Analysing spatio-temporal co-location of categorical incidents : a case study of chronic respiratory diseases in Nanning City

Cheng, Jianquan ORCID: https://orcid.org/0000-0001-9778-9009, Li, Ling, Mai, Xiongfa and Duan, Lian (2022) Analysing spatio-temporal co-location of categorical incidents : a case study of chronic respiratory diseases in Nanning City. In: GISRUK 2022: Geographical Information Science Research UK 2022, 05 April 2022 - 08 April 2022, University of Liverpool.

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Abstract

Analysing spatial pattern of chronic respiratory diseases particularly in children is prerequisite for modelling its demographical, behavioural, and environmental contributions. This paper aims to explore the application of an innovative approach – geographically and temporally weighted co-location quotient (GTWCLQ) into such case study of Nanning City in 2016. The results exhibit the values of GTWCLQ in analysing the spatio-temporal associations, including symmetrical and asymmetrical dependence, between five categories of such diseases by considering their spatio-temporal dependence and heterogeneity. The paper has also discussed its scaling effect and unbalanced temporal scale problem in such urban big data analytics.