Formalizing aeolian morphometry: Object-based topographic mapping of White Sands dunes

Dune field patterns change spatially and temporally in response to the environmental boundary conditions in which they form. Dune morphology reflects complex system interactions at various scales that shape dune topography. We developed an object-oriented topographic framework based on slope attitude, curvature, and contextual analysis to map and analyze dune morphology, reducing reliance on empiricism and prior knowledge of dune field structure and dynamics. The algorithm segments the DEM into slope-steepness and slope-azimuth units using ISODATA clustering, then combines them into slope-facet terrain units. It applies spatial rules to partition dune and interdune areas via substrate interpolation and elevation thresholding. Within dune areas, a Height–Divergence Index identifies dune-part units, which are hierarchically grouped into complete dunes based on boundary divisiveness and adjacency. Using eight LiDAR-derived digital elevation models, we segmented dunes and characterized dune morphology from 2007 to 2020, assessing dune-field behavior and response to environmental changes. The segmentation achieved 92% accuracy compared to manual mapping. From this, we derived dune statistics, including height, width, length, area, volume, area-to-surface-area ratio, circularity, migration rate, and aggradation rate, which aligned well with previous research.The dune field maintained structural coherence and a positive sediment budget despite dynamic migration, possibly indicating dune-field maturation or short-term fluctuations influenced by weather and dune processes. Variations in dune migration rates and sand fluxes depended on the strength and direction of seasonal southwesterly winds, as well as periods of heavy rain or drought. This study emphasizes the need to quantitatively formalize current geomorphological concepts.