Remote Sensing Identification and Hazard Assessment Methods for Spoil Sites

Abstract Spoil sites, as loose accumulations, are prone to instability after disturbances and are a serious threat to the safety of downstream communities. Currently, research on the hazard assessment of regional spoil sites is relatively limited. This study aims to develop an integrated approach that combines spatial, aerial, and ground techniques to rapidly identify and assessment the hazard of spoil sites. Using remote sensing and airborne LiDAR, spoil sites within the region are identified and key factors influencing their stability are appropriately interpreted. Subsequently, based on the numerical simulation results obtained via the material point method, a hazard assessment methodology for spoil sites is proposed, which combines the slope safety factor method with the analytical hierarchy process. The proposed method is applied and validated on a spoil site along an expressway in Guizhou, China. The achieved results reveal that remote sensing combined with unmanned aerial vehicle (UAV) verification technology is capable of quickly and accurately identifying spoil sites and accurately interpreting their critical elements. The hazard assessment of the spoil site is represented by the hazard coefficient (P), where 0 < P < 1 indicates safety, 1 ≤ P < 5 signifies instability, and P ≥ 5 represents extreme instability. The effectiveness of the proposed assessment approach is then verified through the on-site validation, which provides a vital reference for rapid identification and batch assessment of spoil sites.