulation experiments to validate the L-function and its capability to detect aggregation scales. Finally, we apply the solution in a case study with taxi data in Beijing and identify nine aggregation scales of taxi OD flows, ranging from 170 m to 22.1 km. These scales correspond to three classes: less than 300 m, from 600 m to 700 m and more than 1500 m. The classes are related to the sizes of the urban facilities where the dominant flow clusters occur, indicating that the L-function in flow space can detect the aggregation scale of flows at the building scale, the block scale and the district scale.