How Much Can We Rely on InSAR to Measure Deformation Correctly?

InSAR has been nowadays accepted as a standard tool for measuring the earth surface deformation in different natural and human-induced hazard applications. Despite this acceptance, the quality, and in particular the reliability, of InSAR deformation estimates under unfavorable conditions, e.g., large displacements with strong spatio-temporal variations or in highly vegetated and decorrelating terrains is still questionable and sometimes controversial. In particular, under these conditions, the InSAR algorithms are highly prone to unwrapping errors, which can result in incorrect (or biased) deformation estimates. As there is no standard analytical criterion to assess the probability of unwrapping error occurrence, a question is always raised in these scenarios: How much can we rely on InSAR to measure deformation correctly?

Although an experienced InSAR specialist may qualitatively assess the reliability of the results based on his own knowledge and analytical skills, such an assessment is not straightforward for end users of InSAR-derived products. This may end in a misinterpretation of, or a misinformation about InSAR results. In this regard, there is a need for a reliability-description approach capable of digesting the different processing factors, settings, and assumptions to quantify the probability of correct phase unwrapping, and in this way, to provide an analytical measure to assess the reliability of the results.

In this contribution, we argue that InSAR measurements are inherently ambiguous with respect to deformation, in contrast to other geodetic techniques. Therefore InSAR requires a distinctive approach for quality description. As unwrapping errors may occur due to different causes, we argue that we need different quality description approach for each cause. Here we introduce three quality measures: i) measure of unwrapping correctness to quantify the probability of correct unwrapping error for each point, ii) measure of reliability to quantify the sensitivity of the used algorithms to detect unwrapping errors, and iii) measure of falsifiability to quantify how much sensitive the results are to the used a-priori assumptions of phase unwrapping. We argue that with exploitation of these three quality measures, we can offer a comprehensive quality description framework to assess the reliability of InSAR-derived products. The idea of such quality description is demonstrated via different subsidence case studies in Iran.