Environmental hazards pose a significant threat to urban areas due to their potential catastrophic consequences affecting people, property and the environment. Remote sensing has become the de-facto standard for observing the Earth and its environment through the use of air-, space-, and ground-based sensors. Despite the quantity of remote sensing data available, gaps are often present due to the specific limitations of the instruments, their carrier platforms, or as a result of atmospheric interference. Massive amounts of data are generated from social media, and it is possible to mine these data to fill the gaps in remote sensing observations. A new methodology is described which uses social networks to augment remote sensing imagery of transportation infrastructure conditions during emergencies. The capability is valuable in situations where environmental hazards such as hurricanes or severe weather affect very large areas. This research presents an application of the proposed methodology during the 2013 Colorado floods with a special emphasis in Boulder County and The City of Boulder. Real-time data collected from social media, such as Twitter, are fused with remote sensing data for transportation damage assessment. Data collected from social media can provide information when remote sensing data are lacking or unavailable.