Abstract
Soil roughness is one of the most challenging issues in the agricultural domain and plays a crucial role in soil quality. The objective of this research was to develop a computerized method based on stereo vision technique to estimate the roughness formed on the agricultural soils. Additionally, soil till quality was investigated by analyzing the height of plow layers. An image dataset was provided in the real conditions of the field. For determining the soil surface roughness, the elevation of clods obtained from tillage operations was computed using a depth map. This map was obtained by extracting and matching corresponding keypoints as super pixels of images. Regression equations and coefficients of determination between the measured and estimated values indicate that the proposed method has a strong potential for the estimation of soil shallow roughness as an important physical parameter in tillage operations. In addition, peak fitting of tilled layers was applied to the height profile to evaluate the till quality. The results of this suggest that the peak fitting is an effective method of judging tillage quality in the fields.
Highlights
IntroductionIn order to record and analyze the quality of tillage operations, it is important to measure and monitor physical parameters, such as soil aggregate distribution and surface roughness [1]
It takes enormous energy to prepare land for planting in the agriculture sector
Soil surface roughness is mainly caused by two factors: rainfall and tillage operations, when many different tilling machines are used
Summary
In order to record and analyze the quality of tillage operations, it is important to measure and monitor physical parameters, such as soil aggregate distribution and surface roughness [1]. These parameters, which often occur at the soil surface, can be examined more accurately and optimally using recent methods [2,3]. Soil surface roughness is a key parameter which has an important role for understanding and analyzing different soil properties and physical processes which have a direct or indirect relationship with phenomena such as soil erosion, surface water flow movement, agronomy, meteorology, and risk assessment [4]. Soil roughness and soil clods must be considered when evaluating the quality of plowed soil [5]
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