Unveiling a landscape: mapping aeolian dunes in the Argentine Pampa plain using local entropy analysis of DEMs
Keywords:
Remote sensing, Local Entropy, Parabolic dunes, Quaternary, TanDEM-XAbstract
The Pampa plain of Argentina, southern South America, constitutes a vast low-relief landscape whose Neogene-Quaternary history was dominated by aeolian deposition and morphogenesis. Although dunes exist in the region—mostly inactive under current climatic conditions—their full spatial extent and morphology have remained partially obscured by vegetation (grassland) and agricultural activity, rendering them difficult to detect with conventional digital elevation model (DEM) visualization techniques. To address this challenge, we developed DemEntropy, a novel method that applies a local entropy filter to a DEM to quantify topographic disorder and highlight organized geomorphic patterns. This open-source software package is freely distributed and provides a reproducible method for enhancing subtle topographic features based on their textural properties. Application of DemEntropy to TanDEM-X data for the Pampa plain yielded two significant results. First, it successfully enhanced the boundaries and aeolian morphologies of the known Central Pampean Dunefield unit (CPD), of the Pampean Sand Sea, demonstrating the robustness of the method. Second, and more notably, it revealed extensive, previously undocumented aeolian features northeast of the Tandilia range, in the loess domain (Loess and loess-like mantles and blowouts unit, LMB), where such features are not discernible in standard hillshade models. These findings demonstrate the efficacy of local entropy analysis for geomorphological mapping and reveal a more complex and extensive history of aeolian activity in the region than previously recognized. By providing this tool as a freely available software package, we aim to enable the wider community to apply this powerful technique to the study of subtle aeolian and fluvial landscapes in other vegetated and low-relief settings globally.
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