期刊论文

Jin, Cheng

英文

ISPRS International Journal of Geo-Information

2220-9964

2019

8

5

220-

10.3390/ijgi8050220

Conceptualization, Jianquan Cheng and Cheng Jin; Methodology, Lianfa Zhang and Jianquan Cheng; Software, Lianfa Zhang; Validation, Lianfa Zhang, Jianquan Cheng and Cheng Jin; Formal Analysis, Cheng Jin and Jianquan Cheng; Investigation, Cheng Jin; Resources, Cheng Jin; Data Curation, Jianquan Cheng; Writing-Original Draft Preparation, Cheng Jin; Writing-Review & Editing, Jianquan Cheng; Visualization, Cheng Jin; Supervision, Jianquan Cheng; Project Administration, Jianquan Cheng; Funding Acquisition, Cheng Jin and Jianquan Cheng. This research was funded by National Natural Science Foundation of China, grant number 41871137, 41571134, & 41571124 and the Natural Science Foundation of the Jiangsu Higher Education Institutions, grant number 16KJA170002.

本校为其他机构

Due to the emergence of new big data technology, mobility data such as flows between origin and destination areas have increasingly become more available, cheaper, and faster. These improvements to data infrastructure have boosted spatial and temporal modeling of OD (origin-destination) flows, which require the consideration of spatial dependence and heterogeneity. Both ordinary least square (OLS) and negative binomial (NB) regression methods have been used extensively to calibrate OD flow models by processing flow data as different types of dependent variables. This paper aims to compare both...