Flooding is a very costly natural disaster especially when it hits urban areas. Yet synthetic aperture radar (SAR) based flood mapping barely works in urban areas. Buildings and man made objects have similar backscatter signatures as still standing water. This makes them hard to distinguish from one another. Structures can block the visibility of the ground surface for side looking SAR satellites making large parts of potentially flooded ground going unseen by SAR satellites. Smooth surfaces and limited ground visibility make it hard to produce accurate flood maps using SAR in urban environments. Here we have shown how the use of a temporal stack can improve the result of urban flood detection with SAR. Traditionally SAR based flood mapping uses a single image or an image pair to classify flooded and non-flooded pixels. This study found these methods unable to detect flooded pixels in an urban setting. By using a temporal stack of SAR images more pixels are correctly classified as flooded while keeping false positive classifications low. However the number off correctly classified pixels remains too low to be useful on its own, by adding ancillary data in the form of a high resolution DEM an accurate flood map for a very specific area is produced. This means that SAR images are not suitable for flood mapping in urban areas as a single source of information. When they are combined with other data they have the potential to produce accurate flood maps useful for First responders when the next flooding disaster hits.