Using GIS Spatial Distribution to Predict Soil Organic Carbon in Subtropical China

Spatial distribution of organic carbon in soils is difficult to estimate because of inherent spatial variability and insufficient data. A soil-landscape model for a region, based on 151 samples for parent material and topographic factors,was established using a GIS spatial analysis technique and a digital elevation model (DEM) to reveal spatial distribution characteristics ofsoil organic carbon (SOC). Correlations between organic carbon and topographic factors were analyzed and a regression model was established to predict SOC content. Results for surface soils (0-20 cm) showed that the average SOC content was 12.8 g kg-1, with the SOC content between 6 and 12 g kg-1 occupying the largest area and SOC over 24 g kg-1 the smallest. Also, soils derived from phyllite were the highest in the SOC content and area, while soils developed on purple shale the lowest. Although parent material, elevation, and slope exposure were all significant topographic variables (P ＜0.01), slope exposure had the highest correlation to SOC content (r = 0.66). Using a multiple regression model (R2 = 0.611) and DEM (with a 30 m × 30 m grid), spatial distribution of SOC could be forecasted.