## 1 Introduction  
Landslides represent one of the most diffuse and problematic natural hazards in many mountain chains of the world [1]. In many countries, landslides are responsible for large economic losses, damages to houses and infrastructures and fatalities [1, 2]. They are common morphological features throughout the whole Northern Apennines of Italy. Here, most slope deformations occur on old landslide bodies that already failed in the past [3] and continue to exhibit repeated partial or complete reactivations. In many cases, the reactivation of old deposits causes the regression of the main scrap and the physical degradation of the material, which moves downwards as an earthflow. In other cases, the reactivation is more complex and different types of landslides may be present on the same slope [4]. In this context, accurate landslide mapping and detection are important for a correct hazard assessment. Conventional methods used for mapping and monitoring slope instabilities could benefit from remote sensing systems, which allow rapid and easily updatable acquisitions of data over wide areas, reducing fieldwork and costs [5, 6, 7]. A powerful technique for the displacements monitoring of large areas is the synthetic aperture radar interferometry (InSAR, DInSAR) that can measure the deformations of the landslide deposits during the slow-motion stage [8]. Radar interferometry has been successfully used to assess subsidence [9], volcanic inflation or deflation [10], and the deformation field of earthquakes [11, 12]. It was also applied to detect the deformation caused by landslides [13, 14] as well as subsurface excavation and tunneling [15]. The first application of radar interferometry to a landslide investigation dates back to the mid-1990s [16]. However, it was only in the following decade that this technique attracted the attention of the landslide community. Recent advances in radar satellite capabilities (e.g., high spatial resolution and high temporal frequency acquisitions), together with the development of new robust techniques based on the interferometric analysis of large datasets of radar images (multi-interferogram approach), such as the permanent scatterers (PS) [17] or the small baseline technique (SBAS) [18], have increased the potential of remote sensing for landslide investigations. One of the main limitations of multitemporal techniques is the absence of stable reflectors on most active landslides, making them difficult to apply in many critical cases. Traditional two-pass InSAR allows the detection of slow-moving landslides up to several cm per year, following the classifications of [PERSON], 1996 [19], and was successfully used to investigate the seasonal kinematics of earthflows in California [14; 15; 16; 17; 18; 19; 20]. However, before 2015 only L-band data delivered spatially quasi-continuous data in settings like the Northern Apennines. Different InSAR techniques were used in the past to retrieve spatial and temporal displacement of slow slope deformations [13; 20; 21; 22]. The launch of the new Sentinel 1 satellite constellation, which is characterized by a high acquisition frequency of up to six days, is suited to reduce decorrelation in the derived interferograms [23; 24] and permits obtaining promising results with higher temporal resolution [25]. This paper investigates the temporal evolution of surface displacements in a mountainous area characterized by widespread landslides using standard two-pass InSAR analysis. The study area is located in the Northern Apennines of Italy, has an extent of 60 km\({}^{2}\), and during the 4 years of analysis (from January 2016 to December 2019), was subject to the reactivation of three existing landslides caused by intense rainfall. We used an areal InSAR analysis to detect active slope movements during the period of interest. Then we used a local analysis to investigate the relationship between rainfall and landslides acceleration events.