Soil carbon sequestration is of great significance for achieving China's 2060 carbon neutrality goal. However, differences in carbon sequestration between arid and humid regions remain unclear. Here, based on the Chinese terrestrial ecosystems carbon density dataset, this study employed the random forest (RF) model to map soil organic carbon density (SOCD) (1 km x 1 km) in arid and humid regions, and assessed the spatial uncertainty. The results indicated: (1) The RF model can explain about 79%-88% of SOCD variation in 2020. (2) The SOCD in arid regions (4.03 kg C m(-2) in 0-20 cm soil depth, and 9.84 kg C m(-2) in 0-100 cm), were significantly lower than those in humid regions (5.54 kg C m(-2), and 12.91 kg C m(-2)), and had greater spatial heterogeneity. (3) In arid regions, SOCD was mainly driven by mean annual precipitation (MAP), mean annual temperature (MAT), normalized difference vegetation index (NDVI), soil moisture (SM), and land use and land cover (LULC). In humid regions, it was driven by MAT, MAP, elevation, human footprint, and LULC. (4) SOCD exhibited a decreasing trend in arid regions, but exhibited an increasing trend in humid regions under different climate scenarios. The results of this study are of great significance for exploring the response of the SOC pool to climate change in arid and humid regions, identifying vulnerable areas and carbon sinks, and scientifically formulating regional carbon management policies to achieve the goal of carbon neutrality.