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Abstract: A hybrid Remote sensing framework integrating Machine Learning and Decision models for sediment sampling suitability in support of OSL-based Geochronology in Karakum and Kyzylkum Sandy Deserts, Central Asia (AGU25)

A hybrid Remote sensing framework integrating Machine Learning and Decision models for sediment sampling suitability in support of OSL-based Geochronology in Karakum and Kyzylkum Sandy Deserts, Central Asia

Seifu Woldemichael Busho1, Leah Orlovsky1, Shimrit Maman2 and Dan Blumberg3, (1)Ben-Gurion University of the Negev, Jacob Blaustein Institutes for Desert Research, Sede-Boker campus, Israel, (2)Ben-Gurion University of the Negev, Homeland Security Research Institute, Beer Sheva, Israel, (3)Ben-Gurion University of the Negev, The Department of Environmental, Geoinformatics and Urban Planning Sciences, Beer Sheva, Israel
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