Derivation of Soil Roughness Using Multi-Temporal Laser Scanning Point Clouds

The present paper deals with the derivation of roughness parameters of soil from laser scanning point clouds, allowing to draw conclusions about properties of the soil (e. g. soil aggregation, soil sealing) and related to this its vulnerability to soil erosion. For this purpose, soil erosion scenes with agricultural cultivation are acquired in five measuring epochs under field conditions. For geo-referencing of the acquired time series of point clouds, a target-based and a data-driven approach are compared. In order to derive roughness parameters, the point clouds are cleaned of vegetation and then modelled to reduce the measurement noise. For this purpose, a collocation-based approach is used, in which a trend surface roughly approximates the point clouds. Remaining systematic deviations, which are caused by the insufficient functional approximation, are caught with the help of a stochastic signal, the variances and correlations lengths of which simultaneously provide information about the soil’s roughness.