Nighttime radiance as an urban indicator in Ciudad Juárez, Mexico: a spatial analysis using VIIRS and Landsat imagery

Abstract

Nighttime radiance captured by the VIIRS-DNB sensor provides a useful lens for examining urban inequality and territorially differentiated spatial configurations. This article analyzes its relationship with intra-urban attributes in Ciudad Juárez—population density, socioeconomic conditions, major roadways, industrial activity, commerce and services, NDVI, and NDBI—by integrating VIIRS-DNB and Landsat 8 imagery with census and economic data at the urban AGEB level. A global multiple linear regression model was first estimated as a baseline, followed by a geographically weighted regression (GWR) model to identify local variations in the strength and direction of these associations. The results show that nighttime radiance increased between 2013 and 2023 in a predominantly positive but territorially uneven manner. The global model achieved an R² of 0.600, whereas the GWR substantially improved model fit (R² = 0.940; AIC = 4262.48), indicating that the relationships between nighttime radiance and its predictors are not spatially homogeneous. These findings confirm the value of nighttime radiance as an intra-urban diagnostic tool and as a basis for a territorially differentiated reading of the city.