GC033
Earth Observations and Imagery Science to Assess Risk and Resilience of Communities and Infrastructures to Climate Change
Session ID#: 161833
Session Description:
The availability of large volume of imagery at high spatio-temporal resolutions from various sources (small satellites, unmanned areal vehicles) along with advancements in geospatial and computational sciences have enabled implementation of near real-time analytics and modeling approaches to inform decisions about risk, resilience, response and recovery. Even during the COVID-19 pandemic, Earth observation (EO) data were useful in understanding the economic and environmental impacts of the pandemic as well as other extreme events.
In this session, we invites papers using artificial intelligence, image fusion and analytics, geo-visualization and geo-computation techniques to (i) explore and understand the interactions between extreme events, built environment and socio-physical systems, (ii) assess and forecast risk and resilience of communities and infrastructures, (iii) assess socioeconomic and environmental impacts, (iv) visualize and communicate risk and resilience to stakeholders for decision-making, and discussing the ethics and accuracies of using EO data and artificial intelligence to model and assess risk and resilience. We envision the session to include presentations and panels followed by moderated discussions to set the stage for future directions in the above mentioned areas.
Co-Sponsor(s):
Index Terms:
1821 Floods [HYDROLOGY]
1910 Data assimilation, integration and fusion [INFORMATICS]
4337 Remote sensing and disasters [NATURAL HAZARDS]
4341 Early warning systems [NATURAL HAZARDS]
Primary Convener: Bandana Kar, Oak Ridge National Laboratory, Geospatial Science and Human Security Division, Oak Ridge, TN, United States
Conveners: Margaret T Glasscoe, University of Alabama in Huntsville, Huntsville, AL, United States, Guy Schumann, University of Bristol, School of Geographical Sciences, Bristol, United Kingdom and ZhiQiang Chen, University of Missouri Kansas City, Kansas City, MO, United States
Machine Learning Modelling for Predicting Roadside Forest Risk on Distribution Powerlines (1077709)
Harshana Wedagedara, University of Connecticut, Department of Natural Resources and the Environment, Storrs, United States, Chandi Witharana, University of Connecticut, Natural Resources and the Environment, Storrs, United States, Durga Prasad Joshi, University of Connecticut, Department of Natural Resources and the Environment, Groton, CT, United States, Robert Timothy Fahey, University of Connecticut, Natural Resources and the Environment, Storrs, CT, United States, Diego Cerrai, University of Connecticut, Department of Civil and Environmental Engineering, Groton, CT, United States and Jason Parent, The University of Rhode Island, Department of Natural Resources Science, Kingston, RI, United States
Building Community Resilience: Using High Resolution Imagery to Identify Blue Tarps in the Florida Panhandle after Hurricane Michael (1092712)
Elaina Gonsoroski1, Yoonjung Ahn2, Emily W Harville3, Nathaniel Countess2, Maureen Y Lichtveld4, Ke Pan3, Leslie Beitsch5, Samendra prasad Sherchan6 and Christopher Koh Uejio1, (1)Florida State University, Geography, Tallahassee, FL, United States, (2)Florida State University, Geography, Tallahassee, United States, (3)Tulane University of Louisiana, Epidemiology, New Orleans, United States, (4)University of Pittsburgh, Environmental and Occupational Health, Pittsburgh, United States, (5)Florida State University, Behavioral Sciences and Social Medicine, Tallahassee, United States, (6)Tulane University of Louisiana, New Orleans, United States
Resilience Building with Cloud to Street’s Near Real-Time Observation System in Flood Vulnerable Countries. (1124647)
Afolarin Lawal1, Tyler Anderson1, Annalee Tai2, Emmalina Glinskis2 and Alexa Lopez1, (1)Cloud to Street, New York, NY, United States, (2)Cloud to Street, New York, United States
Development of Sectoral Climate Adaptation Plan to Enhance Resilience of the Island Nation of Antigua and Barbuda (1128326)
Marina T. Mendoza1, Shubharoop Ghosh2, Elizabeth Emanuel3 and Melisa Huyck1, (1)ImageCat, Inc., Long Beach, United States, (2)ImageCat, Inc., Long Beach, CA, United States, (3)Sustainability Managers, Kingston, Jamaica
Vulnerable Roads to Long-term Relative Sea Level Rise (RSLR) by 2100: A Case Study of Anne Arundel County, Maryland. (1137948)
Sotonye Ikiriko1, Yi Liu2, Sean Qian3 and Xin Zhou2, (1)Morgan State University, Civil Engineering, Baltimore, MD, United States, (2)Morgan State University, Civil Engineering, Baltimore, United States, (3)Carnegie Mellon University, Department of Civil and Environmental Engineering, Pittsburgh, PA, United States
Prediction of land use changes according to SSP/SPA scenarios for Anseong City in response to a decrease in population (1139434)
Suryeon Kim1, Chan Park1, Somin Park2, Wonkyong Song3 and Jaeyong Choi4, (1)University of Seoul, Seoul, Korea, Republic of (South), (2)University of Seoul, Seoul, South Korea, (3)Dankook University, Cheon an, South Korea, (4)Chungnam National University, Daejeon, South Korea
An Interactive Statewide Spatial Hazard Analysis, Detection, and Environmental Change Tool (SHADE-C) (1156621)
Sourav Saha1, William C Haneberg2, Jason Dortch2, Matthew Crawford2, Douglas Curl1 and Hudson J Koch3, (1)Kentucky Geological Survey Lexington, Lexington, KY, United States, (2)University of Kentucky, Kentucky Geological Survey, Lexington, KY, United States, (3)University of Kentucky, Kentucky Geological Survey, Lexington, United States
Resilience Assessment of Urban Road Network with Flood Damage using Remote Sensing Data (1203615)
ZhiQiang Chen, University of Missouri Kansas City, Kansas City, MO, United States, Molan Zhang, University of Missouri - Kansas City, Division of Energy, Matter, and Systems, Kansas City, United States, Margaret T Glasscoe, JPL-Caltech, Pasadena, CA, United States, Kristy French Tiampo, University of Colorado at Boulder, Department of Geological Sciences, Boulder, CO, United States and Bandana Kar, University of Southern Mississippi, Stennis Space Center, MS, United States
