A LiDAR–optical data fusion approach for identifying and measuring small stream impoundments and dams

Journal Article · 13 November 2019 · Transactions in GIS

DOI: https://doi.org/10.1111/tgis.12595 · OSTI ID:1607262

Swan, Benjamin ^[1]; Griffin, Robert ^[2]

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1. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
2. Univ. of Alabama, Huntsville, AL (United States)

This article outlines a semi-autonomous approach for using a fusion of light detection and ranging (LiDAR) and optical remote sensing data to identify and measure small impoundments (SIs) and their dams. Quantifying such water bodies as hydrologic network features is critical for ecosystem and species conservation, emergency management, and water resource planning; however, such features are incompletely mapped at national and state levels. By merging an airborne LiDAR-derived point cloud with a normalized water index using airborne optical imagery we demonstrate an improvement upon single-source methods for identifying these water bodies; classification accuracies increased over 10% by using this multi-source fusion method. Furthermore, the method presented here illustrates a cost-effective pathway to improve the National Inventory of Dams (NID) and includes a framework for estimating dam heights, with results showing strong correlations between derived dam heights and those recorded in the NID (r=.78). With the steady increase in available LiDAR coverage, the 87,000+ dams in the NID could be updated using this technique, a method which could also be expanded for global inventories of SIs and dams.

• Research Organization: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: USDOE
• Grant/Contract Number: AC05-00OR22725
• OSTI ID: 1607262
• Journal Information: Transactions in GIS, Vol. 24, Issue 1; ISSN 1361-1682
• Publisher: WileyCopyright Statement
• Country of Publication: United States
• Language: English