Infrastructure assessment for disaster management using multi-sensor and multi-temporal remote sensing imagery

In this paper, a new assessment system is presented to evaluate infrastructure objects such as roads after natural disasters in near-realtime. A particular aim is the exploitation of multi-sensorial and multi-temporal imagery together with further {GIS-}data in a comprehensive assessment framework. The combination is accomplished combining probabilities derived from the different data sets. The assessment system is applied to two different test scenarios evaluating roads after flooding yielding very promising results and evaluation values concerning completeness and correctness. The benefit of the data combination, in particular the multi-temporal component, demonstrates the suitability of the proposed method for different application scenarios.