What is already known:
What this study adds:
During the first few weeks of June 2008, the Midwest experienced a weather system that dropped large amounts of rain across the region. In southern Indiana the Wabash and White Rivers went several feet above their flood stage and many people were displaced from their homes and businesses. This study uses the event as a test case for comparisons of resolutions and data from the MODIS and Landsat 5 TM sensors. A k-means classification scheme is created to cluster the data to identify the flood region in the imagery. Calculations are then made to estimate a flood area for each resolution. A statistical study is then performed to analyze false positive and and false negative rates using Landsat imagery as "ground truth." The results of the area estimate and statistical study support a claim that coarse resolutions, 1 and 2 kilometers, provide the most accurate measuring of area in large scale flood events, but the overall location of the fine details of the flood are lost. The finer resolutions (500 and 250 meters), while more accurate about locations of fine details, have a higher false positive and false negative rates that raise questions about their ability to effectively use this classification scheme to measure overall area. The conclusions of this research promote further questions as to what resolutions could be effectively used gain anaccurate map and measurement of the innundated area's extent.