On a sunny Friday afternoon of August 26, 2022, in a sinking Corpus Christi coast, one more MANTIS student has successfully defended a dissertation proposal.
Xiaojun has been working with Remote Sensing and applications for measurements with hyperspectral sensors since his master’s degree and has focused on the utilization of Interferometric Synthetic Aperture Radar (InSAR) for the estimation of land subsidence on the Texan coast as his Ph.D. research topic. His work has been developed under Dr. Chu’s supervision and it is titled Estimating Land Subsidence and Sea-Level Changes Combined with Geodetic Techniques along The Texas Gulf Coast, USA. To learn more, read his abstract below.
Abstract
Global sea-level data have long been recorded via tide gauge (TG) stations by measuring relative water-land movement, referred to as relative sea-level change (RSLC). RSLC is an aggregated effect of 1) vertical land motion (VLM) and 2) sea surface height changes relative to a defined geocentric reference frame, referred to as absolute sea-level change (ASLC). A consistently rising sea level can increase flood risks and cause remarkable impacts on ecosystem resilience, near-shore infrastructures, the daily lives of coastal residents, etc. Understanding the spatial and temporal patterns of VLM is deemed crucial for the knowledge discovery of RSLC. This research proposes to estimate VLM along the Texas Gulf Coast, one of the leading subsided areas in the United States, from multiple sources of observation data: 1) TG plus satellite radar altimetry (SRA); 2) the global navigation satellite system (GNSS); and 3) the interferometric synthetic aperture radar (InSAR). A high-resolution VLM map will be produced by exploring the spatiotemporal patterns of VLM results from different methods. In addition, the VLM results will be aggregated with the ASLC trend estimated using SRA data to project RSLC changes. Finally, based on the estimation results of VLM and RSLC, locations for installing new GNSS/TG stations will be recommended through geographic information system (GIS) and spatial analysis by considering various features, such as distribution of existing stations, spatiotemporal variability of VLM/RSLC, estimation uncertainty, and so forth. Results will hopefully provide knowledge to pertinent stakeholders to assist the decision-making process.