A pixel analysis technique and unmanned aircraft system for horizontal displacement in the landslide potential area

Abstract

Abstract Quantitative horizontal displacement in the landslide potential area is necessary for mitigating casualties, property damage, and economic loss. Focusing on a sliding within a deep-seated landslide potential area located in Guanghua area in northern Taiwan, this study employed an unmanned aerial system (UAS) to capture and produce seven high-precision orthomosaics from February 23 to March 26, 2021. Through particle image velocimetry (PIV) method, these orthomosaics were used to assess the two-dimensional land surface displacement in the sliding-movement region. The results revealed substantial displacement in the study region within the monitoring period. The direction of displacement was consistent with the slope aspect in the region. To evaluate the suitability of the proposed model, the coefficient of efficiency was chosen to determine the goodness-of-fit between the observed and calculated two-dimensional displacement in situ land surface displacement extensometer. The result showed that coefficient of efficiency was up to 0.998. In addition, the greatest displacement was observed in the vegetated section located at the bottom of the sliding-movement region. This section also had the highest slope, and its maximum tree-crow displacement exceeded 9 m. PIV facilitated easy identification of the range and boundaries of the sliding area. This noncontact monitoring technique overcame the limitations of single-point displacement assessment, obviating the time-consuming, costly processes involved in conventional monitoring methods. The achieved results obtained by proposed method gave a worthy support for an accurate understanding and evaluation of the landslide processes in the watershed. The technique can also be applied to other critical infrastructure sites, allowing hazard risk reduction.