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Using Public Surveys to Evaluate the Utility of Lidar Data for Flood Plane Determination

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dc.contributor.advisor Rice, Matthew
dc.contributor.author Marotta, Thomas
dc.creator Marotta, Thomas
dc.date 2017-12-06
dc.date.accessioned 2018-05-03T19:33:35Z
dc.date.available 2018-05-03T19:33:35Z
dc.identifier doi:10.13021/G8B38S
dc.identifier.uri https://hdl.handle.net/1920/10890
dc.description.abstract It is important to collect spatially relevant and evenly distributed elevations to correct for geospatial accuracy in Digital Elevation Models (DEMs). This is typically done by collecting ground truth data out in the field. The problem with conducting a field survey is the process of collecting the data. Visiting a location to collect elevations data is time consuming and can be difficult in areas with extreme terrain. Alternatively, this project proposes that it is possible to create a database of survey elevations based on the work others have already completed based on data that has been made publicly available. This paper reviews the vertical accuracy of elevation data that is submitted to the Federal Emergency Management Agency (FEMA) through the Letter Of Map Change (LOMC) application. The goal being to use completed surveys in lieu of collecting ground truths in the field. The vertical accuracy of the surveyed locations will be tested against a Light Detection and Ranging (LiDAR) elevation model. The result of the analysis shows that the surveyed elevations are within about a foot of the LiDAR elevations. This research demonstrates the FEMA published elevations could be used for future analysis since they are found to be consistent with higher resolution data sources as determined by regression analysis.
dc.language.iso en en_US
dc.subject Digital Elevation Model en_US
dc.subject letter of map change en_US
dc.subject lowest adjacent grade en_US
dc.subject flood insurance rate map en_US
dc.subject base flood elevation en_US
dc.title Using Public Surveys to Evaluate the Utility of Lidar Data for Flood Plane Determination en_US
dc.type Thesis en_US
thesis.degree.name Master of Science in Geoinformatics and Geospatial Intelligence en_US
thesis.degree.level Master's en_US
thesis.degree.discipline Geoinformatics and Geospatial Intelligence en_US
thesis.degree.grantor George Mason University en_US


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