Discovering spatiotemporal characteristics of the trans-regional harvesting operation using big data of GNSS trajectories in China

Abstract

Trans-regional operation of agricultural machinery is an essential socialized service that can enhance the utilization rate of agricultural machinery and accelerate the progress of grain harvesting. In this paper, we quantitatively analyze the trans-regional operations of the harvesters using massive GNSS (Global Navigation Satellite System) data in China and reveal their spatiotemporal characteristics from the province, city and district perspectives. Trajectory data were collected from 25,763 harvesters during wheat harvesting season between May and June 2021 using the agricultural machinery operation big data system. Using the field road segmentation method for GNSS trajectory and the trans-regional operation judgment method, we calculated the quantity, driving distance, harvesting duration, and harvested area. Following this, we obtained the corresponding figures for each region, including the quantity, harvested area, harvesting duration, and distance of harvesters. To further analyze the flow and reliance on harvesters, we examined these factors at the province, city, and district scales for each respective region.. Our analysis revealed that approximately 57.1% of the harvesters were involved in trans-district operation, covering approximately 80.09 % of the total harvested area by all harvesters. Furthermore, we identified 6 provinces, 82 cities and 588 districts with a significant reliance on nonlocal harvesters. The findings provide valuable insights for the government, agricultural machinery enterprises, and agricultural machinery operators to optimize decision-making and configuration schemes to enhance the overall operational efficiency of harvesters.