Abstract
This study examined the utility of a high resolution ground-based (mobile and terrestrial) Light Detection and Ranging (LiDAR) dataset (0.2 m point-spacing) supplemented with a coarser resolution airborne LiDAR dataset (5 m point-spacing) for use in a flood inundation analysis. The techniques for combining multi-platform LiDAR data into a composite dataset in the form of a triangulated irregular network (TIN) are described, and quantitative comparisons were made to a TIN generated solely from the airborne LiDAR dataset. For example, a maximum land surface elevation difference of 1.677 m and a mean difference of 0.178 m were calculated between the datasets based on sample points. Utilizing the composite and airborne LiDAR-derived TINs, a flood inundation comparison was completed using a one-dimensional steady flow hydraulic modeling analysis. Quantitative comparisons of the water surface profiles and depth grids indicated an underestimation of flooding extent, volume, and maximum flood height using the airborne LiDAR data alone. A 35% increase in maximum flood height was observed using the composite LiDAR dataset. In addition, the extents of the water surface profiles generated from the two datasets were found to be statistically significantly different. The urban and mountainous characteristics of the study area as well as the density (file size) of the high resolution ground based LiDAR data presented both opportunities and challenges for flood modeling analyses.
Highlights
Humans have traditionally developed settlements in floodplains and continue to do so, making flood events one of the most consistent and recurring natural disasters experienced by human populations [1,2,3].The management of flood risk and the reduction of potential damages in the United States (U.S.) have been addressed by the Federal Emergency Management Agency (FEMA) through mapping flood hazard areas and the generation of Digital Flood Insurance Rate Maps (DFIRMS)
While the ground-based Light Detection and Ranging (LiDAR) dataset was registered to the ground control points (GCPs), errors associated with LiDAR collection still affected the accuracy of the data
The differences were not extensive on paved surfaces, the complexity of the study area was not fully captured by the airborne LiDAR data which could affect the outcome of the final hydraulic modeling results
Summary
Humans have traditionally developed settlements in floodplains and continue to do so, making flood events one of the most consistent and recurring natural disasters experienced by human populations [1,2,3]. Fewtrell et al [14] conducted one of the first flood inundation analyses based on sub-meter resolution elevation data acquired using a mobile LiDAR system in an urban environment and described the utility of such a high resolution dataset. They concluded that gaps found in their dataset were due to the limited field-of-view of their vehicle-based LiDAR system which produced a variety of undesirable artifacts within the floodwater depth grids (i.e., ponding near the data voids). The all-return mobile and terrestrial LiDAR point clouds were used to extract structural information from features intersecting the study stream reach Utilizing both the airborne and composite datasets, flood inundation analyses were completed and the resultant water surface profiles and depth grids were quantitatively compared. Challenges presented in this research included the complexity of attempting to accurately model an urban stream located in a mountainous headwater sub-basin
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