<html><head><meta http-equiv="content-type" content="text/html; charset=us-ascii"></head><body style="overflow-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div>***Apologies for cross-posting***</div><div><br></div><div>Dear Colleagues, </div><div><br></div><div>We invite you to submit abstracts to our AGU 2024 Session NH016: <a href="https://agu.confex.com/agu/agu24/gateway.cgi">Earth Observations for Monitoring and Assessment of Risk and Resilience of Communities and Infrastructures</a> by <b><i>Wednesday, 31 July 2024 at 23:59 EDT</i></b>. We have been organizing this session for more than five years. We hope that you will contribute to this session and join us in AGU 2024. </div><div><br></div><div><b>Session NH016</b></div><div><b>Session ID:</b> 228508</div><div><b>Section:</b> Natural Hazards </div><div><br></div><div><b>Session Description:</b> The availability of large volumes of imagery data at high spatial and temporal resolutions from various sources (small satellites, unmanned aerial vehicles) and advancements in imagery and computational sciences have enabled the implementation of near real-time analytics to inform decisions about risk, resilience, response, and recovery. Considering that extreme events threaten critical infrastructures and contribute to cascading infrastructure failures, providing timely and reliable information to authorities and stakeholders about pre-disaster conditions, post-disaster loss, and recovery progression is crucial for response management, resource allocation, recovery, and risk reduction from future events. </div><div><br></div><div>In this session, we invite papers focusing on data and image fusion, algorithms and models for near real-time analytics, and applications of emerging theories, tools, and methods for disaster informatics and risk visualization, including digital twin, generative AI, mobile/edge computing, augmented/virtual reality, and other emerging technologies. Papers concerning multi- and inter-disciplinary implications arising from data quality, social/physical uncertainties, ethics of using EO and AI, and future directions to improve resilience are also invited.</div><div><br></div><div>Submit abstract <a href="https://agu.confex.com/agu/agu24/prelim.cgi/Home/0">here</a>. Please feel free to forward to any colleagues that may be interested in submitting an abstract to this session.</div><div><br></div><div>Session Conveners</div><div>Bandana Kar, US Dept. of Energy</div><div>Margaret Glasscoe, UAH</div><div>Guy Schumann, ImageCat Inc.</div><div>ZhiQiang Chen, UMKC</div><div><br></div><div>Thank you for your consideration,</div><div>Maggi</div><br class="Apple-interchange-newline"></body></html>