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            <header>
                <identifier>oai:data.mendeley.com/8dgyv8vz4h.2</identifier>
                <datestamp>2025-08-01T13:42:29Z</datestamp>
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            <metadata><oai_dc:dc xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
    <dc:creator id="https://orcid.org/0000-0002-5269-7829">Soleimani, Masoud</dc:creator>
    <dc:title>Regional dust-impacted areas originating from eastern Iran identified via visual interpretation of MODIS Terra/Aqua imagery (2000–2023)</dc:title>
    <dc:publisher>Mendeley Data</dc:publisher>
    <dc:description>This dataset contains polygon features representing dust-impacted areas originating from eastern Iran and affecting parts of Southwest Asia between 2000 and 2023. Dust plumes were identified through visual interpretation of sub-daily MODIS Terra/Aqua true-color composite (RGB) imagery using NASA’s EOSDIS Worldview platform. On-screen digitizing in a Geographic Information System (GIS) environment was used to delineate the spatial extent of each dust event based on plume dispersion from identified dust hotspots.
To enhance temporal accuracy, imagery from both Terra (~10:30 local time) and Aqua (~13:30 local time) satellites was used, improving detection during daylight hours. Spatial and temporal clustering of adjacent dust hotspots was performed to group them into individual dust events. For multi-day events, the largest visible extent, captured before plume dissipation, was selected as the final footprint.
Each polygon in the dataset is linked to metadata attributes, including the date of occurrence, total affected area, and a unique event ID corresponding to the clustered dust hotspots. The data are provided in standard GIS-compatible formats and include spatiotemporal attributes suitable for environmental, climatological, and hazard-related analyses.</dc:description>
    <dc:subject>Geographic Information System</dc:subject>
    <dc:subject>Visual Analytics</dc:subject>
    <dc:subject>Image Visualization</dc:subject>
    <dc:subject>GIS Database</dc:subject>
    <dc:subject>Hazard Analysis</dc:subject>
    <dc:subject>Satellite Remote Sensing</dc:subject>
    <dc:subject>Geoinformatics</dc:subject>
    <dc:subject>Iran</dc:subject>
    <dc:subject>Optical Remote Sensing</dc:subject>
    <dc:subject>Remote Sensing Application</dc:subject>
    <dc:subject>Dust Storm</dc:subject>
    <dc:subject>Satellite Image</dc:subject>
    <dc:subject>Dust Emission</dc:subject>
    <dc:contributor id="https://orcid.org/0000-0002-6272-9409">Darvishi Boloorani, Ali</dc:contributor>
    <dc:contributor id="https://orcid.org/0009-0006-3591-6934">Amiri, Fatemeh</dc:contributor>
    <dc:contributor id="https://orcid.org/0009-0007-3403-3993">Nasiri, Nastaran</dc:contributor>
    <dc:type>Dataset</dc:type>
    <dc:identifier>doi:10.17632/8dgyv8vz4h.2</dc:identifier>
    <dc:identifier>oai:data.mendeley.com/8dgyv8vz4h.2</dc:identifier>
    <dc:rights>Creative Commons Attribution 4.0 International</dc:rights>
    <dc:rights>http://creativecommons.org/licenses/by/4.0</dc:rights>
    <dc:relation>https://data.mendeley.com/datasets/8dgyv8vz4h</dc:relation>
    <dc:date>2025-08-01T13:42:29Z</dc:date>
</oai_dc:dc></metadata>
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