Big Visual Data analytics for Natural Disaster Management

This tutorial on Big Data Analytics for Natural Disaster Management (NDM) provides a comprehensive overview and in-depth presentation of advanced technologies involved in the acquisition and analysis of Big Data for NDM. NDM can be greatly improved by developing automated means for precise semantic mapping and phenomenon evolution predictions in real-time. Several extreme data sources can significantly help towards achieving this goal: a) autonomous devices and smart sensors at the edge, equipped with AI-capabilities; b) satellite images; c) topographical data; d) official meteorological data, predictions or warnings published in the Web; and e) geosocial media data (including text, image and video). The course focus will be on drone image analysis for Natural Disaster Management.

The course consists of 4 lectures, covering important topics and presenting state-of-the-art technologies in:

Sensors and Big Visual Data Analytics for Natural Disaster Management (NDM)
Wildfire Image Analysis
Flood Image Analysis
Localizing Smoke and Gas Sources using Physics-Inspired Sparse Bayesian Learning Method
The presented technologies find practical application in developing an advanced NDM support system that dynamically exploits multiple data sources and AI technologies for providing an accurate assessment of an evolving crisis situation.