According to the historical table of landslides (Table 1), provided by the Road Directorate of Chefchaouen and the laboratory of Studies and Tests, the area that was started in this study is the province of Chefchaouen precisely Eljebha, Derdara, Bab Berred, Stehat and Talambote, These are points limiting the province of Chefchaouen (Figure 1(a)) which is a region located in the centre of the rifaine chain limited in the North by the Mediterranean Sea over a length of 120 km, in the South by the Provinces of Taounate and Sidi Kacem, the East by the Province of Al Hoceima and in the West by the Provinces of Tetouan and Larache with 600 m (Figure 1(b)) of altitude, it is characterized by a great diversity of the soil formed by limestone and siliceous layers.

The Rifaine zone is formed by a geological structuring consisting of quartzite sandstones and dorsal limestones as well as flysch layers. This context is associated with a climate that is both Mediterranean and oceanic, as well as with the active tectonics of over-rection of the Rifaine domain (Figure 2).

According to the “Roads Directorate, Provincial Equipment, Transportation and Logistics Directorate of Chefchaouen”. Several landslides affected the study area (Chefchaouen province) during the period analysed (October 2012-June 2017)—see Table 1—in particular on national road 16 (Figures 3(a)-(d)), these landslides are mainly triggered by the nature of the geology and heavy rainfall

DATA:

The SAR data used in this study are acquired by the Sentinel1- A sensor and are downloaded free of charge from the Copernicus program. The choice of these data is made on several criteria (satellite mission, type of product, acquisition mode, orbit and polarization) as shown in the following table (Table 2).

We have downloaded the Sentinel-1 images from the Copernicus Open Access Hub in Single Aspect Complex (SLC) level 1 mode, with VV or VV-VH polarizations depending on availability at the various test sites, and Wide Interferometric (IW) acquisition mode. SLC products are based on focused SAR data, geo-referenced using orbit and attitude data from the satellite, and provided in oblique range geometry.

The pairs of Sentinel 1 images were chosen according to the landslides (Table 1) Images before and after the event.

Synthetic Aperture Radar (SAR) is a system capable of obtaining complex, high-resolution images from large areas of terrain, usually located on board an orbital or aerial platform, but which can also be used in ground-based deployments (Yerro et al., 2014). D-InSAR, which uses the phase information of 2 SAR images at different times in the same area by satellite-loaded radar sensors and the DEM of this area to monitor surface deformation, is Differential Interferometry Synthetic Aperture Radar monitoring technology (Raucoules et al., 2007; Berardino et al., 2002).

Advanced SAR image processing has proven its ability to detect and map landslides ( Farina et al., 2006, Cascini et al., 2009, Guzzetti et al., 2009, the traditional

two-pass differential InSAR (D-InSAR) technique has been applied for the monitoring of slow landslides of the order of cm∙yr⁻¹ (Catani et al., 2005).

It provides an image, called a differential interferogram, representing the ground motion between acquisitions with centimetric precision and decametric resolution.

It consists of exploiting the phase information contained in complex SAR imagery recorded by one or more sensors by varying an acquisition parameter (date, position and orientation of the radar, frequency, polarity of the transmitted/received wave) according to the desired application (Bamler & Hartl, 1998). Is a reliable method for measuring small movements (1 cm) with high spatial resolution (10 m) over large areas (50 km²)

The interferometric phase between two SAR images includes the following contributions:

Δ ∅ = Δ ∅ flat + Δ ∅ height + Δ ∅ displacement + Δ ∅ atmosphere + Δ ∅ noise (1)

Hence Δ ∅ flat is the contribution of the flat earth phase, Δ ∅ height presents the topography, Δ ∅ displacement the part of the phase that represents the ground deformation along the line of sight, Δ ∅ atmosphere the contribution of the phase caused by the delay of wave propagation in the atmosphere and Δ ∅ noise is the residual noise, the D-InSAR technique aims to eliminate all interferometric contributions except for the displacement contribution. After removal of all these components, only the ground deformation component is presented on the interferogram.

In our study we collected the previous landslide points of the study area, we had a total of seven points since 2012. However, since the present study will be done with Sentinel 1 Radar imagery, we took the points since 2015 which makes the total of points to about 6 Sentinel 1 Radar images (Table 3), in our study we used Differential Radar Interferometry to generate differential interferograms as shown in (Figure 4) these interferograms were filtered using the GOLDSTEIN fitting and using the SNAP toolbox software, the phase unpacking was performed with the SNAPHU software, then the displacement was calculated from the unwrapped interferogram, finally the results were georeferenced using the Doppler terrain correction.

After Co-registration the SLC images, coherence map is computed due to the complex correlation coefficient between two acquisitions. It gives the level similarity of pixels between the slave and master images in a scale from 0 to 1.

The image of coherence of the couple 8 June/26 July 2015 of the point PK140 RN16 around the Eljebha Point and the Bab Berred point is presented in (Figure 5(a)) the values close to 1 presented in white indicate a strong coherence that means that there is no phase noise while the values close to 0 presented in black indicate a weak coherence that means that there is phase noise, The high elevation of the zone is focused on the eastern part of the zone, Eljebha (Figure 5(b)), while that of the Bab berred zone (Figure 5(b)), is focused on the southern part of the zone.

Figure 6(a) presents the coherence image of the pair 9 June and 21 July 2017 in descending orbit with a time baseline of 41 days over the area of interest presented by yellow pointers (Stehat and Talamobte), it is noted that it is a medium coherence image revealing globally medium to high levels of coherence over the entire area of interest. The coherence is almost high in the coherence image covering the date from 29 June to 24 August 2015 (Figure 7(a)), low to medium in the Talambote zone, and high to very high in the Derdara zone (Figure 7(b)).

With regard to the generation of Interferograms, three components of three peers the interferometric phase carries a lot of information about the surface deformation (force and direction of movement) and the location of the surface break. Concerning the mapping of landslides from Sentinel-1 data, it has already been reported that the approach is based on the estimation of vertical displacement. The interferometric fringes represent a complete cycle of 2π. The fringes appear on an interferogram as arbitrary color cycles, each cycle representing half the wavelength of the sensor. The relative ground motion between two points can be calculated by counting the fringes and multiplying them by half the wavelength of the sensor (Meziane et al., 2018).

(Figure 8(a)) shows a differential interferogram generated from Sentinel-1 data, from the 8 June-26 July 2015 couple in Descending orbit, after subtracting all components, namely the atmospheric and residual components and the topography related component, thus the fringes presented show that the ground deformation extends up to 2.75 over the areas of interest (Figure 8(b)). Figure 9(a) shows the descending interferogram of the Stehat and Talambote zone with a time baseline of 51 days it is represented by a color cycle that shows a phase difference of −2.88 to 2.88 (Figure 9(b)) for the derdara talamobte zone, as shown by the interferogram in (Figure 10(a)), with a time baseline of 25 days which shows the coherence of the zone mean in this period from 29 July to 24 August (Figure 10(b)).