FiTraM: A model for automated spatial analyses of wheel load, soil stress and wheel pass frequency at field scale

Abstract

Cultivated fields are repeatedly affected by the impacts of agricultural machinery. Because the agricultural machines in use have different masses and sizes, however, the traffic-induced load inputs are unequally distributed across a field. Currently, the knowledge about spatial distributions of the amount of wheel passes, loads and stresses by farm vehicles is limited. To-date, no model exists, that will enable automated mapping of the spatially distributed intensities of field traffic. To close this gap, the Field Traffic Model (FiTraM) was developed. It calculates the tracks of each tyre based on routes, e.g. dGPS-recordings, in spatially explicit forms. Furthermore, the presented model provides spatial information about the distribution of field traffic intensities such as the number of wheel passes, wheel load and stress inputs. It also considers the changes in wheel load, e.g. caused by payload changes during harvest and by lifting attached implements. The functionality of the model will be demonstrated by calculating the wheel loads, mean contact area stresses and wheel pass frequencies by modelling three typical work processes (ploughing, sowing and harvesting) and a validation dataset for analysing spatial deviations during turning manoeuvres. The model is programmed with Python and Open-Source modules in order to provide access for a wide range of users. FiTraM enables the spatial analysis of agricultural traffic within individual fields and is designed to study the real traffic intensities, which has hardly been examined so far.