GSA Annual Meeting in Phoenix, Arizona, USA - 2019

Paper No. 237-10
Presentation Time: 10:45 AM


YOUNG, Brennan W.1, BISHOP, Michael P.1 and EWING, Ryan C.2, (1)Department of Geography, Texas A&M University, College Station, TX 77843, (2)Department of Geology and Geophysics, Texas A&M University, 3115 TAMU, College Station, TX 77843

Eolian sand dunes cover Earth’s warm deserts. Wind conditions, sediment supply, climate, and vegetation govern their spatio-temporally dependent morphology. Studying complex eolian morphodynamics is difficult due to challenges associated with semantic definitions and mathematical characterization of process-form relationships. Although remote sensing technologies permit acquisition of large, high-resolution, multi-temporal datasets, geospatial big-data pose spatial analysis efficiency and characterization challenges. Furthermore, a formal framework for characterizing topographic spatial structure does not exist for relating dune structure and patterns to processes. Here, we characterize and map dunes by mathematically formalizing concepts based on linkages between topographic spatial structure and eolian processes.

We use 1 m resolution LiDAR digital elevation models of the dune field at White Sands National Monument (WSNM), New Mexico acquired from 2007 – 2010 and 2015, to assess dune spatial properties. Dunes are mapped using object-oriented analysis by partitioning the topography based on slope angle and slope azimuth, stratifying partitions based on slope angle, and aggregating based on topology. Specific dunes are separated based on connectivity structure (dune bifurcations), mass, and surface morphology. Crestlines are identified based on surface elevation and morphology. Dune field topographic structure is then quantified (volume, length, sinuosity, spacing, etc.).

Our analysis shows that sand dunes at WSNM are barchanoid dunes that exhibit E-W periodicity in dune height, and that crescent dunes have high surface area to planimetric area ratios compared to barchanoid dunes in the study area. We find that dune surface morphology and dune mass distribution may relate to locations of dune collisions and subsequent annealing processes. This suggests that various aspects of dune genetics and behavior may be predicted based on dune morphology alone. Multitemporal characterization of dune topographic structure will assist in evaluating trends in dune migration patterns. Overall, we find that our approach to objective mapping and characterization of topographic structure in dune fields to be effective for deriving meaningful quantification of eolian structure and dynamics.

  • GSA 2019 Young 20190725.pdf (2.7 MB)