2026 Venezuela Earthquake Recovery

An initiative led by C-RASC at George Mason University in partnership with the GulfStream Foundation, transforming earthquake-related data from citizen sensing, geospatial observations, and damage assessments into actionable intelligence for relief and recovery efforts while advancing evidence-based disaster research.

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Research Background

The project collects, integrates, and analyzes heterogeneous data sources to transform raw data into structured knowledge. By leveraging human-AI collaboration methods, it reduces information overload for emergency responders and relief workers, making unstructured crisis data actionable for decision support in emergency services and humanitarian organizations.

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Featured Tools

Two systems were rapidly developed in the aftermath of the June 2026 Venezuela earthquake context — one focused on social media signals for help-seeking and resource needs, and the other on geospatial visualization of damage and infrastructure knowledge.

Citizen Sensing

CHORD: Citizen-Helper Operational Recovery Dashboard

Leveraging the Citizen-Helper platform, the tool collect and integrates disaster-related content from YouTube and Reddit in the context of the 2026 Venezuela earthquakes and transforms it into actionable intelligence using AI methods. Interactive visualizations enable response teams to rapidly assess needs, identify emerging issues, and prioritize relief efforts.

Intent Analyzer categorizes aid requests across clothing, food, medical, shelter, volunteer, and general needs
Sentiment Analyzer tracks public morale to surface concerns and operational gaps in relief activities
Interactive timelines and a Relevancy Controller let users focus on high-confidence requests for a chosen window

Response Radar overview dashboard — Overview — intent, sentiment signals, and resource-request breakdowns

Response Radar comment and video detail view — Detail view — comment stream, video ranking, and embedded playback

Geospatial Knowledge Base

RISE: AI-powered Recovery Intelligence and Support Engine

RISE tool combines a geospatial knowledge graph with an interactive GIS dashboard and natural language querying capabilities to make complex earthquake damage and response activity-related data accessible and actionable. It brings together authoritative data from multiple sources into a single, coherent model of the disaster, enabling users to quickly understand impacts and prioritize relief efforts.

Integration of diverse data from Copernicus damage assessments, OpenStreetMap and Overture Maps infrastructure, AI-predicted building footprints, and USGS ShakeMap intensity
Interactive map for spatial exploration of damage and facilities
Natural-language chatbot for asking questions without GIS expertise

RISE map view with intelligence assistant — Map view — shaking intensity, damage layers, and intelligence assistant

RISE satellite view focused on La Guaira — Satellite view — local damage exploration with guided queries

Local Evidence Dashboard

VENEViewer: Situational Awareness for Venezuela Earthquake Response

VENEViewer is an evidence-oriented dashboard that consolidates geospatial, hazard, infrastructure, and recovery-related information into a single map-centered interface. It supports situational awareness for Venezuela earthquake response and recovery, letting users review conditions alongside the sources backing them.

Map-centered interface for spatial review of hazard, infrastructure, and recovery layers
Selected authoritative data brought together with visible source attribution for each layer
Early public prototype for stakeholder exploration and validation - not an official emergency-management system

Contact

Interested in the work, collaboration, or access to these tools? Reach out to us:

Lead

Prof. Hemant Purohit

Humanitarian Informatics Lab, C-RASC

Email hpurohit AT gmu DOT edu

Center Center for Resilient, Adaptable, and Safe Communities (C-RASC)