Applying two-dimensional Fourier Transform to investigate soil surface porosity by laser-scanned data

Soil surface porosity (SSP) is often a concern in agro-ecosystem. The technique of indirect determination of SSP using a laser scanner was proposed but an ideal index relating soil surface roughness (SSR) to SSP is still expected. This study presented an index based on two-dimensional Fourier Transform (2DFT). The field experiment was conducted at the Dikopshof Farm (6°57′17″E, 50°48′17″N), Bonn, Germany, where soil textural composition (g g−1) was: sand 0.17, silt 0.67, clay 0.16, and organic matter content 0.019 (silt-loam, USDA Standard). Because SSP is not only altered by specific cultivation, but also temporally affected by weather factors, this index was validated with the data laser-scanned from an agricultural field tilled by two types of cultivators and the rainfall data of two years. We found that the variations of soil surface elevation in large- or small-scale could be separated by the spectrum of 2DFT. Consequently, the defined index was sufficient to transform the measured SSR into SSP for these tillage treatments (0.893 ≤ R2 ≤ 0.969) even though the rainfall data of the two years were different. More importantly, the laser scanning time was considerably reduced from about 40 min to 2.5 min using the proposed index in combination with the analysis of grid size.

► Large- and small-scale variations of tilled field can be separable by 2DFT spectrums.
► The proposed index closely relates to SSP under each tillage and weather condition.
► High accuracy with short scanning time can be achieved at an optimal grid size.