Using Texture Statistics to Identify and Map Different Dune Types within the Rub’ al Khali

Date

2023

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Abstract

Understanding the movement, direction, and shape of sand dunes can contribute to reducing their impact on infrastructure and the environment. The Rub’ al Khali desert has a distribution of dune types. This study aims to identify and map the different types of dunes within the Rub’ al Khali using a texture analysis method based on a digital elevation model (DEM). Statistical texture analysis methods (variance, skewness, and kurtosis) show three different textures of sand dune shapes, according to the geography of the dunes, using data contained in global DEMs. The analysis presented in this study focused on the use of DEMs to investigate the varied dune morphology within the Rub’ al Khali. The GMTED2010 and EarthEnv_DEM90 digital elevation models were compared. Spatial variability in dune height, spatial variability in dune texture, and profile graphs were created to examine dune surfaces in cross-section. The results provided six different dune types within the sand sea: giant compound linear dunes, simple linear dunes, simple transverse dunes, compound crescentic dunes (megabarchans), huge star dunes, and many transitional forms that defy classification. The results showed that the compound linear dune and simple linear dune were the dominant dune types, covering 41.61% and 31.7% of the total study area, respectively. The maps of variance, using either 10 × 10 and 30 × 30 focal blocks, produced a fairly sharp distinction in dune texture. It is hoped that future research in aeolian geomorphology will greatly benefit from these results, which could easily be expanded with the use of more sophisticated pattern recognition software, which clearly shows the value of using such an approach.

Description

© 2023 by the authors. cc-by

Keywords

DEM, dune types, Rub’ al Khali, sand dunes, texture analysis

Citation

Almutlaq, F., & Mulligan, K.. 2023. Using Texture Statistics to Identify and Map Different Dune Types within the Rub’ al Khali. Remote Sensing, 15(19). https://doi.org/10.3390/rs15194653

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