Research
EOI-Lab team develops transformative and transdisciplinary solutions by creating world-class Earth observation data and leveraging sophisticated machine learning tools to tackle the grand challenges posed by natural and human-made hazards in the face of changing climate. Our research focuses on developing cutting-edge space-borne synthetic aperture radar technology and addresses emerging challenges at the nexus of water, climate, humans, and the environment. Our research has transformed the ability of large-scale high-resolution and on-demand analysis stream of big satellite data and improved understanding of vertical land motion and land surface change and how it amplifies the impact of compounding and extreme climate events such as prolonged droughts, floods, and rising sea levels. EOI-Lab has been recognized as a world leader in creating large-scale, high-resolution, and precise datasets of land movements.
Active Projects
Defense Resiliency Platform Against Extreme Cold Weather
The Defense Resiliency Platform (DRP) is a research-based multidisciplinary cyberinfrastructure platform enabling data integration and formatting, visualization, predictive analytics, and automated mapping of Arctic terrain data with the goal of maximizing the performance of the U.S. Army/CRREL in extreme cold weather environments.
Spaceborne InSAR Technology for Measuring Land Subsidence, Infrastructure Failure, and Flooding Hazards at DoD Installations in Alaska
While many multi-decadal SAR data sets are already available, the major limitation hindering their effective exploitation by DoD as climate-resilient tools is the lack of dedicated data centers offering high-quality and efficient analysis tools to process them at a fine spatial resolution and high accuracy on demand. From a DoD perspective, there is a pressing need to build transparent computational platforms for diverse end-users with flexible data requirements and quality. Timely access to land subsidence measurements is vital, for instance, to ensure the readiness and safety of DoD infrastructure. This proposal will offer an inexpensive and relatively risk-free framework to enable DoD end-users to obtain actionable data regarding ground surface motion remotely without requiring a field survey and boot on the ground. Our approach can thus significantly reduce costs and, beyond convenience, potentially save DoD personnel lives on battlefields and in unsafe environments.
Democratizing data to support adaptation decision making in the North-Atlantic Coastal Plain: land subsidence, compound flooding hazard and water quality
Spatially and temporally variable groundwater extraction, driven by various forcing factors, results in a poorly understood coastal land elevation change, exacerbating the negative impacts of sea-level rise through increased flooding hazards and saltwater intrusion. It can further impact surface water quality through alterations in flow paths and water chemistry. Despite its importance and impacts, groundwater remains a hidden and highly vulnerable resource, managed less restrictedly than surface water. Also, increased surface water withdrawal impacts water quality by introducing thermal, nutrient, and other contaminant pollution into water bodies and altering downstream flow regimes. To quantify the present-day and future status of (ground)water resources, their vulnerabilities, and socioeconomic impacts on local communities, this project will aim to co-produce knowledge and innovations through an academic-government-stakeholder partnership and leveraging advanced Earth observation data and modeling techniques. We will focus on the Chesapeake bay, home to eleven federally and/or state-recognized indigenous tribes.
Improving Sea level Information at DoD sites for risk assessments using hybrid modeling and data fusion
To improve the Defense Regional Sea Level (DRSL) database of tidal datums and EWL return levels and periods, our research will focus on the development of a holistic approach that hindcasts sea levels and tidal datums at any given location worldwide based on remote sensing and in-situ measurements, but also information on the contributing processes, their forcing, and their interaction. By hindcasting sea level with physical and empirical relationships, we will significantly enhance the existing DRSL database both temporally and spatially, which will ultimately reduce the uncertainties of EWL estimates and their vertical datum to levels commensurate with DRSL applications.
Physics-based induced earthquake forecasting: Process understanding and hazard mitigation
Injecting fluid under the ground is a technologically feasible approach for disposing wastewater, long-term storage of CO2, and enhancing geothermal plants for generating clean electricity. The fluid injection operations will likely increase and expand to densely populated areas to meet the growing need for renewable energy and reduce greenhouse gases. When Injecting large fluid volume, two issues are concerning: where the water goes and how induced seismic hazard evolves. Several influential review papers and DOE roundtable reports indicate that these concerns are the main obstacle to the large-scale deployment of these technologies to combat climate change and produce abundant renewable energy.
Understanding cyclone responses and related social-ecological dynamics in coastal human-mangrove-reef systems
This project will develop a social-environmental systems (SES) framework to understand the drivers of actions and their outcomes for ecosystem-based adaptation to extreme cyclone events. While the concepts of resilience and adaptive capacity in natural-resource systems to climate change are central to social-environmental systems (SES) theory, we do not know how extreme events impact coupled flows between people and ecosystems in these SES. Ecosystem-based Adaptation (EbA) has emerged over the past decade as an adaptation approach focused on managing and using ecosystems and their services to help people adapt to climate change and extreme events.
