Spatiotemporal characteristics of carbon emissions in Shaanxi, China, during 2012–2019: a machine learning method with multiple variables

The back propagation neural network is adopted to estimate carbon emissions at county level in Shaanxi, China, using nighttime light, Normalized Difference Vegetation Index, precipitation, land surface temperature, elevation, and population density, and it can estimate carbon emissions of Shaanxi Province at a finer scale with an acceptable accuracy.