Effect of Phase Filtering on Interferometry based Displacement Analysis of Cultural Heritage Sites

Tripathi, Akshar; Kumar, Shashi

doi:10.1109/upcon.2018.8597027

Cited by 8 publications

(4 citation statements)

References 25 publications

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“…Noise can occur due to temporal decorrelation, geometric decorrelation, volume scattering, and processing error. The Goldstein filter is used to eliminate or partially reduce the influence of the phase noise effect [20][21][22][23][24]. To generate an interferogram in the GTMSAR package, we need to run the script "p2p_S1_TOPS_Frame.csh", the command line looks like this for the first pair of the VV polarization interferogram for July 18 and July 30, 2020.…”

Section: Radar Image Processingmentioning

confidence: 99%

Determination of the Earthquake Epicenter from Line-of-Sight Displacement Images Obtained by Sentinel-1A/B Radar Data Using the GMTSAR Software Package

Akhmadiya¹,

Moldamurat²,

Nabiyev³

et al. 2021

Preprint

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This article described the technology of determining earthquake epicenter with radar remote sensing on the example of Sentinel-1A/B. To determine the epicenter of the earthquake, the Earth's crust displacements were analyzed using radar remote sensing data obtained for the ascending and descending flight orbits. Coordinates of Earthquake epicenters were found according to line-of-sight displacement images via its maximum value. Displacement of the Earth's crust was obtained by processing in the GMTSAR package in the VirtualBox virtual machine of the Linux Ubuntu 16.04 operation system. Two earthquakes that occurred in 2020 were studied to determine the accuracy of finding epicenters using the ascending and descending orbits Sentinel-1A/B. These earthquakes occurred in Western Xizang, China, and Doganyol, Turkey. The maximum deviation from the officially registered epicenter coordinates was 15.38 km for Doganyol and 3.2 km for the Western Xizang earthquake. The negative displacement was 90 mm for Doganyol and 50 mm for Western Xizang.

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Section: Radar Image Processingmentioning

confidence: 99%

Determination of the Earthquake Epicenter from Line-of-Sight Displacement Images Obtained by Sentinel-1A/B Radar Data Using the GMTSAR Software Package

Akhmadiya¹,

Moldamurat²,

Nabiyev³

et al. 2021

Preprint

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“…In remote sensing applied to land resource surveys, wavelengths between 0.4-1.5mm are most used (Aslan et al, 2016). Landsat TM (Thematic Mapper) and SPOT were the satellites that found usage widespread for natural resource mapping for landscapes spread over hectares of land (Akshar Tripathi, 2018). The image type depended upon not only the purpose but also on the sensor used and the number of spectral bands it offered (Lobell et al, 2015), with Landsat providing much greater number of spectral bands than SPOT.…”

Section: Introductionmentioning

confidence: 99%

“…It is the RADAR backscatter per unit area of the distributed target with which the incident signal interacts. It is measured in degree decibels -dB ( Tripathi, Maithani & Kumar, 2018;Shashi, 2019;. Beta nought (β 0 ) is the brightness coefficient of the RADAR.…”

Section: Introductionmentioning

confidence: 99%

A Simplified Sub-Surface Soil Salinity estimation using Synergy of Sentinel-1 SAR and Sentinel-2 multispectral satellite data, for early stages of wheat crop growth in Rupnagar, Punjab, India

Tripathi

Tiwari

2020

Preprint

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Soil salinity has today become a highly disastrous phenomenon that is responsible for crop failure worldwide and specially in countries with low farmer incomes and food insecurity. Soil salinity is often caused due to water accumulation in fields due to unscientific flood irrigation wherein plants intake the water leaving salts behind. It is, however, the sub-surface soil salinity that affects the plant growth. These salts in sub-surface soil get trapped in root nodules of plants and prevent further water intake. There have been very few studies conducted for sub-surface soil salinity estimation. Hence this study aims to estimate sub-surface soil salinity (at 60 cm depth) for early stage of wheat crop growth in a simplified manner using freely available satellite data, which is a novel feature and prime objective in this study. The study utilizes Sentinel-1 SAR (Synthetic Aperture RADAR) data for backscatter coefficient generation, Sentinel-2 multispectral data for NDSI (Normalised Differential Salinity Index) generation and on ground equipment for direct collection of soil electrical conductivity. The data were collected for two dates in November and December 2019 and one date for January 2020 during the early stage of wheat crop growth. The dates were selected keeping in mind the satellite pass over the study area of Rupnagar on the same day. Ordinary Least Squares regression was used for modelling which gave R2-statistics of 0.99 and 0.958 in training and testing phase and root mean square error of 1.92 in modelling for soil salinity estimation.

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“…SAR or Microwave remote sensing has truly revolutionised the world of remote sensing with its versatile nature and all-weather availability (Abdikan, Sanli, Ustuner, & Calò, 2016). Like many other areas of study, SAR remote sensing has been highly useful in mapping and analysis of floods (Tripathi & Kumar, 2017). Floods have been a normal natural calamity for the people living in areas of low elevation (Huete, 2011).…”

Section: Introductionmentioning

confidence: 99%

Utilization of Spaceborne C-Band Sar Data for Analysis of Flood Impact on Agriculture and Its Management

Tripathi

Tiwari

2019

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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<p><strong>Abstract.</strong> North India, since time immemorial remained the cradle of agricultural development. Every year during the monsoons, there is a high upsurge in the river Rapti. This leads to heavy flooding in the area and takes a toll on life and property besides submerging acres of precious agricultural land. Till now, such floods have been mapped using satellite data from optical sensors, but in monsoons due to cloud cover the task becomes difficult. Spaceborne SAR (Synthetic Aperture RADAR) data solves this problem by offering all-weather availability. This study aims to utilize the potential of C-band dual PolSAR data from Sentinel-1A for flood mapping and analysis of its impact on agriculture along with suggesting mitigation measures. Sentinel-1A data of January and September 2018 was taken and pre-processed. Thereafter, an interferogram was prepared and was phase filtered using modified Goldstein phase filter to remove phase distortions and a DEM (Digital Elevation Model) was prepared. The phase maps generated were analyzed for phase variations after removing the topographic phase and it was found that there was very less phase variation from urban and agricultural lands surrounding the river which clearly indicated heavy flooding and submergence of land in water. Using the DEM map generated, hydrological processing was done to delineate flow lines and calculation of catchment area at point of maximum submergence of agricultural land. This was followed by the generation of contours in the area and finally, the flood impact analysis was done by calculating the water volume in watershed during the flood.</p>

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Effect of Phase Filtering on Interferometry based Displacement Analysis of Cultural Heritage Sites

Cited by 8 publications

References 25 publications

Determination of the Earthquake Epicenter from Line-of-Sight Displacement Images Obtained by Sentinel-1A/B Radar Data Using the GMTSAR Software Package

Determination of the Earthquake Epicenter from Line-of-Sight Displacement Images Obtained by Sentinel-1A/B Radar Data Using the GMTSAR Software Package

A Simplified Sub-Surface Soil Salinity estimation using Synergy of Sentinel-1 SAR and Sentinel-2 multispectral satellite data, for early stages of wheat crop growth in Rupnagar, Punjab, India

Utilization of Spaceborne C-Band Sar Data for Analysis of Flood Impact on Agriculture and Its Management

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