International Journal of Civil Engineering and Technology (IJCIET) Volume 9, Issue 5, May 2018, pp. 105–113, Article ID: IJCIET_09_05_013 Available online at http://iaeme.com/Home/issue/IJCIET?Volume=9&Issue=5 ISSN Print: 0976-6308 and ISSN Online: 0976-6316
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DIFFERENTIAL SYNTHETIC APERTURE RADAR INTERFEROMETRY FOR LAND MOVEMENTS MAPPING CASE OF EL JEBHA (NORTH OF MOROCCO)
Soukaina MEZIANE, Lahcen BAHI, Latifa OUADIF L3GIE Laboratory, Mohammadia Engineering School, Mohammed V University, Rabat, Morocco
ABSTRACT An analysis of land movements is presented using remote sensing data through applying Differential Synthetic Aperture Radar Interferometry Processing (DInsAR).The method used is based on the DinSAR detection of ground subsidence. In this paper, the study focuses El Jebha area (North of Morocco) where occurs land instability because of the conjunction of several factors triggering landslides such as heavy rainfall, saturated soil, heterogeneous lithology with marl and clay soil especially in overlapping fractures and along feeder roads. The DInSAR method computes the displacement between two date’s single look complex IW acquisition of 05 November 2016 and 05 March 2017 acquired from Sentinel-1A satellite. The produced ground deformation maps allow detecting land subsidence and measure vertical displacements reaching up to 50 cm and uplift to -54cm in the observed time interval. The process applications are Sentinels Application Platform (SNAP) software and SNAPHU for unwrapping processing. DInSAR results with rain, geotechnics and geologic data explain the impact of natural and human activities on land movements. Key words: Mapping, Land Movements, Aperture Radar, El Jebha, Morocco Cite this Article: Soukaina MEZIANE, Lahcen BAHI, Latifa OUADIF, Differential Synthetic Aperture Radar Interferometry for Land Movements Mapping Case of El Jebha (North of Morocco), International Journal of Civil Engineering and Technology, 9(5), 2018, pp. 105–113. http://iaeme.com/Home/issue/IJCIET?Volume=9&Issue=5
1. INTRODUCTION El Jebha is located in northern Morocco on the Rif’s chain on its Mediterranean facade. It is a fragile area and vulnerable to land movements. Several studies show that this zone does not miss problems of instabilities and this because of several triggers [1-12]. There are a number of methods for mapping with GIS methods for vulnerable area to landslides and land movements in Mediterranean basins [13-15]. In parallel, several studies focused on DInSAR methods from the algorithm development to its direct application on determining
http://iaeme.com/Home/journal/IJCIET 105 [email protected] Differential Synthetic Aperture Radar Interferometry for Land Movements Mapping Case of El Jebha (North of Morocco) displacements of the Earth ground. Among DInSAR algorithms figures Persistent Scatterers Interferometry (PSI) [16-19] and Small Baseline techniques [20]. This article discusses the ground deformation in El Jebha using Synthetic Aperture Radar (SAR). This Differential interferometric SAR is based on processing two single look complex interferometric wide images (SLC IW). Each pixel of SAR data contains a complex number (amplitude and phase) of the microwave field backscattered, which corresponds to resolution cell, projected on the ground [21]. In fact, through TOPS coregistration process and phase unwrapping, interferometric analysis allows obtaining land subsidence. This paper presents ground deformations mapping in El Jebha, in order to monitor these areas and to help strengthen them especially if it presents risks of human and material damage.
2. DESCRIPTION OF AREA STUDY El Jebha is located in the Northern Internal Rif. This zone is composed of three geological layers. Indeed, the layer of ghomarids rests in abnormal contact on the metamorphic substratum of the sheet of the Sebtides in the West. This substratum is composed mainly of peridotites surrounded by gneiss, mechachists and sericitoschists associated with sericitous quartzites and cipolins. These series end locally with metamorphic dolomites of the Triassic. While in the East, it is limited by the domain of flysches to the tablecloth Tisirene (According to the geological map of El Jebha).
