Satellite data supporting situational awareness and management in a disaster

Abstract

Management of the disaster event requires seamless coordination across numerous agencies, systems, and stakeholders. A shared understanding of the situation is critical as responders from different organizations (e.g., fire, medical, police, military) must operate under high pressure. Satellite data supports situational awareness, and it is crucial to utilize satellite data and ontology platforms in disaster management. This article introduces an analysis of the utilization of ICEYE's SAR satellite technology and semantic ontology platforms in creating a situational picture and situation management of natural disasters, especially major floods. The article highlights that the challenge of traditional optical satellites is their weather dependence, which often makes them unusable in storms and heavy rains. This problem is solved by ICEYE’s SAR radar technology, which is able to penetrate clouds, smoke and darkness, producing weather-independent and real-time geographic information (GIS) from the incident area up to six hours apart. Satellite- based SAR data is important to integrate on regional sensor data (e.g. ground-based sensor fusion data, drone data and weather sensor data).The intelligent solution, MobiJOPA™ of start-up enterprise Husqtec Corp, served as use case environment for situation management. The received satellite data is directed to the semantic infrastructure of the MobiJOPA™ unit, where rule-based artificial intelligence and a common ontology model fuse it with, among other things, terrain elevation models (DEMs) and existing infrastructure information. The system harmonizes data from different sources into an unambiguous situational picture tied to the emergency workers’ own language, which breaks down information silos and effectively prevents misunderstandings between different authorities. The article shows that the seamless interaction of radar data and semantic modeling significantly speeds up critical decision-making.

Keywords: Disaster Awareness and Management, SAR-Radar Data, Geographical Information System, Data Integration, Semantic Modeling, Decision Making

DOI: 10.54941/ahfe1008202