Major: Environmental Science, Physics
Academic Affiliation: The City University of New York at Herbert H. Lehman College
Ayanna gained an appreciation for wildlife and environmental conservation when she saw her father free a seagull tangled in fishing line on a boat dock when she was a child. Her interest in the geosciences specifically, was sparked after her first earthquake experience during the 2011 M5.8 Virginia earthquake. This summer, Ayanna’s research focused on detecting and measuring land subsidence due to excessive groundwater pumping in the Houston-Galveston (HG) region of Texas using geodetic techniques such as radar interferometry (i.e. Interferometric Synthetic Aperture Radar (InSAR) and global positioning systems (GPS). Her work is a continuation of a prior study by Qu et al. 2015 on subsidence patterns in HG and aims to produce new time-series data from satellite and ground-based observations. The implications of this work will strengthen land subsidence monitoring systems in HG and broadly aid in the development of effective water resource management policies and strategies.
Detecting and Measuring Land Subsidence in Houston-Galveston, Texas Using Interferometric Synthetic Aperture Radar (InSAR) and Global Positioning System Data, 2012-2016
Several cities in the Houston-Galveston (HG) region in Texas have subsided up to 13 feet over several decades due to natural and anthropogenic processes [Yu et al. 2014]. Land subsidence, a gradual sinking of the Earth’s surface, is an often human-induced hazard and a major environmental problem expedited by activities such as mining, oil and gas extraction, urbanization and excessive groundwater pumping. We are able to detect and measure subsidence in HG using interferometric synthetic aperture radar (InSAR) and global positioning systems (GPS). Qu et al.  used ERS, Envisat, and ALOS-1 to characterize subsidence in HG from 1995 to 2011, but a five-year gap in InSAR measurements exists due to a lack of freely available SAR data. We build upon the previous study by comparing subsidence patterns detected by Sentinel-1 data starting in July 2015. We used GMT5SAR to generate a stack of interferograms with perpendicular baselines less than 100 meters and temporal baselines less than 100 days to minimize temporal and spatial decorrelation. We applied the short baseline subset (SBAS) time series processing using GIAnT and compared our results with GPS measurements. The implications of this work will strengthen land subsidence monitoring systems in HG and broadly aid in the development of effective water resource management policies and strategies.