A Covariance-Based Approach to Merging InSAR and GNSS Displacement Rate Measurements

This paper deals with the integration of deformation rates derived from Synthetic Aperture Radar Interferometry (InSAR) and Global Navigation Satellite System (GNSS) data. The proposed approach relies on knowledge of the variance/covariance of both InSAR and GNSS measurements so that they may be com...

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Main Authors: Alessandro Parizzi, Fernando Rodriguez Gonzalez, Ramon Brcic
Format: Article
Language:English
Published: MDPI AG 2020-01-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/12/2/300
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spelling doaj-ed7af75af28a49af918a0ccbff81101d2020-11-25T02:45:08ZengMDPI AGRemote Sensing2072-42922020-01-0112230010.3390/rs12020300rs12020300A Covariance-Based Approach to Merging InSAR and GNSS Displacement Rate MeasurementsAlessandro Parizzi0Fernando Rodriguez Gonzalez1Ramon Brcic2Remote Sensing Technology Institute German Aerospace Center (DLR) Münchenerstraße 20, 82234 Weßling, GermanyRemote Sensing Technology Institute German Aerospace Center (DLR) Münchenerstraße 20, 82234 Weßling, GermanyRemote Sensing Technology Institute German Aerospace Center (DLR) Münchenerstraße 20, 82234 Weßling, GermanyThis paper deals with the integration of deformation rates derived from Synthetic Aperture Radar Interferometry (InSAR) and Global Navigation Satellite System (GNSS) data. The proposed approach relies on knowledge of the variance/covariance of both InSAR and GNSS measurements so that they may be combined accounting for the spectral properties of their errors, hence preserving all spatial frequencies of the deformation detected by the two techniques. The variance/covariance description of the output product is also provided. A performance analysis is carried out on realistic simulated scenarios in order to show the boundaries of the technique. The proposed approach is finally applied to real data. Five Sentinel-1A/B stacks acquired over two different areas of interest are processed and discussed. The first example is a merged deformation map of the northern part of the Netherlands for both ascending and descending geometries. The second example shows the deformation at the junction between the North and East Anatolian Fault using three consecutive descending stacks.https://www.mdpi.com/2072-4292/12/2/300insargnssdeformation
collection DOAJ
language English
format Article
sources DOAJ
author Alessandro Parizzi
Fernando Rodriguez Gonzalez
Ramon Brcic
spellingShingle Alessandro Parizzi
Fernando Rodriguez Gonzalez
Ramon Brcic
A Covariance-Based Approach to Merging InSAR and GNSS Displacement Rate Measurements
Remote Sensing
insar
gnss
deformation
author_facet Alessandro Parizzi
Fernando Rodriguez Gonzalez
Ramon Brcic
author_sort Alessandro Parizzi
title A Covariance-Based Approach to Merging InSAR and GNSS Displacement Rate Measurements
title_short A Covariance-Based Approach to Merging InSAR and GNSS Displacement Rate Measurements
title_full A Covariance-Based Approach to Merging InSAR and GNSS Displacement Rate Measurements
title_fullStr A Covariance-Based Approach to Merging InSAR and GNSS Displacement Rate Measurements
title_full_unstemmed A Covariance-Based Approach to Merging InSAR and GNSS Displacement Rate Measurements
title_sort covariance-based approach to merging insar and gnss displacement rate measurements
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2020-01-01
description This paper deals with the integration of deformation rates derived from Synthetic Aperture Radar Interferometry (InSAR) and Global Navigation Satellite System (GNSS) data. The proposed approach relies on knowledge of the variance/covariance of both InSAR and GNSS measurements so that they may be combined accounting for the spectral properties of their errors, hence preserving all spatial frequencies of the deformation detected by the two techniques. The variance/covariance description of the output product is also provided. A performance analysis is carried out on realistic simulated scenarios in order to show the boundaries of the technique. The proposed approach is finally applied to real data. Five Sentinel-1A/B stacks acquired over two different areas of interest are processed and discussed. The first example is a merged deformation map of the northern part of the Netherlands for both ascending and descending geometries. The second example shows the deformation at the junction between the North and East Anatolian Fault using three consecutive descending stacks.
topic insar
gnss
deformation
url https://www.mdpi.com/2072-4292/12/2/300
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