ABSTRACT:Masouleh is one of the ancient cities located in a high mountainous area in Gilan province of northern Iran. The region is threatened by a hazardous landslide, which was last activated in 1998, causing 32 dead and 45 injured. Significant temporal decorrelation caused by dense vegetation coverage within the landslide area makes the use of Synthetic Aperture Radar Interferometry (InSAR) for monitoring landslide movement very challenging. In this paper, we investigate the capability of three InSAR time-series techniques for evaluating creep motion on Masouleh landslide. The techniques are Persistent Scatterer Interferometry (PSI), Small BAseline Subset (SBAS) and SqueeSAR. The analysis is done using a dataset of 33 TerraSAR-X images in SpotLight (SL) mode covering a period of 15 months between June 2015 and September 2016. Results show the distinguished capability of SqueeSAR method in comparison to 2 other techniques for assessing landslide movement. The final number of scatterers in the landslide body detected by PSI and SBAS are about 70 and 120 respectively while this increases to about 345 in SqueeSAR. The coherence of interferograms improved by about 37% for SqueeSAR as compared to SBAS. The same rate of displacement was observed in those regions where all the methods were able to detect scatterers. Maximum rates of displacement detected by SqueeSAR technique in the northern edge, older and younger part of the landslide body are about -39, -65 and -22 mm/y, respectively.
ABSTRACT:Due to its special imaging characteristics, Synthetic Aperture Radar (SAR) has become an important source of information for a variety of remote sensing applications dealing with environmental changes. SAR images contain information about both phase and intensity in different polarization modes, making them sensitive to geometrical structure and physical properties of the targets such as dielectric and plant water content. In this study we investigate multi temporal changes occurring to different crop types due to phenological changes using high-resolution TerraSAR-X imagers. The dataset includes 17 dual-polarimetry TSX data acquired from June 2012 to August 2013 in Lorestan province, Iran. Several features are extracted from polarized data and classified using support vector machine (SVM) classifier. Training samples and different features employed in classification are also assessed in the study. Results show a satisfactory accuracy for classification which is about 0.91 in kappa coefficient.
Shabkola is a village located in Mazandaran province of northern Iran that suffers from the mass movement happening in the upstream. Deforestation and changes to land use are the main reasons for the soil instability in this region, which together with steep slope, relatively high precipitation rate and natural erosion has led to such a condition. The area of mass movement is approximately 90 hectares which is a big threat for people living in the region. In this study, we have utilized two different geodetic techniques including InSAR time-series analysis and GPS measurements to assess slope stability in Shabkola. The SAR dataset includes 19 ALOS/PALSAR images spanning from July 2007 to February 2011 while GPS observations are collected in 5 campaigns from September 2011 to May 2014. Displacement as much as approximately 11.7 m in slope direction was detected by GPS observations for the 2011-2014 time period. Most of the slope geometry is in north-south direction, for which the sensitivity of InSAR for displacement detection is low. However, ALOS PALSAR data analysis revealed a previously unknown landslide, covered by dense vegetation in the northern part of main Shabkola landslide, showing line-of-sight velocity of approximately 2cm/year in the time period 2007-2011.
ABSTRACT:The aim of this study is to investigate the effect of various Global Digital Elevation Models (GDEMs) in producing high-resolution topography model using TanDEM-X (TDX) Coregistered Single Look Slant Range Complex (CoSSC) images. We selected an image acquired on Jun 12 th , 2012 over Doroud region in Lorestan, west of Iran and used 4 external digital elevation models in our processing including DLR/ASI X-SAR DEM (SRTM-X, 30m resolution), ASTER GDEM Version 2 (ASTER-GDEMV2, 30m resolution), NASA SRTM Version 4 (SRTM-V4, 90m resolution), and a local photogrammetry-based DEM prepared by National Cartographic Center (NCC DEM, 10m resolution) of Iran. InSAR procedure for DEM generation was repeated four times with each of the four external height references. The quality of each external DEM was initially assessed using ICESat filtered points. Then, the quality of, each TDX-based DEM was assessed using the more precise external DEM selected in the previous step. Results showed that both local (NCC) DEM and SRTM X-band performed the best (RMSE< 9m) for TDX-DEM generation. In contrast, ASTER GDEM v2 and SRTM C-band v4 showed poorer quality.
Coastal communities in deltaic regions worldwide are subject to subsidence through a combination of natural and anthropogenic processes. The city of Karachi in southern Pakistan is situated along the diffuse western boundary of the tectonically active Indian Plate, making it more susceptible to natural subsidence processes from plate motion-related deformational events such as earthquakes and faulting. Karachi has a dense population of over 16 million people, and determining the rate of subsidence and extent of neotectonic activity is crucial for mitigating seismic hazards. Excessive abstraction of groundwater and extensive groundwater use in irrigation are some of the anthropogenic contributions to subsidence in the area. A combination of the lack of historical data and few previous studies of the area make it difficult to determine the rate and extent of deformation in this region. We present an analysis of subsidence and neotectonic activity in Karachi and its surrounding areas using Interferometric Synthetic Aperture Radar (InSAR) timeseries techniques. The InSAR results for satellite LOS velocity change in both ascending and descending Sentinel-1 tracks indicate subsidence in key residential and industrial areas. Further decomposition into two dimensions (east–west and vertical) quantifies subsidence in these areas up to 1.7 cm per year. Furthermore, InSAR data suggest the presence of an active north–east dipping listric normal fault in North Karachi that is confirmed in the shallow subsurface by a 2D seismic line. Subsidence is known to cause the reactivation of faults, which increases the risk of damage to infrastructure.
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