Z Sadeghi; M.J Valadanzouj; M Dehghani
Abstract
Temporal and geometrical decorrelation often prevents SAR conventional interferometry from being an operational tool for surface deformation monitoring. Persistent Scatterer Interferometry (PSI) techniques presented to overcome the limitation of SAR conventional interferometry and use ...
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Temporal and geometrical decorrelation often prevents SAR conventional interferometry from being an operational tool for surface deformation monitoring. Persistent Scatterer Interferometry (PSI) techniques presented to overcome the limitation of SAR conventional interferometry and use amplitude analysis and considering temporal deformation model for PS pixel selection fail to identify PS pixels in rural areas lacking man-made structures. On the other hand, the high subsidence rates lead to not be fulfilled the required condition for unwrapping (Nyquist sampling criterion) and significant phase unwrapping errors in novel PSI algorithm (StaMPS) that applies amplitude analysis as well as phase stability in order to select the PS pixels without using a pre-define deformation model. Therefore, in this paper we present an enhanced algorithm based on PSI in order to estimate deformation rate in rural area undergoing high and nearly constant deformation rate using the available SAR images. The proposed approach integrates the merits of all existing PSI algorithms in PS pixel selection and phase unwrapping. PS pixels are selected based on the amplitude information and phase stability and their phase are compensated for APS and nonlinear deformation contribution by applying temporal filter. Deformation rate is then estimated using LAMBDA method that is a fast and optimal without considering Niquist sampling criterion. The approach was applied to the ENVISAT ASAR images of Southwestern Tehran basin and the results were evaluated with leveling data and the maximum difference rate across the leveling stations was 5 cm/yr demonstrating the high performance of the proposed algorithm in comparison with the obtained results from other interferometry methods. Moreover, the presented algorithm was applied to the simulated data and the value of RMSE was obtained 0.003 m/yr confirming this success.
Y. Rezaei; M. J. Valadan Zoej; F. Vaziri
Abstract
Considering glaciers as a main source of potable water in Iran, their investigations and protection are necessary. It means their parameters such as maximum and minimum altitude, area and perimeter, position of snow line and etc, should be estimated. In a time and expenses point of view, regarding research ...
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Considering glaciers as a main source of potable water in Iran, their investigations and protection are necessary. It means their parameters such as maximum and minimum altitude, area and perimeter, position of snow line and etc, should be estimated. In a time and expenses point of view, regarding research difficulties in these areas when using direct measurements approach and field working, remote sensing technology seems to be useful and efficient. IRS and ASTER satellite images, Arial photographs and DEM, have been used to identify and estimate different glacier parameters of Khersan glacier in the Zardkuh Mountain. Using various unsupervised classification algorithms on Aster images, different parts of glaciers are classified. Feature space and spectral wave of snow and ice have been used to recognize various parts of glacier, such as ice, last years frozen snow as well as frost snow. Ultimately DEM, fused images, information extracted from classification methods, and vision interpretation, have been applied to up to date the old map of the region and extract the boundary of glacier
H. Fattahi; M. J. Valadan Zouj; M. R. Mobasheri; M. Dehghani
Abstract
Interferometric Synthetic Aperture Radar (InSAR) technique using phase information has demonstrated its abilities in topographic mapping and measuring surface deformation with the precision of meter and sub-centimeter, respectively in a very high spatial resolution. However, ...
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Interferometric Synthetic Aperture Radar (InSAR) technique using phase information has demonstrated its abilities in topographic mapping and measuring surface deformation with the precision of meter and sub-centimeter, respectively in a very high spatial resolution. However, various limiting factors such as spatial and temporal decorrelation, atmospheric effects and thermal noise of the radar sensor introduce different types of noise into the interferograms, which makes the phase unwrapping too difficult to obtain the accurate results. In this study, an algorithm for noise suppression is presented based on wavelet transform in the complex domain. The high-frequency data due to the phase jumps is not appeared in the complex domain. Therefore, the wavelet coefficients obtained in the complex domain include mostly the noise. The wavelet coefficients of the noisy interferogram are then filtered using the threshold computed from the related wavelet band. In comparison with the other noise reduction methods such as multi-look processing and those based on Fourier transform in small windows, the proposed algorithm can reduce the noise while keeping the spatial resolution without the need for windowing the interferogram. Quantitative and qualitative evaluations of the results obtained by the new method applied on the simulated and real noisy data show high performance of the wavelet transform in noise reduction.
M. Dehghani; M. J. Valadan Zouj; A. Mansourian
Abstract
study several 2D and 3D math models have been tested in order to correct slant range SAR data geometrically. Some of these models consider the imaging geometry at the time of imaging while the others relate the ground space to the image one by mathematical polynomials. The images used here are 3 ENVISAT ...
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study several 2D and 3D math models have been tested in order to correct slant range SAR data geometrically. Some of these models consider the imaging geometry at the time of imaging while the others relate the ground space to the image one by mathematical polynomials. The images used here are 3 ENVISAT ones of Bam area. In order to extract the 3D GCPs, a topographic map with a scale of 1:25000 and SRTM DEM were used. The 2D math models used in this study include Global polynomial, Point wise, Piece wise and Projective while the 3D models are DLT and Rigorous SAR model. Since the images used in this study were originally ordered for interferometry studies, their baseline is so small that the precision of 3D coordinates extraction is not satisfactory enough. However, the results of 2D models are much better.
