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

dc.contributor.advisorRice, Matthew
dc.contributor.authorMarotta, Thomas
dc.creatorMarotta, Thomas
dc.date2017-12-06
dc.date.accessioned2018-05-03T19:33:35Z
dc.date.available2018-05-03T19:33:35Z
dc.description.abstractIt 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.identifierdoi:10.13021/G8B38S
dc.identifier.urihttps://hdl.handle.net/1920/10890
dc.language.isoen
dc.subjectDigital Elevation Model
dc.subjectLetter of map change
dc.subjectLowest adjacent grade
dc.subjectFlood insurance rate map
dc.subjectBase flood elevation
dc.titleUsing Public Surveys to Evaluate the Utility of Lidar Data for Flood Plane Determination
dc.typeThesis
thesis.degree.disciplineGeoinformatics and Geospatial Intelligence
thesis.degree.grantorGeorge Mason University
thesis.degree.levelMaster's
thesis.degree.nameMaster of Science in Geoinformatics and Geospatial Intelligence

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