Digital mapping of soil carbon stock in Jeolla province using cubist model

Seong-Jin Park1,2   Chul-Woo Lee1   Seong-Heon Kim1   Take Keun Oh2,*   

1Division of soil and fertilizer, National Institute of Agricultural Science, RDA, Wanju 55365, Korea
2Department of Bio-Environmental Chemistry, College of Agriculture and Life Science, Chungnam National University, Daejeon 34134, Korea


Assessment of soil carbon stock is essential for climate change mitigation and soil fertility. The digital soil mapping (DSM) is well known as a general technique to estimate the soil carbon stocks and upgrade previous soil maps. The aim of this study is to calculate the soil carbon stock in the top soil layer (0 to 30 cm) in Jeolla Province of South Korea using the DSM technique. To predict spatial carbon stock, we used Cubist, which a data-mining algorithm model base on tree regression. Soil samples (130 in total) were collected from three depths (0 to 10 cm, 10 to 20 cm, 20 to 30 cm) considering spatial distribution in Jeolla Province. These data were randomly divided into two sets for model calibration (70%) and validation (30%).-2. The R2 value representing the model's performance was 0.6, which was relatively high compared to a previous study. The total soil carbon stocks at a depth of 0 to 30 cm in Jeolla Province were estimated to be about 81 megatons.

Figures & Tables

Fig. 1. Sampling site (n = 130) on Jeolla Province.