UAV-based monitoring of residual plastic film pollution in cotton fields before sowing with AIC-UNet

This study optimizes UAV sampling methods and path planning, and constructs the AIC-UNet (Improved ASPP-InceptionV4-CBAM UNet) model to mitigate the interference of illuminance variations with residual plastic film (RPF) extraction from cotton field images. This achieves rapid and automatic monitoring of RPF pollution in pre-sowing cotton fields. Current research faces challenges such as low RPF extraction accuracy, poor alignment between the UAV sampling range and the plot boundaries, and low path planning efficiency. To tackle these challenges, this study optimizes the UAV sampling process and innovatively proposes an RPF extraction model. Firstly, this study designs a UAV adaptive sampling method by combining the geometric center-based radiation method and the Held-Karp algorithm. This achieves dynamic adjustment of sampling intervals and accurate matching with plot boundaries, providing high-quality image samples for AIC-UNet modeling. Then, this study constructs the AIC-UNet model that integrates the improved ASPP, CBAM, and InceptionV4 structure to efficiently extract RPF features under complex illuminance conditions. The results show that the proposed scheme not only enhances RPF pollution assessment accuracy under different illuminance conditions but also significantly enhances the monitoring efficiency and practicality. The AIC-UNet achieves a mIoU of 88.59% for RPF extraction under different illuminance conditions, and the R 2 reaches 0.968 in the linear fitting with manually labelled values. Additionally, the average UAV sampling path planning time is only 0.06963 s, and the average D (superiority degree of the path) reaches 100%, significantly enhancing the efficiency of RPF monitoring. This study provides technical support for farmland RPF pollution assessment and contributes to sustainable agricultural development. • A multi-illumination environmental dataset was created via UAV low-altitude imaging. • Geometric-center radiation sampling was used for adaptive UAV sampling tuning. • Held-Karp was used for rapid planning of the shortest UAV sampling path. • AIC-UNet was proposed for residual film recognition and image segmentation. • Technical support was provided for sustainable agriculture development.