Study on spatio-temporal modelling between NPP-VIIRS night-time light intensity and GDP for major urban agglomerations in China

Abstract

ABSTRACT Currently, most of the studies establish the relationship between night-time light intensity (NTLI) and gross domestic product (GDP) only in the temporal dimension or spatial dimension, without combining both of them or considering real spatio-temporal modelling. Moreover, few studies verify the spatio-temporal heterogeneity of the model. To solve the aforementioned problems, this paper is the first to propose using the geographically and temporally weighted regression model (GTWR) for coupling NTLI and GDP. The NTLI derived from NPP-VIIRS satellites and GDP statistics for 14 urban agglomerations in China from 2013 to 2020 were systematically studied by comparing four methods, including OLS (ordinary least squares), GWR (geographically weighted regression model), TWR (time-weighted regression model), and GTWR. It is found that the GTWR model has the highest coefficient of determination. This finding proves that ‘the spatio-temporal nature of material movement is inseparable from each other’ and verifies the superiority, correctness, and scientific validity of the GTWR model. The implications of this paper include 1) demonstrating the superiority of the GTWR model (i.e. three-dimensional spatio-temporal model) in fitting the relationship between NTLI and GDP of urban agglomerations; 2) solving the problem of insufficient sample size of the single dimension of NPP-VIIRS through the spatio-temporal model; 3) quantitatively detecting the spatio-temporal heterogeneity of urban agglomerations and analysing the high non-stationarity urban agglomerations by GTWR and spatio-temporal cube with spatio-temporal hot spot analysis.