Soil property mapping by combining spatial distance information into the Soil Land Inference Model(SoLIM)

The Soil Land Inference Model(SoLIM) was primarily proposed by Zhu et al.(Zhu A X, Band L, Vertessy R, Dutton B. 1997. Derivation of soil properties using a soil land inference model(SoLIM). Soil Sci Soc Am J. 61: 523–533.) and was based on the Third Law of Geography. Based on the assumption that the soil property value at a location of interest will be more similar to that of a given soil sample when the environmental condition at the location of interest is more similar to that at the location from which the sample was taken, SoLIM estimates the soil property value of the location of interest using the soil property values of known samples weighted by the similarity between those samples and the location of interest in terms of an attribute domain of environmental conditions. However, the current SoLIM method ignores information about the spatial distances between the location of interest and those of the sample. In this study, we proposed a new method of soil property mapping, So LIM-IDW, which incorporates spatial distance information into the SoLIM method by means of inverse distance weighting(IDW). The proposed method is based on the assumption that the soil property value at a location of interest will be more similar to that of a known sample both when the environmental conditions are more similar and when the distance between the location of interest and the sample location is shorter. Our evaluation experiments on A-horizon soil organic matter mapping in two study areas with independent evaluation samples showed that the proposed SoLIM-IDW method can obtain lower prediction errors than the original SoLIM method, multiple linear regression, geographically weighted regression, and regression-kriging with the same modeling points. Future work mainly includes the determination of optimal power parameter values and the appropriate setting of the parameter under different application contexts.

Bank gully extraction from DEMs utilizing the geomorphologic features of a loess hilly area in China

As one of most active gully types in the Chinese Loess Plateau,bank gullies generally indicate soil loss and land degradation.This study addressed the lack of detailed,large scale monitoring of bank gullies and proposed a semi-automatic method for extracting bank gullies,given typical topographic features based on 5 m resolution DEMs.First,channel networks,including bank gullies,are extracted through an iterative channel bum-in algorithm.Second,gully heads are correctly positioned based on the spatial relationship between gully heads and their corresponding gully shoulder lines.Third,bank gullies are distinguished from other gullies using the newly proposed topographic measurement of "relative gully depth (RGD)."The experimental results from the loess hilly area of the Linjiajian watershed in the Chinese Loess Plateau show that the producer accuracy reaches 87.5%. The accuracy is affected by the DEM resolution and RGD parameters,as well as the accuracy of the gully shoulder line.The application in the Madigou watershed with a high DEM resolution validated the duplicability of this method in other areas.The overall performance shows that bank gullies can be extracted with acceptable accuracy over a large area,which provides essential information for research on soil erosion,geomorphology,and environmental ecology.