Investigating the use of C-band phase closure data to produce soil moisture maps

Abstract

Soil Moisture is a key hydrological variable since it controls the interactions between the atmosphere, biosphere and hydrosphere. It is responsible for the partitioning of precipitation into evaporation, transpiration, percolation and run-off. Soil Moisture monitoring is used to indicate droughts in vegetated areas and is an important parameter to early warning systems for flood. Therefore, throughout the years human population attempted to monitor and control it. The advent of Remote Sensing, during the past decades, enormously influenced soil moisture research by enabling acquisition of large scale data. Many Remote Sensing systems were developed exclusively to study this variable. Land subsidence, triggered both by human activity and natural processes, is another phenomenon whose monitoring is crucial for the environment and the human populationa and is thus an essential variable which needs to be continuously monitored in vulnerable areas, since it can damage buildings’ foundations. Remote Sensing and more specifically Microwave remote sensing has been pivotal in studying land deformation and subsidence in near real time. Detecting and monitoring land subsidence and deformation with InSAR method has been meticulously researched however there are still obstacles to overcome such as vegetation. The aim of this research is to study whether InSAR closure phases can be used to detect moisture changes. The idea of using closure phases for soil moisture estimation was proposed by De Zan, Parizzi, et al. 2013 and further studied by Zwieback, Hensley, and Hajnsek 2015a. The closure phase inversion model of De Zan and Gomba 2018 is implemented in this thesis using Sentinel-1 C-band for the inversion and SMAP data for the evaluation of the results. The results support the idea that this method has potential over bare soil and low vegetated areas but struggles to overcome vegetation due to its limited penetration capability. Furthermore, soil moisture changes may introduce a systematic error to land subsidence measurements. For this reason, the idea was to make use of the generated soil moisture data to produce interferometric phase corrections over the study areas. However, the results are inconclusive due to the poor quality of the data over vegetated areas.