Abstract
The P-factor for support practice of the Universal Soil Loss Equation (USLE) accounts for soil conservation measures and leads to a significant reduction in the modelled soil loss. However, in the practical application, the P-factor is the most neglected factor overall due to high effort for determining or lack of input data. This study provides a new method for automatic derivation of the main cultivation direction from seed rows and tramlines on agricultural land parcels using the Fast Line Detector (FLD) of the Open Computer Vision (OpenCV) package and open remote sensing data from Google Earth™. Comparison of the cultivation direction with the mean aspect for each land parcel allows the determination of a site-specific P-factor for the soil conservation measure contouring. After calibration of the FLD parameters, the success rate in a first application in the low mountain range Fischbach catchment, Germany, was 77.7% for 278 agricultural land parcels. The main reasons for unsuccessful detection were problems with headland detection, existing soil erosion, and widely varying albedo within the plots as well as individual outliers. The use of a corrected mask and enhanced parameterization offers promising improvements for a higher success rate of the FLD.
Highlights
Soil erosion caused by wind or water is a well-known global problem, but a natural process
The share of arable land is somewhat lower at 61%, and with only 38.5%, this share is significantly lower for land is somewhat lower at 61%, and with only 38.5%, this share is significantly lower the Fischbach catchment
To detect the main cultivation direction on each land parcel, the Fast Line Detector (FLD) for detecting linear elements was applied to open remote sensing data retrieved from Google EarthTM
Summary
Soil erosion caused by wind or water is a well-known global problem, but a natural process. The term soil erosion includes the processes of detachment, transportation, and sedimentation of soil particles [1]. The intensity of the removed mass depends on erosive factors such as precipitation and the resulting surface runoff as well as erodible factors that take into account soil properties and land cover as well as practice management [3]. High erosion rates can lead to significant damage, initially affecting the farmland itself, known as on-site damage. The associated loss of the most fertile topsoil causes a decrease in soil quality and productivity and an impairment of important soil functions, which in turn leads to a loss of yield [4]
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