Flood Modeling Using a Synthesis of Multi-Platform LiDAR Data
| Autor: | Ashleigh Turner, Jeffrey Colby, Ryan Csontos, Michael Batten |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2013 |
| Předmět: |
LiDAR
lcsh:Hydraulic engineering Meteorology Geography Planning and Development mobile Aquatic Science Biochemistry Triangulated irregular network File size lcsh:Water supply for domestic and industrial purposes lcsh:TC1-978 terrestrial Lidar data Multi platform Water Science and Technology Remote sensing lcsh:TD201-500 HEC-RAS Flood myth airborne Ranging mountains flood inundation analysis Lidar Environmental science urban ArcGIS |
| Zdroj: | Water; Volume 5; Issue 4; Pages: 1533-1560 Water, Vol 5, Iss 4, Pp 1533-1560 (2013) |
| ISSN: | 2073-4441 |
| DOI: | 10.3390/w5041533 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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