Analysis of Factors for Pedestrians’ Spatial Distribution in Sakae District of Nagoya Using Mobile Phone Location Data

Zhang, Yufan and Kaneda, Toshiyuki and Ota, Akira (2022) Analysis of Factors for Pedestrians’ Spatial Distribution in Sakae District of Nagoya Using Mobile Phone Location Data. Mobility, Knowledge and Innovation Hubs in Urban and Regional Development. Proceedings of REAL CORP 2022, 27th International Conference on Urban Development, Regional Planning and Information Society. pp. 79-88. ISSN 2521-3938

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Abstract

Recently, mobile phone location data containing the activities of different urban residents can be employed for an urban study. Compared with field research, mobile phone location data have a larger volume, wider range, and higher frequency. It can provide fresh data to support urban research. Most analyses of the spatial distribution of pedestrians employ linear or log–log models using least squares, but the drawback is that the number of pedestrians and the number of counts do not always follow a normal distribution and the leastsquares method is vulnerable to outlier effects. Thus, the use of generalised linear model (GLM) with maximum likelihood estimation for the analysis of the factors influencing pedestrian distribution makes sense. However, these models lack suitable indicators to rank the factors’ strengths. In this study, we employed the Sakae district of Nagoya as the object of the study and divided the factors influencing the spatial distribution of pedestrians into four categories: street attribute factor, land use, space configuration, and transportation accessibility factor. Finally, we employed a GLM to study the factors influencing the pedestrians’ distribution. We introduced a mean standardised partial differential value to compare the significance of each variable in the model. The findings showed that the correlation coefficient between forecast and actual values was better for the linear model whereas the mean absolute percent error was better for the negative binomial distribution model. Both models revealed that the integration value generated from the segment angular investigation was substantially correlated with the pedestrian distribution as a space configuration indicator.

Item Type:	Article
Uncontrolled Keywords:	Mobile Phone Location Data, Pedestrians, Generalized Linear Model, Segment Angular Analysis, Urban Planning
Subjects:	G Geography. Anthropology. Recreation > G Geography (General) G Geography. Anthropology. Recreation > GE Environmental Sciences
Depositing User:	The CORP Team
Date Deposited:	10 Nov 2022 13:38
Last Modified:	18 Dec 2022 14:20
URI:	http://repository.corp.at/id/eprint/893

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