D-record: Disaster Response and Relief Coordination Pipeline
Document Type
Article
Publication Date
11-2018
Abstract
We employ multi-modal data (i.e., unstructured text, gazetteers, and imagery) for location-centric demand/request matching in the context of disaster relief. After classifying the Need expressed in a tweet (the WHAT), we leverage OpenStreetMap to geolocate that Need on a computationally accessible map of the local terrain (the WHERE) populated with location features such as hospitals and housing. Further, our novel use of flood mapping based on satellite images of the affected area supports the elimination of candidate resources that are not accessible by road transportation. The resulting map-based visualization combines disaster-related tweets, imagery and pre-existing knowledge-base resources (gazetteers) to reduce decision-making latency and enhance resiliency by assisting individual decision-makers and first responders for relief effort coordination.
Repository Citation
Kar, S.,
Al-Olimat, H. S.,
Thirunarayan, K.,
Shalin, V. L.,
& Sheth, A. P.
(2018). D-record: Disaster Response and Relief Coordination Pipeline. ARIC'18: Proceedings of the 1st ACM SIGSPATIAL Workshop on Advances on Resilient and Intelligent Cities, 13-16.
https://corescholar.libraries.wright.edu/knoesis/1165
