Modelling Flood Prone Areas Using a UAV-Based LiDAR Dataset: Jacksonville-Anniston-Oxford, Alabama Metropolitan Area

Keywords: Urban flooding, LiDAR, drones, hydrology, GIS, Jacksonville-Anniston-Oxford, Alabama metropolitan area
Abstract Type: Paper Abstract

Abstract

Urban flooding has been ranked as the fourth-costliest type of extreme climate disasters in the U.S. Currently, the Urban Flood Reports have estimated 3,600 urban floods over the past 25 years. The southeastern region of the United States has been frequently affected by severe floods caused by extreme rainfalls from hurricanes and tornadoes. In addition, this region contains the 20 fastest growing metropolitan areas. With rapid population growth, land-cover change, aging infrastructure, and sea-level rise, urban areas are currently at higher risk of flooding. The magnitude and extent of these floods are highly dependent on topographic conditions. As new high resolution elevation datasets predict that 250 million people are currently living below annual flood levels, which is three times more than the estimations from low resolution satellite-based elevation datasets. Hence, for effective flood response planning, the technological advances of remote sensing field can be used to accurately identify the extent of flood zones and the population and elements at high risk. Therefore, this study aims at i) full catchment scale flood assessment using regional airborne LiDAR, ii) and mapping areas in high risk with the three sample site locations within Jacksonville, Anniston and Oxford using supplementary UAV borne LiDAR elevation datasets to assess the improvement of flood estimations at local scale, and evaluate the capability of UAV-based digital terrain models (DTM) for identifying elements at high risk.