Abstract: The distribution of soil organic carbon (SOC) in urban areas is influenced by human factors such as ur? ban construction and industrialization, and thus shows obvious spatial differences. To reveal the impact of human ac? tivities such as urbanization and industrialization on SOC in Shizuishan City, the spatial distribution of SOC in Shi? zuishan was predicted using ordinary Kriging (OK), multiple linear regression Kriging (RK), remote sensing inver? sion (RS), and remote sensing- geographically weighted regression Kriging (RGWRK). The SOC content changed from 1.31 g/kg to 66.92 g·kg^{- 1}, with an average of 17.61 g·kg^{- 1}. There were significant differences in SOC content among different functional areas in Shizuishan (p < 0.05). Specifically, the performance in decreasing order was, in? dustrial areas, medical areas, commercial areas, roads, residential areas, parks, farmlands, scientific and education? al areas. The coefficient of variation of SOC content was 66.27% and there was moderate variation. The best fitting model was the Gauss model, and C₀/(C₀ +C) was 0.02, indicatingstrong spatial autocorrelation. There was a signifi? cant correlation (p < 0.01) between SOC and differences of DN values in different bands of RS images (B1-B7, B3- B7, and B4-B7) and topographic factors (elevation, slope, and relief amplitude). Comparing the results of the four methods demonstrated that SOC predicted by RGWRK was the most accurate, being 10.05% higher than that of OK, 8.79% higher than that of RK, and 8.92% higher than that of RS. SOC content in the northern part of Shizuis? han was higher than the southern part. The SOC content in industrial areas was 1.92 times higher than farmlands, in? dicating that the SOC content in the urban area was enriched.

Key words: soil organic carbon, spatial prediction, remote sensing inversion, geographically weighted regression Kriging