PREFERRED

Following the 2061/04.08.22 decision of the Attika Region Governor, the financing of the project «PREVENTING FIRE EVENTS BY REDISCOVERING & EXTENDING DEEP LEARNING METHODS-PREFERRED) was approved.
The funding scheme relies on the Activity RESEARCH INNOVATION SYNERGIES IN THE ATTICA REGION of the OPERATIONAL PROGRAM ATTICA 2014-2020.
The climate change escalation, all over the world, increases the vulnerability of forests to fires, and threatens, on the one hand their very existence and on the other, especially in the contact zones of urban areas and natural vegetation (wildland urban interface/ WUI), the safety of citizens, the social cohesion and prosperity. The severity of the effects (loss of human life, infrastructures’ damages, etc.), as recorded in a multitude of catastrophic events, highlights the level of danger for the environment we live in, as well as, the criticality of timely valid information availability towards a more effective management of the events.
Under the above frame, and with reference to the Priority «3.10.1 Effects of the climate change to the urban environment», the project focuses to the Subject Area 3-ESD: Environment and Sustainable Development.
The relative research activities, with the objective of & "Mitigation and adaptation to climate change and natural disasters (3.10)" focus, among other, to the development of innovative services, which may be exploited by, agencies and institutes that are, directly or indirectly, involved with firefighting and damages’ recovery and/ or crisis management (fire departments, civil protection agencies), and/ or management of infrastructures and structures (e.g. refugee accommodation structures, camps, etc..), environmental parks, archaeological sites, etc.
Focusing on the Priority 4: Enhancing disaster preparedness, of the Sendai Framework for Disaster Risk Reduction and to urban areas (WUI), in the context of the project, innovation of the research activities applies to a series of Scientific & Technological fields: a/ Design & Implementation of Big Data Geospatial Databases; automation & triggering, data fusion & data smart analytics, etc. b/ Innovative modelling (machine learning technologies) for the risk estimation through dynamic update of parameters, c/ Retrieval & provision, collection, management & processing of satellite data and d/ Analysis of big geospatial data using deep learning methods.

GEOAPIKONISIS S.A.P&GE. has the responsibility of the project technical management, while the scientific responsibility of the research belongs to the BEYOND Operational Unit of the National Observatory of Athens.
The Research Center ATHENA – Research &Innovation Information Technologies contributes to the research through developing innovative, deep learning modelling.

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