STRADAR: Sinkhole hazards in linear transport infrastructures. Automatic detection and risk digitization
Convocatoria: Proyectos Estratégicos Orientados a la Transición Ecológica y a la Transición Digital, convocatoria 2021.
Financiación: Financiado por la Agencia Estatal de Investigación MCIN/AEI/10.13039/501100011033 y por la Unión Europea NextGenerationEU/PRTR.
Referencia: TED2021-1301183B-I00/MCIN/AEI/10.13039/501100011033
Summary:
Climate change is an important cause which can have an adverse influence on the behavior of pavements, thereby affecting transportation infrastructure performance and service life all over the world. A key factor in assuring the resilience and safety of transportation infrastructure is the integrity of the ground they are built upon. When soils shift or are washed away severe damage can occur like sinkholes and devastating failures under traffic that seriously compromise public safety and the environment. The effects of climate change on foundations soils should be then incorporated into the management strategies and decision-making processes of road service. Moreover, The European Environment Agency (EEA) warns that the largest increase in the number of drought and heavy rain events in Europe are projected for the Southern Europe and therefore in Spain. Therefore, it is becoming clear that the challenge of assessing sinkhole hazards and risks management strategies will become more common in the future.
STRADAR will provide a new procedure for the automatic detection and modelling of sinkholes formation within critical transport infrastructures from GPR (Ground-Penetrating Radar) data, as well as procedures for data quality assurance and digitization. Early detection and preventive maintenance are vital to avoid the damage that a sinkhole can cause, especially in urban areas and primary transport networks. There are common signs of sinkholes formation that can be identified in the road subsurface by GPR scans, such as settlements, moisture damage, voids and cavities. Thus, STRADAR will consist of a deep learning-based approach for detecting those signs of pavement and subgrade deformations that can lead to forming sinkholes. Moreover, new procedures will be also developed to digitize the forming sinkholes and the signs of risk detected into interoperable GIS/BIM (Geographic Information Systems / Building Information Modelling) information models. This risk digitization will be then used to elaborate sinkholes density and hazards maps, and determining key performance indicators (e.g. sinkholes severity and potential hazard), thus exploiting the capabilities of the STRADAR solutions for the rapid and early transmission of disaster information, the reliable and accurate understanding of disaster situations, impacts on road operations, influence on disaster response and recovery activities, and impacts on economic and social activities, as well as technological for understanding these impacts and supporting more appropriate decision-making based on these technologies.
STRADAR is mainly aligned with the Strategic Goal 3 Prevention and reduction of climate change impacts and improvement of resilience in towns and cities of the Urban Agenda 2030, principally through its lines of action “incorporate natural risk maps to planning” and “Prepare to be resilient”. The STRADAR objectives are also aligned with other national strategies such as the EECTI Challenge 5 Climate, Energy and Mobility and AI Strategy Priority 2 Connected Industry 4.0.
