Time series methods for Synthetic Aperture Radar data to monitor ground deformation, soil moisture and floodwater

• Main Authors: Karamvasis, Kleanthis, Καραμβάσης, Κλεάνθης
• Format: Doctoral or Postdoctoral Thesis
• Language: English
• Published: National Technical University of Athens (NTUA) 2022
• Subjects: Εδαφική υγρασία; Εδαφική παραμόρφωση; Συμβολομετρία ραντάρ; Ραντάρ συνθετικού ανοίγματος/κεραίας (SAR); Πλημμύρες; Soil moisture; Floods; Synthetic Aperture Radar (SAR); Ground deformation; SAR interferometry; Γεωεπιστήμες και Επιστήμες Περιβάλλοντος; Φυσικές Επιστήμες; Γεωεπιστήμες; διεπιστημονική προσέγγιση; Περιβαλλοντική Μηχανική; Επιστήμες Μηχανικού και Τεχνολογία; Επιστήμη και Τεχνολογία υδάτων; Earth and Related Environmental Sciences; Natural Sciences; Geosciences; interdisciplinary; Environmental Engineering; Engineering and Technology; Water Science and Technology; permafrost
• Online Access: http://hdl.handle.net/10442/hedi/52921; https://doi.org/10.12681/eadd/52921

Climate change is a major challenge of our time. Adapting to climate action is an economic and environmental imperative. In order to enhance our climate resilience, we need to improve our understanding of climate change impacts. Some of the most important impacts are temperature increase, more severe storms, increased drought and warming and increasing ocean. Many of these impacts are interrelated and have many associated causes. An essential need is to better understand the interdependencies between climate change cause/effect variables. Earth observation data have a unique role for improving understanding of climate change, due to the fact that they enable monitoring at several spatiotemporal scales with global coverage. Remote sensing technology can improve climate change modelling but it also has some limitations. For example, multispectral and hyperspectral sensors can provide data only during the day with no cloud coverage. On the contrary, SAR datasets can provide consistent data flows day and night. The unprecedented increased volume of SAR/InSAR data can enable approaches that can hugely benefit climate change adaptation actions. This dissertation contributes to enhancing the role of time series of SAR/InSAR data for three climate change related topics.The first topic is the study of TSInSAR methodologies that estimate ground deformations, as well as ground deformation relationships with natural agents. Ground deformation is an essential climate change variable which is connected to a) increasing groundwater extraction due to increasing droughts; b) permafrost thawing due to increasing temperature and c) increased flood/sinking risk over coastal regions. A thorough analysis of several TSInSAR methodologies for ground deformation is presented. First, an accuracy assessment of the vertical component of ground deformation which was estimated from multiple orbit TSInSAR results is presented. Then, a detailed performance analysis of several TSInSAR methodologies is provided. Next, a wavelet-based ...