Abstract
The collection of spatialised electricity consumption data is considered of crucial importance for planning electric power facilities and achieving the United Nations Sustainable Development Goal 7 (SDG7). However, the predominance of statistical data on electricity consumption in China in combination with the lack of spatialised electricity consumption data for the past five years poses a serious challenge. To effectively address this issue, a nighttime light remote sensing estimation model of China's electricity consumption was developed in this work. Specifically, NPP-VIIRS nighttime light and publicly available electricity consumption data were used, and a spatialised Chinese electricity consumption data product for the period 2012-2023 was derived. At the same time, the time-space variation of China's electricity consumption was systematically analysed. For the spatial dimension, the power function model was proven to be the most suitable estimation model for China, with an average R(2) of 0.9385, while for the temporal dimension, the quadratic polynomial model was the most suitable, with an R(2) of 0.9706. From the analysis of time-space variation, an increase in both the number and extent of high electricity consumption areas was observed, particularly in third- and fourth-tier cities in the south, while some industrial cities experienced a decline in electricity consumption.