###### Abstract  
During the interferometric synthetic aperture radar (InSAR)-based ground displacement monitoring in mining areas, the overlying land is mainly covered by low vegetation and arable land, which makes interferograms acquired by InSAR techniques easily susceptible to decorrelation, resulting in the quantity and density of highly coherent points (CPs) are not enough to reflect the spatial location and spatio-temporal evolution process of ground displacement, which is hardly meeting requirements of high-precision ground displacement monitoring. In this study, we developed an approach for monitoring ground displacement in mining areas by integrating Persistent Scatterer (PS), Slowly Decoherent Filtering Phase (SDF), and Distributed Scatterer (DS) based on signal-to-noise ratio (SNR) to increase the spatial density of CPs. A case study based on a mining area in Heze was carried out to verify the reliability and feasibility of the proposed method in practical applications. Results showed that there were four significant displacement areas in the study area and the quantity of CPs acquired by the proposed method was maximum 6.7 times that of conventional PS-InSAR technique and maximum 2.3 times that of SBAS-InSAR technique. The density of CPs acquired by the proposed method increased significantly. The acquired ground displacement information of the study area was presented in more detail. Moreover, the monitoring results were highly consistent with ground displacement results extracted by PS-InSAR and SBAS-InSAR methods in terms of displacement trends and magnitudes. ground displacement in coal mining areas; time series InSAR; high coherence point target; distributed scatterer; Yuncheng county in Shandong province +
Footnote †: journal: Applied sciences  
already more than 20,000 km\({}^{2}\) by 2020, and, thus, will destroy the natural terrain and cause serious damage to the ecological environment, such as land resources, water resources, and atmosphere in the mining area, as well as houses, railways, roads, bridges, and other structures around the displacement area [3,4]. Hence, accurate monitoring of surface deformation in mining areas and adopting control measures are essential to prevent mining subsidence disasters in the coal mines [5,6]. Traditional ground displacement monitoring techniques in coal mining areas include level measurement, trigonometric leveling, and global navigation satellite system (GNSS) measurement [7]. Although the accuracy of those monitoring methods is relatively high, their spatial resolution is limited by the quantity and distribution of the monitoring points. This makes them more suitable for high-precision ground displacement monitoring than for reflecting the overall characteristics of the ground displacement in large-scale, large-span coal mining areas [8,9]. Synthetic Aperture Radar Interferometry (InSAR) can effectively offset the shortcomings of traditional ground displacement monitoring techniques by extracting the phase difference between two SAR images taken from the same area at different times, is a powerful technique for monitoring ground displacement in coal mining areas with wide coverage and high precision in all weather conditions [10,11]. The time series InSAR technologies represented by Persistent Scatterer (PS)-InSAR and Small Baseline Subsets (SBAS)-InSAR use the phase values of high coherence pixel points which are influenced slightly by space-time decoherence and show relatively stable scattering properties in synthetic aperture radar (SAR) images as the time series analysis object, can be used for long-term ground displacement monitoring in mining areas [12,13]. Nevertheless, it is difficult for the conventional time series InSAR technique to obtain enough uniformly distributed high CPs in the mining areas and surrounding surfaces which are usually covered by vegetation or bare lands [14].