Determination of Cultivated Area, Field Boundary and Overlapping for A Plowing Operation Using ISO 11783 Communication and D-GNSS Position Data

Abstract

Easily available and detailed area-related information is very valuable for the optimization of crop production processes in terms of, e.g., documentation and invoicing or detection of inefficiencies. The present study dealt with the development of algorithms to gain sophisticated information about different area-related parameters in a preferably automated way. Rear hitch position and wheel-based machine speed were recorded from ISO 11783 communication data during plowing with a mounted reversible moldboard plow. The data were georeferenced using the position information from a low-cost differential global navigation satellite system (D-GNSS) receiver. After the exclusion of non-work sequences from continuous data logs, single cultivated tracks were reconstructed, which represented as a whole the cultivated area of a field. Based on that, the boundary of the field and the included area were automatically detected with a slight overestimation of 1.4%. Different field parts were distinguished and single overlaps between the cultivated tracks were detected, which allowed a distinct assessment of the lateral and headland overlapping (2.05% and 3.96%, respectively). Incomplete information about the work state of the implement was identified as the main challenge to get precise results. With a few adaptions, the used methodology could be transferred to a wide range of mounted implements.

Latest Advances in Sensor Applications in Agriculture

“…Currently, these data are combined with GNSS sensors for site specific management practices, and also due to their reduced price this allows archiving data and operations with position references. The article by Heiß et al [24] is titled "Determination of Cultivated Area, Field Boundary and Overlapping for A Plowing Operation Using ISO 11783 Communication and D-GNSS Position Data". In this study, authors developed an algorithm that deals with georeferenced data recorded during plowing operation in order to calculate different area-related parameters in an automated way.…”

ISOBlue HD: An Open-Source Platform for Collecting Context-Rich Agricultural Machinery Datasets

“…Commercial loggers, backed by their powerful software suites, are favorable choices among researchers for capturing CAN data via the ISOBUS diagnostic port for machine-centric analysis. For instance, a commercial logger was configured in [ 25 ] to log GNSS data, to determine field boundaries for plowing operations. Moreover, three commercial loggers were evaluated in [ 26 ] for their feasibilities in real-time engine speed and load analysis.…”

Development of a Depth Control System Based on Variable-Gain Single-Neuron PID for Rotary Burying of Stubbles

“…A large number of tests showed that the tillage depth could reach more than 15 cm and the burying rate of stubbles was 90%, which met the requirements of the agricultural machinery standard (NY/T499-2013) for rotary tillers (the tillage depth should be greater than 12 cm and the burying rate should be greater than 80%). In light of the complex surface environment in the field, researchers have mainly used inclination sensors [8][9][10], lasers [11][12][13][14], and the global positioning and navigation system (GNSS) [15][16][17][18] to develop measurement methods of field surface data. The inclination sensor can estimate the height change of the field surface through the pitch angle of the vehicle, which is low in cost and easy to develop.…”