Using digital images obtained from an unmanned aerial vehicle for evaluating productivity and soil deformation of mechanized harvesting equipment

In this study, it was aimed to evaluate mechanized harvesting equipment in terms of productivity and soil deformation by using digital images obtained with an Unmanned Aerial Vehicle (UAV). During the solution phase, high-resolution digital images were obtained for the harvesting machines (harvester, skyline system, farm tractor, loader) with UAV and then productivity analysis was performed with time analysis measurements to be carried out on the images in the office. In the study, the effects of some parameters (product length, product diameter, number of pieces, volume, skidding distance) on the productive machine time and productivity of harvesting machines were determined by statistical analysis. On the other hand, a productivity estimation model was developed for the harvesting machines by using the Weibull distribution, one of the logarithmic models. The rut depths and volumetric soil deformation formed during the skidding of logs with the agricultural tractor were calculated using high-resolution UAV images. At this stage, rut depths were also determined by manual method and the results were compared with the results obtained by UAV. In the study, soil samples were taken along the skidding road and bulk density, hygroscopic moisture, soil texture and soil organic matter content were examined at three depth levels (0-5 cm, 5-10 cm and 10-15 cm) for different number of turns (10 - 20) and land slopes (0-10% and 10-20%). According to the results, the average productivity for the harvester was found to be 40.123 m3/hour and it was determined that the factors affecting the productivity were product diameter and product volume. In the skyline method, the average productivity 11.756 m3/hour and the factors affecting the productivity were product diameter, product length and product volume. In the method of harvesting with an agricultural tractor, the average productivity was found to be 5.671 m3/hour and the product diameter, length and volume were effective on the productivity. The results showed that the average productivity for the loader was 22,567 m3/hour, and the effective factors on the productivity were product diameter and volume. The volume estimation models developed using the Weibull distribution were suitable for the mechanical equipment. The volumetric deformation occurring during tractor skidding, measured by UAV method, increased by 0.052 m3/m in the 20th turn compared to the 10th. In the study, it was determined that after the 20th turn, the average rut depth increased by 4.88 cm according to UAV method and by 4.69 cm according to manual method with a ruler, compared to the 10th. According to the analyzes carried out on soil samples taken from the study area, it was determined that the volumetric weight, hygroscopic moisture and organic matter amount in the study area varied depending on the number of tours.