Abstract
1 min readAbstract We increase the resilience of the Inland Water Ways (IWW) infrastructures and the connected land-infrastructures, thus ensuring reliable network availability under unfavorable conditions, such as extreme weather, accidents and other kind of hazards, a critical aspect towards resilience of these regions. Our main target is to combine downscaled climate change scenarios (applied to IWW infrastructures) with simulation tools and actual data to provide the relevant authorities/operators with integrated tools for more effective management of these infrastructures. Towards this direction, we aim to (a) use high resolution modelling data for the determination and the assessment of the climatic risk of on transport infrastructures and associated expected damages; (b) use existing data from various sources with new types of sensor-generated data (computer vision) to feed the used simulator; (c) utilize tailored weather forecasts for specific hot-spots, providing early warnings with corresponding impact assessment in real time; (d) develop improved multi-temporal, multi-sensor Unmanned Aerial Vehicles (UAV)- and satellite-based observations with robust spectral analysis, computer vision and machine learning-based assessment for diverse transport infrastructures; (e) design and implement an integrated Resilience Assessment Platform environment as an innovative planning tool that permit a quantitative resilience assessment through an end-to-end simulation environment; and (f) design and implement a Common Operational Picture, including an enhanced visualization interface and an Incident Management. This research fills the gap of the current practice where manual inspection is often used for managing the IWW infrastructures. Our approach is designed under a generic way to be applicable to other land uses and civil infrastructures like rural/urban regions monitoring, freight management over rivers, and environmental inspection of Natura areas. Our platform aims to address multi-hazard risk understanding, smart prevention and preparedness, as well as faster, adapted and efficient response.
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