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Effect of open soil surface patterns on soil detectability based on optical remote sensing data
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1  V. V. Dokuchaev Soil Science Institute
2  Agrarian-Technological Institute of RUDN University

Published: 22 March 2018 by MDPI in 2nd International Electronic Conference on Remote Sensing session Applications

Arable soils are subjected to altering influence of agricultural and natural processes determining surface feedback patterns (spatial arrangement, distribution and manifestation of surface structure elements) therefore affecting their ability to reflect light. However remote soil mapping and monitoring usually ignore information on surface state at the time of spectral data acquisition. Conducted research demonstrates the contribution of seasonal surface feedback dynamics to soil reflectance and its relationship with soil properties.

Research area is comprised of 4 test sites located in Saratovskaya and Tulskaya oblasts of Russia.

Analysis of variance showed that even at a sample level surface patterns significantly affect soil spectral features accounting for 71 % of their variation (Pillai’s trace=0.71, F=2.37, p=0.03, partial eta squared=0.71). The effect of surface smoothing on the relationships between soil reflectance and its properties varies. In case of organic matter and medium and coarse sand particles correlation decreases with the destruction of surface patterns. For particles of fine sand and coarse silt, homogenization changes the spectral areas of high correlation. Partial least squares regression models also demonstrated the variations in complexity, R2cv and RMSEPcv.

Two-year field research showed that on arable lands seasonal surface feedback dynamics causes 22-46 % of soil spectral variations depending on the growing season and soil types represented on the test plots. Tillage interference adds up to the impact of seasonality. The directions and areas of spectral changes seem to be soil-specific.

Therefore, surface feedback patterns should be considered when modelling soil properties on the basis of remotely measured spectral data to ensure stable, reliable and reproducible results.

Keywords: remote sensing, digital soil mapping, spectral reflectance, surface feedback
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