Detection Threshold Estimates for InSAR Time Series: A Simulation of Tropospheric Delay Approach.

Emre Havazli,Shimon Wdowinski

doi:10.3390/s21041124

Emre Havazli, Shimon Wdowinski

Open Access

https://doi.org/10.3390/s21041124

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Abstract

We present a method for estimating the detection threshold of InSAR time-series products that relies on simulations of both vertical stratification and turbulence mixing components of tropospheric delay. Our simulations take into account case-specific parameters, such as topography and wet delay. We generate the time series of simulated data with given intervals (e.g., 12 and 35 days) for temporal coverages varying between 3 and 10 years. Each simulated acquisition presents the apparent noise due to tropospheric delay, which is constrained by case-specific parameters. As the calculation parameters are randomized, we carry out a large number of simulations and analyze the results statistically and we see that, as temporal coverage increases, the amount of propagated error decreases, presenting an inverse correlation. We validate our method by comparing our results with ERS and Envisat results over Socorro Magma Body, New Mexico. Our case study results indicate that Sentinel-1 can achieve ≈1 mm/yr detection level with regularly sampled data sets that have temporal coverage longer than 5 years.

Highlights

Interferometric Synthetic Aperture Radar (InSAR) time-series techniques are important tools for studying tectonic and non-tectonic ground deformation over large areas with millimeter-per-year-level accuracy [1,2,3]
We modeled vertical stratification by using a digital elevation model (DEM) and standard deviation of wet delay calculated from precipitable water vapor (PWV) data collected by the moderate resolution imaging spectroradiometer (MODIS) instrument on the Terra and
We developed a simulation technique to systematically investigate the impact of tropospheric phase delay on InSAR time series by accounting for two main tropospheric processes: vertical stratification, and turbulence mixing

Summary

Introduction

Interferometric Synthetic Aperture Radar (InSAR) time-series techniques are important tools for studying tectonic and non-tectonic ground deformation over large areas with millimeter-per-year-level accuracy [1,2,3]. Tropospheric delay remains a significant error source in InSAR time series, which propagates through the time-series inversion into analysis products, e.g., velocity field [3,11,12,13,14]. More advanced methods used additional data sources for estimating the tropospheric phase delay and removed it from InSAR observations. These additional data sources vary from GPS-derived phase delays [22,23] to satellite-observed phase delays, such as medium resolution imaging spectrometer (MERIS) and moderate resolution imaging spectroradiometer (MODIS) [24,25,26,27,28], and numerical weather models, such as ERA5 of the European Centre for Medium-Range

Results

Discussion

Conclusion