Effects of soil surface roughness on soil processes and remote sensing data interpretation and its measuring techniques - a review

Surface roughness is a very important physical feature of soil, affecting various soil processes and accuracy of remote sensing data interpretation. Thus, there is a need to describe it quantitatively. The main aim of the paper was to show needs and benefits of collecting quantitative information about soil surface roughness which is the most relevant parameter used as an index to predict water and wind erosion. Surface roughness can reduce soil erosion and soil losses even by up to 31%. Thereby, it increases the development of fauna and flora and improves the structure of soil and its biological quality. In the first section of the paper there are presented definitions of soil roughness proposed by different authors. The next section explains how various factors influence soil surface roughness. Then, the categorization of soil surface roughness discussed in literature is presented. The next part of the paper includes information about a role of soil roughness in agricultural, soil science and a hydrology research. Moreover, soil surface roughness plays an important role in a remote sensing of soils. The knowledge of quantitative soil surface roughness allows more accurate interpretation of the soil properties from remote sensing data, because this soil feature can decrease soil spectra even over 70% and makes their analysis difficult. In addition, deepening knowledge about soil roughness will allow more precise conclusions about the amount of reflected shortwave solar radiation indirectly shaping the Earth’s climate. In the final section, the techniques for measuring and indices for describing soil roughness are shown. However, the authors prefer a photogrammetry technique for collecting these data, because it is quick and easy to use, ensuring high resolution and accuracy of data (about 1 mm) and the image processing is currently simplifid as software to process is absolutely affordable.