Figure 1 Extract of trust map of Rif chain El Jebha has a Mediterranean climate characterized by heavy rainfall. Maximum rainfall is in November and December, while July and August are dry months, with thunderstorms on the top. These rains can be continuous, with torrential rains [8]. They feed the highly fractured and weakened soil, causing infiltration of water to marl, marl-calcareous and clay formations. Due to the importance of precipitation [22], the imperviousness of the ground cover and the mountainous character makes that the runoff is relatively important in this zone and that the streams have irregular regimes characterized by a torrential flow in periods of floods. In addition, there is discordance in the stratigraphy marked by steep slopes and heterogeneous and contrasted lithology, especially in faults (figure1). There are N40-N50 oriented fractures with the most dominant to the crossover faults associated with the N60-N80 direction of the
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Jebha-Chrafate fault [22]. Road improvements and quarrying on hillsides often lead to a break in the natural slope. They can also constitute corridors of circulation and infiltration of water. They modify the surface runoff and destabilize the slopes.
3. DATA AND METHODS 3.1. Satellite Data Sentinel-1 is a satellite for Earth observation developed by the European Space Agency [23] as part of the Copernicus program. The first satellite Sentinel-1A is into orbit in 03 April 2014 and the Sentinel-1B in 25 April 2016 in order to take over the ENVISAT and ERS missions. Each satellite carries a payload constituted by the synthetic aperture radar operating in C-band (wavelength 5.6 cm) which provides views with a resolution of up to 5 meters [23]. Compared to other SAR missions, Sentinel-1 provides short revisit time (Sentinel-1A with twelve days and six days with Sentinel-1B). The InSAR uses complex single look image, which is a digital SAR image, composed by columns and rows of small elements pixels forming a two-dimensional array [23]. Each pixel corresponds to cell resolution associated with a small area of the Earth’s surface. Each image has different rows and columns associated respectively with different azimuth locations and different slant range locations (also named Line of Sight direction LOS) [23]. The resolution cell coordinates in azimuth and slant-range depend only on the SAR system characteristics. In addition, the satellite supports four different operational imaging modes (Interferometric Wide swath (IW) mode, Extra Wide swath (EW) mode, Strip-Map (SM) mode, and Wave (WV) mode [23]. In this study, two single look complex Sentinel-1A TOPS mode Interferometric data in Single polarization IW mode for November 05th 2016 and March 5th 2017 are downloaded from Sentinels Scientific Data Hub (Table 1) and are processed with SNAP –S1TBX (Sentinel Application Platform –Sentinel 1 Toolbox) software [24] and with SNAPHU processing for unwrapping [25]. Figure 2 and 3 show the localization of El Jebha in footprint images and in SLC 20170503 Sentinel-1A image.
Table 1 Data sets summary Acquisition Processing Orbit Sensor Stack Polarisation Date type Direction 05 nov2016 Sentinel1-A C Master VV Ascending 05march 2017 Sentinel1-A C Slave VV Ascending
Figure 2 Footprints of 03March 2017 and 05November 2016 SLC IW Sentinel-1A images
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Figure 3 SLC Image of 2017-05-03 Sentinel-1A
3.2. Sentinel-1 TOPS Interferometric Processing DinSAR process includes several steps since the TOPS coregistration of images into a stack and the interferogram formation to phase filtering (earth flatting, topographic phase removal, Goldstein filter). Once unwrapping phase is computed, the phase is converted to displacement, which is geocoded and converted to (.kmz) format for visualizing map deformation on Google Earth. DInSAR method [26] proposes to observe deformation in El Jebha. Interferometric SAR derives the phase difference based on two images of Sentinel -1 observations taken between 05 November 2016 and 05 March 2017. According to the processing of interferometric SAR, those images are coregistered into a stack. Before coregistration, InSAR stack overview determines 05 November 2016 as master image and 05 march 2017 as slave image. Coregistration is essential for accurate determination of difference phases. Phase φ has the following linear dependence on the slant range coordinate r where λ is the SAR wavelength [26] (1) Considering that the phase of the transmitted signal is zero [26], the received signal that covers the distance 2R travelling from the satellite to the target and back is: radians (2)
The SAR interferogram is complex multiplication of coregistrated SAR images. It is generated by cross-multiplying the master SAR image pixel with the complex conjugate pixel of the slave [26]. Thus, the interferogram amplitude is the amplitude of the first image multiplied by that of the second one, whereas its phase is the difference between the acquisitions. The interferometric phase variation ΔΦ is then proportional to ΔR divided by the transmitted wavelength λ.
