Carbon Emission Inversion Model from Provincial to Municipal Scale Based on Nighttime Light Remote Sensing and Improved STIRPAT

Carbon emissions and consequent climate change directly affect the sustainable development of ecological environment systems human society, which is a pertinent issue concern for all countries globally. The construction carbon emission inversion model has significant theoretical importance practical significance accounting control. Established models usually adopt socio-economic parameters or energy statistics to calculate emissions. However, high-precision estimates in administrative regions lacking are difficult. This problem especially prominent small-scale regions. Methods accurately estimate needed. Based on nighttime light remote-sensing data STIRPAT (Stochastic Impacts by Regression Population, Affluence, Technology) model, combined with environmental Kuznets curve, this paper proposes an ISTIRPAT (Improved Stochastic model. Through improved (ISTIRPAT) panel regression, provincial inventory were downscaled municipal level, scale inventories obtained. study took 17 cities prefectures Hubei Province, China, as example verify accuracy from 2012 2018 calculated original compared real values. results show that using downscale reached 0.9, was higher than Overall, Province showed upward trend. Regarding spatial distribution, main area formed central part ring-shaped mountain peak. lowest expanded outward, increased, gradually decreased edge province. overall composition eastern those western Hubei.