Version 1
: Received: 14 June 2022 / Approved: 17 June 2022 / Online: 17 June 2022 (08:57:52 CEST)
Version 2
: Received: 18 January 2023 / Approved: 19 January 2023 / Online: 19 January 2023 (11:50:03 CET)
How to cite:
Olsen, K.; Calef, M.; Agram, P. Contextual Accuracy Assessments for InSAR Methods Using Synthetic Data. Preprints2022, 2022060251. https://doi.org/10.20944/preprints202206.0251.v1
Olsen, K.; Calef, M.; Agram, P. Contextual Accuracy Assessments for InSAR Methods Using Synthetic Data. Preprints 2022, 2022060251. https://doi.org/10.20944/preprints202206.0251.v1
Olsen, K.; Calef, M.; Agram, P. Contextual Accuracy Assessments for InSAR Methods Using Synthetic Data. Preprints2022, 2022060251. https://doi.org/10.20944/preprints202206.0251.v1
APA Style
Olsen, K., Calef, M., & Agram, P. (2022). Contextual Accuracy Assessments for InSAR Methods Using Synthetic Data. Preprints. https://doi.org/10.20944/preprints202206.0251.v1
Chicago/Turabian Style
Olsen, K., Matthew Calef and Piyush Agram. 2022 "Contextual Accuracy Assessments for InSAR Methods Using Synthetic Data" Preprints. https://doi.org/10.20944/preprints202206.0251.v1
Abstract
InSAR and associated analytic methods enable relative surface deformation measurements from low Earth orbit with a potential accuracy of centimeters to millimeters. However, assessing the actual accuracy of individual points can be quite difficult. The analytic methods are complicated enough that na¨ıve analytic error propagation is infeasible, and, in many settings, InSAR practitioners lack sufficient ground truth to assess results. Phase noise due to partial decorrelation from changes in the scattering properties of the ground is a prominent source of accuracy loss. In this paper we present a method to assess the loss of precision due to this component of phase noise. The proposed method consists of generating synthetic data whose statistical properties match that of the actual input SAR data stacks, and then using the synthetic data for an ensemble calculation. The spread of the results of the ensemble calculation indicates the loss of precision. We show examples of the ensemble analysis at a mining operation in South Africa, and demonstrate the ability to assess the most reliable methods for particular points of interest using this ensemble analysis and the ability to filter out points based on the width of the spread of results
Keywords
InSAR; deformation; synthetic data; ensemble methods; uncertainty estimate; time series analysis
Subject
Environmental and Earth Sciences, Geophysics and Geology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
