Integrated Stage-Based Evacuation with Social Perception Analysis and

Dynamic Population Estimation

The research will help emergency response agencies better understand public perceptions and needs during disaster events, and create more effective evacuation plans for local communities. This project will integrate multiple data sources—including social media, census survey, geographic information systems (GIS) data layers, volunteer suggestions, and remote sensing data—to develop an integrated wildfire evacuation decision support system (IWEDSS) for the County of San Diego as a demonstration prototype system. IWEDSS will consist of four core modules: dynamic population estimation, stage-based robust evacuation models, social perception analysis, and a web-based geospatial analytics platform. It will offer scientifically-based and data-driven analytic tools for evacuation planers, resource managers, and decision makers to support efficient and effective decision-making activities that can reduce the evacuation time and potential number of injuries and deaths. The research team will collaborate with staff from the Office of Emergency Services (OES) of San Diego County, the San Diego/Imperial Counties Chapter of the American Red Cross, and 2-1-1 San Diego to develop IWEDSS together. The four main goals of this project are to:

Goal 1: Build a dynamic estimated population distribution (density) model in urban areas by integrating multiple data sources and GIS models (dasymetric mapping methods).

Goal 2: Design stage-based evacuation plans with population density distributions and develop robust optimization models to account for demand uncertainties.

Goal 3: Create a public opinion monitor and a resident feedback network to improve evacuation plans by understanding social perception of the disasters in local communities through the real-time analysis of social media and volunteer suggestions.

Goal 4: Build a web-based geospatial analytics platform and provide interactive decision support tools for decision makers, emergency resource managers, and public officers.

Introduction of SMART 2.0 Dashboard

SMART Dashboard is a Geo-Targeted search tool for Twitter messages to monitor the diffusion of information and social behavior changes which provides an automatic procedure to help researchers to:
1. Search geographically in cities
2. Filter noises (such as removing redundant retweets and using machine learning methods to improve precisions)
3. Analyze social media data from a spatiotemporal perspective
4. Visualize social media data in various aspects (such as weekly and monthly trends, top URLs, top retweets, top mentions, or top hashtags)

GIScience and Web GIS (Tsou), GIScience (Nara),
Transportation (Yang), Transportation (Ghanipoor Machiani)