Site selection for landslide GNSS monitoring stations using InSAR and UAV photogrammetry with analytical hierarchy process

Abstract

Site selection for global navigation satellite system (GNSS) monitoring stations is the primary task in landslide GNSS monitoring work, and the selected site directly determines the monitoring effect of landslide deformation. Currently, the method for selecting site locations predominantly relies on the manual judgment of geological disaster experts by site inspections, which is experimental and labor-intensive. In this study, we propose an alternative site selection method on GNSS landslide monitoring station aided by interferometric synthetic aperture radar (InSAR) and unmanned aerial vehicle (UAV) photogrammetry methodology. Firstly, InSAR technology is used to obtain historical deformation data of the landslide area as prior information. Then, high-resolution digital surface model (DSM) and digital orthophoto map (DOM) are obtained by using UAV photogrammetric methodology, and relevant site selection criteria such as slope, aspect, surface roughness index, and vegetation index are extracted. Finally, the analytic hierarchy process (AHP) method is applied to evaluate and quantify the suitability of GNSS station site selection at various positions in the landslide area. The suitability of GNSS monitoring station site selection was evaluated in an experimental area located in the Heifangtai landslide in Northwest China’s Gansu province. Seven evenly and reasonably distributed locations with suitability values exceeding 0.67 were recommended as potential sites for the construction of GNSS monitoring stations, which can meet the requirements for their establishment. With less manual intervention, this method provides quantitative and intuitive representation of suitability distribution, which make GNSS site selection more intelligent.