Recording Plan: 

Curated Track: 

Zhenlong Li, Pennsylvania State University

Call For Participation
We invite presentations to this session that has been organized for seven years. For participation in this session with a paper presentation, submit your abstract through the online portal by October 31. Please visit (https://www.aag.org/events/aag2025/) to complete your submission. Afterwards, please send an email containing your abstract's code/PIN, your paper's title, and the abstract to any of the session's organizers by December 2, 2024.

Description:

Aims and Scope:

Rapid onset disasters, often difficult to prepare for and respond to make disaster management a challenging task worldwide. Disaster and emergency management effectiveness depends heavily on making good decisions in near-real time under extreme duress. These keys, often life-saving, decisions are possible only with real-time data sources and the ability to timely collect, process, synthesize, and analyze these multi-sourced data. Traditional data collection practices such as remote sensing and field surveying often fail to offer timely information during or immediately following damaging events. For example, stream gauges are only useful for flood mapping while the stations are functioning properly and before they are overtopped by floodwaters and rendered inoperable.

Fortunately, sharing information such as texts, images, and videos through social media platforms enables all citizens to become part of a large sensor network and a homegrown disaster response team. Compared to traditional physical sensors, such a citizen-sensor network (social sensing) is low cost, more comprehensive, and always broadcasting situational awareness information. For example, with social sensing, massive amounts of micro-level disaster information (e.g., site specific damage) can be captured in real-time through social media platforms (e.g., Twitter, Facebook) and voluntarily reported via dedicated crowdsourcing applications (volunteered geographic information, VGI), enabling rapid assessment of evolving disaster situations. On the other hand, data collected with social sensing is often massive, heterogeneous, noisy, unreliable, and comes in continuous streams. This is inherent “Big Data”, for example, millions of microblog posts from different social media platforms can be generated in a short time right after an impactful disaster. Hence, Big Data computing methods and technologies such as cloud computing, distributed geo-information processing, spatial statistics/modeling, data mining, spatial database, and multi-source data fusion become critical components of using social sensing to understand the impact of and response to the disaster events in a timely fashion. Along these lines, this session aims to capture the insights in and bring up the discussion of leveraging social sensing and big data computing for supporting disaster management in one or more disaster phases (mitigation, preparedness, response, and recovery).

Possible topics include (but not limited) as following:
1- The role of social media as a real-time sensor network for disaster response and management
2- Challenges and solutions in using volunteered geographic information (VGI) for rapid disaster situation assessments
3- Advances in cloud computing and distributed geo-information processing for disaster management
4- Spatial statistics and modeling techniques for analyzing heterogeneous and noisy data from social sensing
5- Data mining strategies for extracting useful information from massive, unreliable streams of disaster-related data
6- Spatial database innovations for managing and querying large-scale disaster data
7- Techniques for multi-source data fusion to enhance situational awareness during disasters
8- Case studies of social sensing contributing to disaster management in recent events
9- Ethical considerations and privacy concerns in using social data

We invite presentations to this session that has been organized for seven years. For participation in this session with a paper presentation, submit your abstract through the online portal by October 31. Please visit (https://www.aag.org/events/aag2025/) to complete your submission. Afterwards, please send an email containing your abstract's code/PIN, your paper's title, and the abstract to any of the session's organizers by December 2, 2024.

Organizers
• Zhenlong Li, The Pennsylvania State University, zhenlong@psu.edu
• M. Naser Lessani, The Pennsylvania State University, mzl6134@psu.edu
• Huan Ning, Pennsylvania State University, hmn5304@psu.edu
• Qunying Huang, University of Wisconsin, qhuang46@wisc.edu
• Bandana Kar, U.S. National Renewable Energy Laboratory, yourbandana75@gmail.com

Non-Presenting Participants