This is a Preprint and has not been peer reviewed. This is version 1 of this Preprint.
Downloads
Authors
Abstract
Sand dune morphology is indicative of complex system interactions at a wide range of spatial and temporal scales that govern dune topographic structure. We created an object-oriented topographic framework based on slope attitude, curvature, and contextual analysis to map and characterize sand dune morphology at White Sands National Park, New Mexico, USA that limits empiricism and reliance on a priori knowledge of dune field structure and dynamics. We used eight LiDAR-derived digital elevation models with our framework to segment sand dunes and characterize dune morphology from 2007 to 2020 and evaluated dune field behavior and resilience. The segmentation is 92% accurate relative to manual mapping. From the segmentation, we calculated dune statistics, including height, width, length, area, volume, area-surface area ratio, circularity, migration rate, and aggradation rate. We found these statistics compared well with prior research. We identified a trend toward fewer dunes with greater area and volume from 2007 to 2020, which may be related to typical dune field maturation or short-term (seasonal to decadal) fluctuations related to weather and dune processes. Changes in dune migration rate and sand flux depended on the strength and directionality of seasonal southwesterly winds and likely periods of intense precipitation or drought. Trends identified in this study can be considered a baseline from which longterm trends identified through on-going monitoring can be evaluated. This research highlights current dependence on incomplete models for mapping and characterizing dunes and landscape resilience, and the need to quantitatively formalize numerous geomorphological concepts.
DOI
https://doi.org/10.31223/X5Z427
Subjects
Geomorphology
Keywords
White Sands, LiDAR, geomorphology, Geomorphometry, spatial structure, resilience
Dates
Published: 2024-09-25 12:29
Last Updated: 2024-09-25 19:29
License
CC BY Attribution 4.0 International
Additional Metadata
Conflict of interest statement:
None
Data Availability (Reason not available):
Data and code necessary to replicate this research can be found in the Texas Data Repository, DOI: 10.18738/T8/1KW6W2. https://dataverse.tdl.org/dataset.xhtml?persistentId=doi:10.18738/T8/1KW6W2
There are no comments or no comments have been made public for this article.