Brennan William Young , Don R Hood, Michael P Bishop, Ryan C. Ewing, David Bustos

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.