CALL FOR PROPOSALS:

ORGANIZERS

  • Harvey Thorleifson, Chair
    Minnesota Geological Survey
  • Carrie Jennings, Vice Chair
    Minnesota Geological Survey
  • David Bush, Technical Program Chair
    University of West Georgia
  • Jim Miller, Field Trip Chair
    University of Minnesota Duluth
  • Curtis M. Hudak, Sponsorship Chair
    Foth Infrastructure & Environment, LLC

 

Paper No. 17
Presentation Time: 9:00 AM-6:00 PM

GEOMORPHIC MAPPING OF HOLOCENE ALLUVIUM USING LIDAR IN THE UPPER LITTLE TENNESSEE RIVER VALLEY, NORTH CAROLINA


MCDONALD, Jacob M., Geography, University of Georgia, GG Building, 210 Field St., Room 204, Athens, GA 30602 and LEIGH, David S., Department of Geography, The University of Georgia, Geog.-Geol. Building, 210 Field St., Room 204, Athens, GA 30602, jmcdon@uga.edu

A geomorphic map of the Upper Little Tennessee River valley, in Macon County, North Carolina, was constructed utilizing the Soil Survey Geographic (SSURGO) database and a digital elevation model (DEM) constructed from light detection and ranging (LiDAR) data. Soil survey map units from the SSURGO database were merged into similar landform categories (floodplain, low terrace, high terrace, colluvium, residuum, etc.) to produce a generalized (1:24,000 scale) geomorphic map of the valley. A 3-meter LiDAR-derived DEM was then manipulated to produce a large scale (1:1,000) geomorphic map of the study area. Though the valley slopes are mostly forested, the valley bottom is more heavily utilized as residential and agricultural land, which allowed a high level of confidence to be placed in the bare earth LiDAR point accuracy. A longitudinal profile of the historical terrace (T1) was created at a vertical resolution of 0.25 m. Using the longitudinal profile, a sloping plane was then created. This sloping plane was subtracted from the LiDAR DEM to create a slope-normalized residual plane. Geomorphic interpretation was based on the sign (positive or negative) and landscape position of the residual values. Positive residuals were interpreted as overbank levees and splays or terrace flats. Negative residuals were interpreted as channel, floodplain, point bar, or paleochannels. Landforms were manually digitized using high-resolution aerial photographs to differentiate between man-made and natural features. The LiDAR-derived geomorphic map allows a high degree of classification and provides a better understanding of the geomorphology compared to the coarser SSURGO data.
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