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(3) In case that some of point scatterers on the ground slightly change their relative position in the time interval between two SAR observations , then the following additive phase term, independent of the baseline, appears in the interferometric phase [26] (4)
Where λ is the transmitted wavelength and d is the relative scatterer displacement projected on the slant range direction (LOS displacement). If a digital elevation model DEM (SRTM 3-arc-second) is available, it can be used in this case and which the height reference datum was transformed from a geoid datum into an ellipsoidal datum (WGS 84) [27] Finally, Goldstein filter [28] is used for interferogram flattening, phase calibration, phase simulation and geocoding and for noise reduction. The interferogram filtered provides wrapping measurement of the relative terrain altitude due to the 2π cyclic nature of the interferometric phase. Therefore, the phase can be any value + n 2 with n is an integer [26]. The filtered interferogram is further unwrapped by way of the triangulation based minimum cost flow method using SNAPHU processing [25]. Therefore, the interferogram phase is restricted to [- ;]. In addition, all pixels with coherence lower than a threshold of 0.6 were masked. After phase filtering and using the precise baseline information, the unwrapped interferogram generated a height map by computing vertical displacement from the equation (4) (5)
Interferometric Processing •Coregistra on •Interferogram forma on •Phase ltering •Phase unwrapping •Phase to height conversion •Geocoding
Input Output •20161105 (master) •Map deforma on •20170305(slave)
Figure 4 DinSAR Processing In the final step, the height map is geocoded from Range-Doppler-Coordinates to Geographic Coordinates referred to the geodetic coordinate system relative to the WGS84
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4. RESULTS AND DISCUSSION 4.1. Interferogram Formation and Coherence Map After Coregistration 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. Pixels of high coherence appear bright whereas pixels with poor coherence appears dark (Figure 5a). The high coherence between master and slave images allow to produce Digital Elevation Model DEM. Loss of coherence can produce poor interferometric results. Interferometric fringes represent a full 2π cycle. Fringes appear on an interferogram as cycles of arbitrary colors, with each cycle representing half the sensor’s wavelength. Relative ground movement between two points can be calculated by counting the fringes and multiplying by half of the wavelength (Figure 5b).
Figure 5 a. coherence map and b. Interferogram generated between 05 Nov 2016 and 05 March 2017 in El Jebha
4.2. Deformation Map
Figure 6 Vertical displacement map of El Jebha between 05 November 2016 and 05 March 2017 (a. coherence up to 0.6 and b. coherence map from 0 to 0.6)
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SAR images of Sentinel-1A processed by SNAP generate LOS deformation maps of El Jebha between 05 November 2016 and 05 March 2017. The process into SNAPHU [25] developed at Stanford university, processing before phase filtering, phase unwrapping is a key step during the signal processing of interferometric synthetic aperture radar (InSAR) data. The result visualized in SNAP [24] is given in figure 5. The figure 6.a displays only coherence up to 0.6 whereas figure 6.b displays all pixels. The deformation map (Figure 7) from November 2016 (Early precipitations) to March 2017 shows that El Jebha area has known only subsidence. In fact, good coherence pixels proves that on the ravines, the embankments of steep slope of the reliefs and long road of the bypass and feeder roads, deformation is between -50.5 cm and -32.81 cm and while deformation is -2.00 cm -3.20cm on the average slopes and lower -3.20 cm on the low slopes. In addition, outside study area especially on the limestone dorsal, uplift is between 26 cm to 56 cm due to important ground movements of the limestone dorsal resulted in the deposit of materials obtained during winter periods and flood periods.
Figure 7 Displacement map of El Jebha between 05 November 2016 and 05 March 2017 visualized on Google Earth
5. CONCLUSIONS This paper proves that InSAR data allows identifying land movements. Applying DInSAR in El Jebha is effective because it allows to analyze and to map ground deformation in remote area freely. Exploiting phase differentiating using Sentinel-1 toolbox SNAP and SNAPHU for unwrapping phase, this process is useful and gives satisfactory results even if it is based on two SLC images to finally get deformation map visualized in Google Earth. Other advanced process is possible for refining results and use multiple data acquisitions. The DInSAR method is applied in this paper and proves that El Jebha is vulnerable area because of soil fracturing and the soft geotechnical nature with high precipitation. Weak cohesion (soil generally composed of alterations and colluviums) show that the infiltration of water along with fractures and some geological formations in addition to anthropogenic factors (roads and quarries), deep pore pressures increase, reducing the shear strength of formations with poor mechanical characteristics. Once they reach saturation, it engenders a plastic behavior in the presence of water triggering landslides.
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