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    ARTICLE

    Digital Soil Mapping (DSM) Using a GIS-Based RF Machine Learning Model: The Case of Strandzha Mountains (Thrace Peninsula, Türkiye)

    Emre Ozsahin1,*, Huseyin Sarı2, Duygu Boyraz Erdem2, Mikayil Ozturk2

    Revue Internationale de Géomatique, Vol.33, pp. 341-361, 2024, DOI:10.32604/rig.2024.054197

    Abstract This study assessed and mapped the spatial distribution of soil types and properties developed under the forest cover of the Strandzha Mountains of Türkiye. The study was conducted on a micro-scale in the riparian zone of the Balaban River, which characterizes the soils distributed in the mountainous area. The effect of environmental factors on the spatial distribution of soil types and properties was also determined. To gather data, soil sampling, laboratory analysis, data processing and mapping were sequentially performed. These data were analyzed using the Geographical Information System (GIS) based Random Forest (RF) machine learning… More > Graphic Abstract

    Digital Soil Mapping (DSM) Using a GIS-Based RF Machine Learning Model: The Case of Strandzha Mountains (Thrace Peninsula, Türkiye)

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