Abstract
In the past few years, SAR Interferometry specially InSAR and D-InSAR were extensively used for deformation monitoring related applications. Due to temporal and spatial decorrelation in dense vegetated areas, effectiveness of InSAR and D-InSAR observations were always under scrutiny. Multi-temporal InSAR methods are developed in recent times to retrieve the deformation signal from pixels with different scattering characteristics. Presently, two classes of multi-temporal InSAR algorithms are available- Persistent Scatterer (PS) and Small Baseline (SB) methods. This paper discusses the Stanford Method for Persistent Scatterer (StaMPS) based PS-InSAR and the Small Baselines Subset (SBAS) techniques to estimate the surface deformation in Tehri dam reservoir region in Uttarkhand, India. Both PS-InSAR and SBAS approaches used sixteen ENVISAT ASAR C-Band images for generating single master and multiple master interferograms stack respectively and their StaMPS processing resulted in time series 1D-Line of Sight (LOS) mean velocity maps which are indicative of deformation in terms of movement towards and away from the satellites. From 1D LOS velocity maps, localization of landslide is evident along the reservoir rim area which was also investigated in the previous studies. Both PS-InSAR and SBAS effectively extract measurement pixels in the study region, and the general results provided by both approaches show a similar deformation pattern along the Tehri reservoir region. Further, we conclude that StaMPS based PS-InSAR method performs better in terms of extracting more number of measurement pixels and in the estimation of mean Line of Sight (LOS) velocity as compared to SBAS method. It is also proposed to take up a few major landslides area in Uttarakhand for slope stability assessment.
Highlights
Synthetic aperture radar (SAR) is an innovative technology of radar community
In order to overcome the aforementioned limitations of Interferometric SAR (InSAR), time-series interferometric synthetic aperture radar (InSAR) methods are developed in the past to retrieve the deformation signal from pixels with different scattering characteristics
Persistent Scatterer (PS)-InSAR processing using 15 geocoded single master interferograms resulted in more than 12,50,000 PS candidates based on the DA value in each patch with the area being divided into 6 patches which resulted in 19,549 PS pixels
Summary
Synthetic aperture radar (SAR) is an innovative technology of radar community. It is an active microwave remote sensing mechanism which is capable of imaging the earth in all weather conditions and making it valuable for several hazards monitoring application by measuring surface deformation. In order to overcome these limitations, Hooper et al (2007) developed Stanford Method of Persistent Scatterer (StaMPS) approach which uses spatial correlation of interferogram phase in defined neighbourhood to identify phase stable pixels over a period of time even with low amplitude stability which makes the approach capable of detecting PS pixels in non-urban areas. Apart from the PS, a few natural targets such as desert and noncultivated areas, often referred as DS with moderate coherence in few interferometric pairs, can be explored to retrieve the timeseries deformation These targets with moderate phase stability over complete observation period possess high spatial density compared to PS in non-urban areas. It has been observed that time-series of geophysical parameters can be extracted from DS by reducing the decorrelation effect This is achieved by forming interferograms between image pairs with small temporal baselines and a small difference in look angles.
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