Abstract
Atmospheric effects represent one of the major error sources of repeat-pass Interferometric Synthetic Aperture Radar (InSAR), and could mask actual displacements due to tectonic or volcanic deformation. The tropospheric delays vary both vertically and laterally and can be considered as the sum of (i) a vertically stratified component highly correlated with topography and (ii) a turbulent component resulting from turbulent processes in the troposphere varying both in space and time. In this paper, we outline a framework to routinely use pointwise GPS data to reduce tropospheric effects on satellite radar measurements. An Iterative Tropospheric Decomposition (ITD) model is used and further developed to separate tropospheric stratified and turbulent signals and then generate high-resolution correction maps for SAR interferograms. Cross validation is employed to assess the performance of the ITD model and act as an indicator to users of when and where correction is feasible. Tests were carried out to assess the impact of GPS station spacing on the ITD model InSAR correction performance, which provides insights into the trade-off between station spacing and the achievable accuracy. The application of this framework to Sentinel-1A interferograms over the Southern California (USA) and Southern England (UK) regions shows approximately 45–78% of noise reduction even with a sparse (~50–80km station spacing) GPS network and/or with strong and non-random tropospheric turbulence. This is about a 50% greater improvement than previous methods. It is believed that this framework could lead to a generic InSAR atmospheric correction model while incorporating continuous and global tropospheric delay datasets, e.g. numerical weather models.
Highlights
Based on the dynamic nature of the troposphere, numerous attempts have been made on the quantification and mitigation of Interferometric Synthetic Aperture Radar (InSAR) tropospheric effects which are usually divided into two types
We have demonstrated a framework to routinely use GPS to reduce tropospheric effects on radar measurements
Cross validation and station spacing tests were carried out to serve as indicators of correction performance to inform users whether the correction is applicable and provide insights into the trade-off between station spacing and the achievable accuracy
Summary
Radar signals are delayed when passing through the troposphere, especially the wet delay part due to atmospheric water vapor, which is a major Interferometric Synthetic Aperture Radar (InSAR) error source when mapping the Earth's surface movements (e.g. Massonnet et al, 1994; Massonnet and Feigl, 1998; Williams et al, 1998; Simons and Rosen, 2007; Ding et al, 2008; Hooper et al, 2012; Jolivet et al, 2014). Of all the external information, GPS provides the highest temporal resolution (e.g. 5 min) of Zenith Total Delay (ZTD) measurements, and avoids additional uncertainties due to the time differences between water vapor and radar measurements when using MODIS, MERIS or ECMWF (Li et al, 2009; Walters et al, 2013). (1) The Iterative Tropospheric Decomposition (ITD) interpolation model developed by Yu et al (2017) is utilized (and further developed for applicability to relative delays for InSAR) to better separate both stratified and turbulent components from the total tropospheric delays without using predefined local parameters, and as a spatial interpolator to generate total delay maps from both dense and sparse networks and in either flat or topography variation areas;. (3) Tests are carried out to assess the impact of GPS station spacing on the performance of the ITD based InSAR tropospheric correction, which provides insights into the tradeoff between station spacing and the achievable accuracy
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