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S.A.N. van Diepen

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SPAMS

A new empirical model for soft soil surface displacement based on meteorological input data

Journal article - Philip Conroy, S.A.N. van Diepen, R.F. Hanssen

We present SPAMS: Simple Parameterization for the Motion of Soils, a model to describe the motion of deformable soils in the Vadose zone, mainly peat and clay, herein called shallow soft soils. The SPAMS model estimates the reversible and irreversible vertical component of surfac ...

Probabilistic Estimation of InSAR Displacement Phase Guided by Contextual Information and Artificial Intelligence

Journal article - Philip Conroy, S.A.N. van Diepen, Sanneke Van Asselen, Gilles Erkens, Gilles Erkens, F.J. van Leijen, R.F. Hanssen

Phase unwrapping, also known as ambiguity resolution, is an underdetermined problem in which assumptions must be made to obtain a result in SAR interferometry (InSAR) time series analysis. This problem is particularly acute for distributed scatterer InSAR, in which noise levels c ...

Bridging Loss-of-Lock in InSAR Time Series of Distributed Scatterers

Journal article - Philip Conroy, S.A.N. van Diepen, F.J. van Leijen, R.F. Hanssen

We introduce the term loss-of-lock to describe a specific form of coherence loss that results in the breakage of a synthetic aperture radar interferometric (InSAR) time series. Loss-of-lock creates a specific pattern in the coherence matrix of a multilooked distributed scatterer ...

Hybrid InSAR Processing for Rapidly Deforming Peatlands Aided by Contextual Information

Conference paper - Philip Conroy, S.A.N. van Diepen, F.J. van Leijen, R.F. Hanssen

We present a novel InSAR processing scheme which combines point scatterer (PS) and distributed scatter (DS) approaches in a hybrid framework along with contextual information about the environment under study. Data such as land parcel divisions, precipitation and temperature are ...

Absolute Elevation Time Series of Peat Soils from InSAR Observations using Integrated Geodetic Reference Stations

Poster - S.A.N. van Diepen, Philip Conroy, F.J. van Leijen, R.F. Hanssen

Peat areas in the Netherlands are expected to exhibit extremely dynamic vertical motion, including both reversible and irreversible components. Yet the exact behaviour as a function of time is unknown, and is spatially very variable. This results in a poorly known estimation of greenhouse gas emissions and impact to existing infrastructure, and consequently limited ability to design and deploy mitigating or adaptive measures. In situ measurements are inefficient to capture this dynamic spatio-temporal variability. To monitor wide areas, InSAR has the necessary coverage, resolution, and high temporal sampling, but is very sensitive to noise due to temporal decorrelation of vegetated areas, which in combination with the high temporal dynamics exacerbates the success rate of the phase ambiguity estimation. Moreover, motion measured with InSAR is inherently relative to a reference point which is typically not stable in time. Thus even if InSAR would yield sufficiently coherent results, interpretation is notoriously difficult. To address these problems, an Integrated Geodetic Reference Station (IGRS) was installed in a peat area. It includes SAR reflectors mechanically coupled to a GNSS antenna. Arcs from the IGRS to natural scatterers can therefore be connected to ETRS89. The resulting arcs are thus single-differences of elevation with respect to a reference epoch. In order to reduce noise, and subsequently increase the success rate of ambiguity resolution, we define Elementary Usage Polygons (EUPs), which are expected to move homogeneously. This is achieved by constraining each EUP to have only one subsurface type and one land usage, which allows for the definition of an expected functional model of the vertical movement. Using the expected functional model in combination with the GNSS measurements on the IGRS we can constrain the unwrapping on the arcs between the IGRS and nearby EUPs in order to improve the success rate of the unwrapping. By making use of elevation model data from 2020, the elevation of the reference epoch can be constrained. The single-difference arcs showing elevation change with respect to the reference epoch are transformed into elevations with respect to NAP, allowing for an absolute elevation time series from InSAR observations in the vegetated rapid-moving peat areas of the Netherlands.@en

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Evaluating the value of Integrated Geodetic Reference Stations

Assessment of the InSAR and GNSS observations

Master thesis - I. ZOUROS, R.F. Hanssen, S.A.N. van Diepen, D.C. Slobbe

Interferometric Synthetic Aperture Radar (InSAR) and Global Navigation Satellite Systems (GNSS) are widely used to monitor the dynamic behavior of the Earth. InSAR is a geodetic technique that estimates millimeter-level relative displacement time-series in an opportunistic network of a multitude of coherent points on the Earth’s surface, in a local datum. GNSS uses ground-based instrumentation to acquire time-series data over a limited number of specific and well-defined points in a known geodetic datum.The Integrated Geodetic Reference Station (IGRS) is designed to combine these (and other) techniques into one common instrument, establishing an integrated benchmark, i.e., a GNSS antenna and two radar corner reflectors, ensuring an identical kinematic behavior. This enables a geodetic datum connection, effectively enabling the InSAR results to be represented in a common geodetic datum, instead of a free network.However, the efficacy of the IGRS has not yet been proven, i.e., a thorough analysis of the first empirical results of an IGRS network has not yet been performed.Here we show that by using three years of data from a spatio-temporal network of 29 IGRS stations in an area of 60×60 km, and 742 independent Synthetic Aperture Radar (SAR) acquisitions, we reach a high level of agreement, demonstrating that IGRS can be used to connect InSAR information products to a well-defined geodetic datum.By using an Overall Model Test with a significance level of 5% we found that 96% of the double-difference arcs in time and space, sustain the null hypothesis that both the InSAR and the GNSS results stem from the same distribution. We found that the main reason for rejecting the null hypothesis for the remaining 4% of the double-difference arcs is that the results of both the InSAR and the GNSS are affected by a leakage of signal from the functional to the stochastic model. For the InSAR observations there is inadequately modeled atmosphere leaking into the stochastic model, while for the GNSS it appears that the precision estimate of the periodically moving stations is worse than the non-periodically moving stations, which suggests that the stochastic model is influenced by the the functional model.In the end, this study proved the efficacy of the IGRS to connect different geodetic datums, and this enables the InSAR results to be integrated in a well-defined geodetic datum.