scholarly journals OPTIMUM CONDITIONS FOR DIFFERENTIAL SAR INTERFEROMETRY TECHNIQUE TO ESTIMATE HIMALAYAN GLACIER VELOCITY

2018 ◽  
Vol IV-5 ◽  
pp. 137-140 ◽  
Author(s):  
B. R. Nela ◽  
G. Singh ◽  
A. V. Kulkarni ◽  
K. Malik
Keyword(s):  
Displacement Component ◽  
Sar Interferometry ◽  
Srtm Dem ◽  
Optimum Conditions ◽  
Topographic Information ◽  
Chhota Shigri Glacier ◽  
Measuring Surface ◽  
L Band ◽  
Glacier Velocity ◽  
Differential Sar Interferometry

<p><strong>Abstract.</strong> Differential SAR Interferometry (DInSAR) is the process of differencing two Interferograms for measuring surface movement with an accuracy of millimeter range. The DInSAR process can be applied to observe glacier movement, earthquake deformations, volcanic activities and rate of subsidence or uplift caused due to the extraction of groundwater or coal. By using single pass interferometry technique we can also generate accurate DEM. In this paper, we are presenting the movement of a Chhota Shigri glacier with the help two pass DInSAR technique and mainly we concentrated on the optimum conditions for estimating glacier movement using DInSAR. We got good coherence and Interferogram fringes for L-band sensor with less temporal baseline. Therefore, we generated glacier velocity using ALOS-2 data with 14 days temporal baseline. Initially, we generated Interferogram (defo-pair) by taking 10th March 2015 image as a master and 24th March 2015 image as a slave. But this generated Interferogram also having topographic information and atmospheric errors with the displacement component. Therefore, we used SRTM DEM for removing topographic information from the Interferogram. Because we are using L-band data, results may not be affected by troposphere. Maximum glacier velocity we observed in the accumulation zone as 7.285<span class="thinspace"></span>cm/day in the month of March and while it’s moving towards ablation zone the glacier velocity is decreasing.</p>

scholarly journals Comment on “Study of Systematic Bias in Measuring Surface Deformation With SAR Interferometry” by Ansari et al. (2021)

2021 ◽  
Author(s):  
Claudio De Luca ◽  
Francesco Casu ◽  
Michele Manunta ◽  
Giovanni Onorato ◽  
Riccardo Lanari
Keyword(s):  
Surface Deformation ◽  
Sar Interferometry ◽  
Systematic Bias ◽  
Phase Errors ◽  
Measuring Surface ◽  
Systematic Biases ◽  
Small Baseline ◽  
Differential Sar Interferometry ◽  
Long Baselines ◽  
Baseline Approach

<p>In a recent publication Ansari et al. (2021) [1] claim (see, in particular, the Discussion and Recommendation Section in their article) that the advanced differential SAR interferometry (InSAR) algorithms for surface deformation retrieval, based on the small baseline approach, are affected by systematic biases in the generated InSAR products. Therefore, to avoid such biases, they recommend a strategy primarily focused on excluding “the short temporal baseline interferograms and using long baselines to decrease the overall phase errors”. In particular, among various techniques, Ansari et al. (2021) [1] identify the solution presented by Manunta et al. (2019) [2] as a small baseline advanced InSAR processing approach where the presence of the above-mentioned biases (referred to as a fading signal) compromises the accuracy of the retrieved InSAR deformation products. We show that the claim of Ansari et al. (2021) [1] is not correct (at least) for what concerns the mentioned approach discussed by Manunta et al. (2019) [2]. In particular, by processing the Sentinel-1 dataset relevant to the same area in Sicily (southern Italy) investigated by Ansari et al. (2021) [1], we demonstrate that the generated InSAR products do not show any significant bias.</p>

scholarly journals Comment on “Study of Systematic Bias in Measuring Surface Deformation With SAR Interferometry” by Ansari et al. (2021)

