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There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
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Xiao Huang is a third-year Ph.D. candidate from the Department of Geography at University of South Carolina (expected to graduate in Spring 2020). He obtained his bachelor’s degree from Wuhan University in 2015 and his Master’s degree from Georgia Institute of Technology in 2016. In his 3-year Ph.D. career, he has published more than 10 leading-author publications, with 3 of them winning student competition awards in fields of applied geography, remote sensing, and cyberinfrastructure. In 2019 alone (so far), he received 7 grants/scholarships, both internal and external. Recently, He was awarded Paul Lovingood Graduate Research Award, the SPARC Graduate Research Grant and was one of the thirteen exceptional graduate students who were honored as Breakthrough Graduate Scholars by USC’s Office of the Vice President for Research. His research primarily focuses on geospatial analysis, environmental modeling, computer and data science, and Big Data analytics within the general area of GIScience.
Title:
Sensing and Improving Flood Awareness via Remote Sensing and Social Sensing
Abstract:
Remote sensing (RS) and social sensing (SS) have fundamentally facilitated the acquisition of flood awareness in many ways. Transcending field survey methods, remotely sensed images provide larger spatial coverage and make near real-time flood monitoring possible. Social sensing has witnessed increasing attention due to the popularity of crowdsourcing approaches. Volunteered geographical information (VGI), a type of crowdsourcing data, provides an alternative approach to reporting useful information about a flood in a real-time manner. In this talk, I will discuss some remote/social sensing challenges and innovative methods to monitor human-flood interactions during and after flood events. Specifically, I will address the potential of fusing heterogeneous data sources (RS and SS) via advanced geospatial models to provide enhanced flood awareness.
