Geoinformatics for Food, Energy, and Water
As groundwater resources have been increasingly susceptible to climate variability and change in many semi-arid regions, there is a critical need to understand the challenges of sustainable water resource management and to develop coping strategies. Groundwater sustainability can be understood from a social-ecological system (SES) perspective, or viewed as a critical part of Food, Energy, Water (FEW) nexus.
AI and Big Data for FEW
I currently work on three projects related to AI and Big Data for food, energy, and water research: (1) Using GeoAI to identify hydraulic drainage structures (i.e., culverts and bridges) for terrain-based drainage modeling (water), (2) Using social media and machine learning to examine the public perception of fossil-fuel and renewable energies (energy), and (3) Using drone images and AI to identify crop diseases (food).
PI, Social Media Footprints of Public Perception on Energy Issues and Their Policy Implications, 07/01/2017-06/30/2018, CO-PI: Justin Schoof, Energy Boost Seed Grant awarded by SIU Advanced Coal and Energy Research Center
Smart and Connected Rural Communities
Concerning potential widening rural-urban divide in smart society and community development, my research attempts to (1) understand smart divide by analyzing gaps in both physical and social infrastructures, and (2) smart connectivity solutions for rural health and disaster resilience. In 2020, we proposed an emerging concept - smart divide - in a paper of Annals of AAG.
PI, EAGER: SAI: Understanding and Bridging the Smart Technology Infrastructure Divide in Rural America . 09/2021-8/2023, Co-PI: J. Crowe, K. Chen, awarded by National Science Foundation
PI, Preparing for 2024 Total Solar Eclipse: A Social Sensing Approach for Understanding Human Mobility in Southern Illinois, 01/01/2021-12/31/2021, SIU Foundation Board Research Award