2021 ◽  
Author(s):  
Claudio De Luca ◽  
Francesco Casu ◽  
Michele Manunta ◽  
Giovanni Onorato ◽  
Riccardo Lanari
Keyword(s):  
Surface Deformation ◽  
Sar Interferometry ◽  
Systematic Bias ◽  
Phase Errors ◽  
Measuring Surface ◽  
Systematic Biases ◽  
Small Baseline ◽  
Differential Sar Interferometry ◽  
Long Baselines ◽  
Baseline Approach

<p>In a recent publication Ansari et al. (2021) [1] claim (see, in particular, the Discussion and Recommendation Section in their article) that the advanced differential SAR interferometry (InSAR) algorithms for surface deformation retrieval, based on the small baseline approach, are affected by systematic biases in the generated InSAR products. Therefore, to avoid such biases, they recommend a strategy primarily focused on excluding “the short temporal baseline interferograms and using long baselines to decrease the overall phase errors”. In particular, among various techniques, Ansari et al. (2021) [1] identify the solution presented by Manunta et al. (2019) [2] as a small baseline advanced InSAR processing approach where the presence of the above-mentioned biases (referred to as a fading signal) compromises the accuracy of the retrieved InSAR deformation products. We show that the claim of Ansari et al. (2021) [1] is not correct (at least) for what concerns the mentioned approach discussed by Manunta et al. (2019) [2]. In particular, by processing the Sentinel-1 dataset relevant to the same area in Sicily (southern Italy) investigated by Ansari et al. (2021) [1], we demonstrate that the generated InSAR products do not show any significant bias.</p>

scholarly journals Spaceborne Differential SAR Interferometry: Data Analysis Tools for Deformation Measurement

2011 ◽  
Vol 3 (2) ◽  
pp. 305-318 ◽  
Author(s):  
Michele Crosetto ◽  
Oriol Monserrat ◽  
María Cuevas ◽  
Bruno Crippa
Keyword(s):  
Data Analysis ◽  
Deformation Measurement ◽  
Sar Interferometry ◽  
Analysis Tools ◽  
Differential Sar Interferometry

Survey and monitoring of landslide displacements by means of L-band satellite SAR interferometry

Landslides ◽  
2005 ◽  
Vol 2 (3) ◽  
pp. 193-201 ◽  
Author(s):  
Tazio Strozzi ◽  
Paolo Farina ◽  
Alessandro Corsini ◽  
Christian Ambrosi ◽  
Manfred Thüring ◽  
...  
Keyword(s):  
Sar Interferometry ◽  
L Band

Comparative Analysis of Forest Height Retrieval Methods by Polarimetric SAR Interferometry

2013 ◽  
Vol 726-731 ◽  
pp. 4686-4689
Author(s):  
Zhu Bo Zhou ◽  
Hong Zhang Ma ◽  
Xiao Bo Zhu ◽  
Lin Sun
Keyword(s):  
Comparative Analysis ◽  
Difference Method ◽  
Sar Interferometry ◽  
Combined Method ◽  
Polarimetric Sar ◽  
Forest Height ◽  
L Band ◽  
Polarimetric Sar Interferometry ◽  
Combined Methods

The objective of this paper is to compare and analyze the forest height retrieval methods from Polarimetric SAR Interferometry(POLINSAR).Both of the methods based on DEM difference and that on interferometry coherence amplitude are generalized, analyzed, and compared.Also in this paper combined methods of DEM difference and interferometry coherence amplitude are proposed and validated.The ESA fullpolarimetric interferometry L-band data are used for forest height analysis.The results show that the height is severely underestimated using DEM difference method,In constast,interferometry coherence amplitude method has a overest imation of height.The combined method of DEM difference and interferometry coherence amplitude has a much better estimate,closer to the true height than these two methods.

Crustal deformation monitoring of volcanoes in Japan using L-band SAR interferometry

2000 ◽  
pp. 285-288
Author(s):  
Makoto Murakami ◽  
Satoshi Fujiwara ◽  
Takuya Nishimura ◽  
Mikio Tobita ◽  
Hiroyuki Nakagawa ◽  
...  
Keyword(s):  
Crustal Deformation ◽  
Deformation Monitoring ◽  
Sar Interferometry ◽  
L Band
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