Predicting mattic epipedons in the northeastern Qinghai-Tibetan Plateau using Random Forest

Abstract

Mattic epipedon (ME), a special diagnostic surface horizon for soils in alpine meadow, plays an important role in carbon storage, soil water retention, and indication of alpine meadow degradation. At the global scale, it mainly distributes in the Qinghai-Tibetan Plateau and other similar alpine environments. However, its spatial patterns and the relations with environmental conditions remain unknown. This study attempts to explore key environmental variables responsible for the occurrence of the special surface soil horizon and based on those factors to predict and map digitally the spatial distribution of ME. By combining a variable selection procedure and the Random Forest (RF) algorithm, the variables extracted from Landsat 5 TM mosaic image, ASTER GDEM, and climate data were optimized and their importance was measured. The classification accuracy was compared with that obtained from binary logistic regression algorithm. In addition, a land use/land cover (LULC) map-based modification was conducted to further improve the classification accuracy. Results showed that the variable selection procedure had little effect in improving prediction accuracy. However, the number of used variables markedly reduced from 26 to 6 with a 77% decrease, which could speed up the training of the RF model (about one-third of the computation time could be saved). Analysis of variable importance showed that band 3 of TM and normalized difference vegetation index were the most important environmental variables influencing the occurrence of ME. The final overall accuracy of the ME map was predicted to be 84%. Our results demonstrate that the proposed procedure, which combined the proposed variables (derived from remote sensing, GDEM, and climate data), the variable selection approach, the RF algorithm, and the LULC map-based modification method can identify key environmental variables influencing the occurrence of ME and map the spatial distribution of ME effectively on the Qinghai-Tibetan Plateau.