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Layer: World_Map_Grid_01 (1)

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Description: This layer provides a global latitude and longitude grid at 1-degree intervals, suitable for detailed mapping and analysis. It is part of the World Latitude and Longitude Grids dataset, which offers multiple grid resolutions for use as overlays in GIS applications. The 1-degree grid is ideal for applications requiring a fine-grained reference system for global data visualization and analysis (https://hub.arcgis.com/maps/ece08608f53949a4a4ee827fd5c30da1/about).

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Layer: World_Map_Grid_005 (2)

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Description: This layer provides a global latitude and longitude grid at 5-degree intervals, balancing detail and readability for medium-scale world maps. It belongs to the World Latitude and Longitude Grids dataset, designed for use as a base reference in GIS applications. The 5-degree grid is well-suited for regional studies, thematic maps, and general global reference overlays (https://hub.arcgis.com/maps/ece08608f53949a4a4ee827fd5c30da1/about).

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Layer: World_Map_Grid_025 (3)

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Description: This layer provides a global latitude and longitude grid at 25-degree intervals, designed for small-scale, global overviews. It is part of the World Latitude and Longitude Grids dataset, which provides grids at multiple resolutions to support diverse mapping needs. The 25-degree grid is most effective for broad-scale visualization, navigation reference, and educational use in global mapping projects (https://hub.arcgis.com/maps/ece08608f53949a4a4ee827fd5c30da1/about).

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Layer: Mecca_Boundary (4)

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Description: Mecca Region Boundary provides a 2022 boundary with a total population count. The layer is designed to be used for mapping and analysis. It can be enriched with additional attributes using data enrichment tools in ArcGIS Online. The 2022 boundaries are provided by Michael Bauer Research GmbH. These were published in December 2022.https://www.arcgis.com/home/item.html?id=5aa5fd4f9664472db9f4f48587cda7bf

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Layer: Riyadh_boundary (5)

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Description: Riyadh Region Boundary provides a 2022 boundary with a total population count. The layer is designed to be used for mapping and analysis. It can be enriched with additional attributes using data enrichment tools in ArcGIS Online. The 2022 boundaries are provided by Michael Bauer Research GmbH. These were published in December 2022.https://www.arcgis.com/home/item.html?id=5aa5fd4f9664472db9f4f48587cda7bf

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Layer: Urban_areas_Roads_ (6)

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Layer: Landuse_ESA_2021 (7)

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Description: The land-cover product we have generated from the ESA 2021 Land Cover dataset offers a high-quality, satellite-based map that provides detailed information on the Earth's surface cover. The map is highly regarded for its accuracy, resolution, and the use of advanced remote sensing technology to classify different types of land cover, such as vegetation, water bodies, urban areas, bare surfaces, etc. It's considered a good quality product because of its comprehensive coverage, frequent updates, and the rigorous validation processes it undergoes. These features make it particularly useful for environmental monitoring, climate change studies, and land management. The detailed land cover information helps distinguish dunes from other land cover types, facilitating targeted analysis and interventions in those areas. The source data can be downloaded at https://worldcover2021.esa.int/.

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Layer: Wind Patterns (8)

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Layer: Composite_U100_V100_January_Mean_WM.tif (9)

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Description: Monthly mean near-surface winds from the ERA5 reanalysis dataset were analyzed to further constrain the seasonal variability of wind patterns influencing dune morphology. The average winter winds (month: January) (Fig. 5-Report #2). We then correlated the three wind products with the distribution of Barchan and Seif dunes to assess which of the wind regimes can best explain the observed distribution of the Barchan dunes in Riyadh and Mecca.

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Layer: Composite_U100_V100_July_Mean_WM.tif (10)

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Description: Monthly mean near-surface winds from the ERA5 reanalysis dataset were analyzed to further constrain the seasonal variability of wind patterns influencing dune morphology. The average summer winds (year: 1940–2025; month: July) (Fig. 4, Report #2). It was found that the summer wind product, hereafter referred to as the dominant wind direction, can best account for the overall distribution of Barchan dunes and Seif dunes across the KSA, including Mecca and Riyadh Provinces.

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Layer: Wind_Pattern_Arabian_Peninsula (11)

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Description: We used autoRIFT (Lei et al., 2021; Gardner et al., 2018), an open-source software package, to track dune migration between 2000 and 2023 using the Landsat panchromatic image catalog over the Riyadh and Mecca provinces. AutoRIFT is a feature-tracking algorithm that measures and geocodes inter-image displacements in optical or radar remote sensing imagery. It detects pixel offsets between two images captured at different times using the normalized cross-correlation (NCC) method (Gardner et al., 2018)—a statistical similarity measure that identifies optimal pixel shifts by comparing reference and template image patches. The NCC process evaluates the correlation between pixel intensity patterns and identifies the displacement corresponding to the peak correlation value using a Gaussian pyramid-based oversampling technique. The method employs a nested grid approach with progressively larger chip sizes to optimize resolution and signal-to-noise ratio. This sparse-to-dense search strategy enables the exclusion of low-coherence regions (Lei et al., 2021).To implement this methodology in tracking dune migration over the Mecca and Riyadh provinces, we selected cloud-free Landsat image pairs (2000–2023) from similar dates and seasons to minimize illumination differences due to shadows, topography, and sun angle elevation. Landsat scenes from the same date, path, and UTM zone were mosaicked and processed to avoid reprojection-related offsets and ensure a seamless mosaic. The generated offset images in the X and Y directions for each image pair were merged to produce a consistent displacement mosaic for the entire study area.Lei, Y., Gardner, A. and Agram, P., 2021. Autonomous Repeat Image Feature Tracking (autoRIFT) and Its Application for Tracking Ice Displacement. Remote Sensing, 13(4), p.749.

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