Automating Dune slack detection and mapping using QGIS
Hans van der Kwast, Md. Kausar Hossein, Yonas Asfaha
Dune slacks are low-lying depressions within dune ecosystems that exhibit unique microclimates, forming cold air pools during nighttime. This nocturnal cooling varies between slacks due to differences in their geomorphological characteristics, influencing local biodiversity and the broader ecosystem.
This study focuses on the automated detection of dune slacks using freely available geospatial data in QGIS. A dynamic thresholding parameter will be developed to accurately delineate dune slacks based different attributes. Following detection, each slack will be indexed and ranked according to geomorphological parameters to indicate their relative thermal behavior—ranging from coldest to warmest.
The methodology will integrate LiDAR-derived Digital Terrain Models (DTMs), in-situ temperature measurements, and other open-source spatial datasets. This approach not only streamlines the identification of dune slacks but also lays the groundwork for informed conservation strategies and deeper ecological insights into climate-sensitive dune environments.