Agricultural soil roughness is pertinent to important agricultural phenomena, such as evaporation, infiltration or compression. Monitoring roughness variations would make possible the improvement of tillage operations. In the present work, implementation of the Microsoft Kinect™ RGB-depth camera for dynamic characterization of soil micro-relief is proposed and discussed. The metrological performance and the effect of the operating conditions on three-dimensional reconstruction was analyzed considering both laboratory tests on calibrated reference surfaces and field tests on different agricultural soil surfaces. Data set analysis was made on the basis of surface roughness parameters, as defined by ISO 25178 (2012) series: average roughness, root mean square roughness, skewness and kurtosis. Correlation between different tillage conditions and roughness parameters describing soil morphology was finally discussed

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Kinect is the de facto standard for real-time depth sensing and motion capture cameras. The sensor is here proposed for exploiting body tracking during driving operations. The motion capture system was developed taking advantage of the Microsoft software development kit (SDK), and implemented for real-time monitoring of body movements of a beginner and an expert tractor drivers, on different tracks (straight and with curves) and with different driving conditions (manual and assisted steering). Tests show how analyses can be done not only in terms of absolute movements, but also in terms of relative shifts, allowing for quantification of angular displacements or rotations.