The exposure of critical transport infrastructure to natural hazards and climate change effects has severe consequences on world economies and societies and, thus, safety and resiliency of transport networks are of paramount importance. The currently available frameworks for quantitative risk and resiliencebased design and assessment have been mainly developed for bridges exposed to earthquakes. However, there is an absence of well-informed exposure, vulnerability, functionality and recovery models, which are the main components in the quantification of resilience. The present paper proposes an integrated framework for the data-driven resilience assessment of transport infrastructure exposed to multiple hazards by using multiscale monitoring data, such as terrestrial and airborne data, as well as open-access crowd data and environmental measurements. Monitoring and early warnings are expected to produce accurate and rapidly informed quantitative risk and resilience assessments for transport infrastructure and to enhance asset management. Therefore, this framework aims to facilitate stakeholders’ decision-making for daily and catastrophic events and to support adaptation and preparedness with preventive and/or retrofitting measures against multiple hazards.