PROGRESS IN GEOGRAPHY ›› 2006, Vol. 25 ›› Issue (2): 112-122.doi: 10.11820/dlkxjz.2006.02.013

• Original Articles • Previous Articles     Next Articles

Spatial Variability and Prediction of Soil Organic Matter at County Scale on the Loess Plateau

LIAN Gang11,2, 21, GUO Xudong12, FU Bojie22   

  1. y Laboratory of Land Use, Ministry of Land and Resources, China Land Surveying &|Planning Institute, Beijing 100035|2 Key Laboratory of Systems Ecology,Research Center for Eco-Environmental Sciences, CAS, Beijing, 100085
  • Received:2006-01-01 Revised:2006-02-01 Online:2006-03-25 Published:2006-03-25

Abstract:

Analysis and forecast on the spatial distribution and dynamics of soil properties is an important element of sustainable land management. Spatial variation of soil organic matter was analyzed according to different land use types and different topography conditions, based on data from 254 points of surface soil (0~20cm) in Hengshan county on the Loess Plateau (NW China). Correlation analyses were carried out between the soil organic matter and the terrain attributes and remote sensing indices. Finally, the land use types and the terrain attributes and remote sensing indices were used to predict soil organic matter spatial distribution by multiple-linear regression analysis. Significant differences in soil organic matter among different land use types were found, the highest values in soil organic matter were measured in soils from paddy field, and lower values in the soils from woodland and shrub land. For soil organic matter, the tendency was: paddy field>irrigated farmland>terrace farmland>check-dam farmland>grassland>slope farmland>woodland>shrub land. In different slope gradients, soil organic matter in ‘0~3°’ gradients was significantly higher than other slope gradient classes. There was little difference in soil organic matter among different slope aspects, but there was a tendency that soil organic matter in northern aspects was higher. Different correlations were found between the soil organic matter and the terrain attributes and remote sensing indices. It was found that there are positive correlations between soil organic matter and the COSα, CTI, MSAVI and WI. There is a strong negative correlation between soil organic matter and elevation. Using environmental variables to predict soil organic matter, the regression model explains 34.6% of the variability of the measured soil organic matter. But the variation is rather large and there is a more smoothing effect on the predicted values for soil organic matter.

Key words: land use, regression analysis, remote sensing indices, soil organic matter, spatial variation, terrain attributes

CLC Number: 

  • S159