ABSTRACT
Disaster response plays a vital role in reducing disaster impacts and building resilient communities. Efficient disaster response relies heavily on timely information describing disaster impacts and local needs to coordinate first responders and allocate resources. Geospatial big data offer a novel channel to observe time-sensitive, disaster-related information that can support effective disaster response. However, accurately identifying valuable information from geospatial big data and applying it in disaster response is technically and practically challenging. The emergence of Geospatial Artificial Intelligence (GeoAI) provides new opportunities. This chapter aims to foster the convergence of GeoAI and disaster response with three objectives: (1) establishing a comprehensive paradigm that expounds upon the diverse applications of GeoAI with geospatial big data towards enhancing disaster response efforts; (2) exhibiting the employment of GeoAI in disaster response through the analysis of social media data during the 2017 Hurricane Harvey with advanced Natural Language Processing models; and (3) identifying the challenges and opportunities associated with the complete realization of GeoAI's potential in disaster response research and practice. The results will extend the GeoAI knowledge and its critical role in disaster response, as well as underscore prospects for future research and practice in this domain.
