Improving Low-Relief Coastal LiDAR DEMs with Hydro-Conditioning of Fine-Scale and Artificial Drainages

ECU Author/Contributor (non-ECU co-authors, if there are any, appear on document)
Thomas Richard Allen (Creator)
Robert Howard (Creator)
East Carolina University (ECU )
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Abstract: Improvements in Light Detection and Ranging (LiDAR) technology and spatial analysis of high-resolution digital elevation models (DEMs) have advanced the accuracy and diversity of applications for coastal hazards and natural resources management. This article presents a concise synthesis of LiDAR analysis for coastal flooding and management applications in low-relief coastal plains and a case study demonstration of a new, efficient drainage mapping algorithm. The impetus for these LiDAR applications follows historic flooding from Hurricane Floyd in 1999, after which the State of North Carolina and the Federal Emergency Management Agency (FEMA) undertook extensive LiDAR data acquisition and technological developments for high-resolution floodplain mapping. An efficient algorithm is outlined for hydro-conditioning bare earth (BE) LiDAR DEMs using available US Geological Survey1 National Hydrography Dataset (NHD) canal and ditch vectors. The methodology is illustrated in Moyock, North Carolina, for refinement of hydro-conditioning by combining pre-existing BE DEMs with spatial analysis of LiDAR point clouds in segmented and buffered ditch and canal networks. The methodology produces improved maps of fine-scale drainage, reduced omission of areal flood inundation, and subwatershed delineations that typify heavily ditched and canalled drainage areas. These preliminary results illustrate the capability of the technique to improve the representation of ditches in DEMs as well as subsequent flow and inundation modeling that could spur further research on low-relief coastal LiDAR applications.

Additional Information

Frontiers in Earth Science; 3:72 p. 1-10
Language: English
Date: 2015
Hydrologic Enforcement, Inundation modeling, Coastal Plains, Agricultural ditches, Light Detection and Ranging, LiDAR

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