. Flood detection through Optical and SAR data

Abstract
Flooding is one of the most prevalent natural disasters in the world, causing many fatalities and high economic loss. Thus, there is a need to quantify flooding in ways which can aid in disaster management and decision making. In particular, coastal regions are highly susceptible to flooding, including the Shabelle River which runs through Somalia in Africa. Between approximately April the end of May 2018, particular regions of the Shabelle experienced significant flooding, resulting in an an interesting region to test new methods to quantify flooding. This includes determining the spatial extent of the flooding from the before and after boundaries, water cover before and during flooding, and the depth of the water. Here we employ the method employed by Refice et al. (2018) to quantify flooding for a specific region of the Shabelle river. This method uses both SAR and optical data to quantify the flooded region. This technique is ideal because it allows for an increased temporal resolution in quantifying the flooded region, which can also give us more information about the dynamics of the flooding. A basic histogram thresholding technique will be applied to separate water from non-water pixels in both the SAR and optical images to create binary maps of either non-flooded or flooded. These binary maps will then be plotted in time to quantify how the flooding changes ifrom before the floods, through the flood time period, and after the waters recede. The expected results consist of this binary flooding map through time, area calculation of the flooded region, and estimates of the height of the water in the flooded region.