Name Thomas Scholten Affiliation پژوهشگر خارجی Degree _ Website Email — JournalPaper Presentation Speech WorkShop Book Innovation GrantAttraction Thesis Festival FinishedProject Sales Art StandardCreation TitleJournal 1 Comparing UAV-Based Hyperspectral and Satellite-Based Multispectral Data for Soil Moisture Estimation Using Machine Learning Water 2 Random Forest-Based Soil Moisture Estimation Using Sentinel-2, Landsat-8/9, and UAV-Based Hyperspectral Data Remote sensing 3 Assessment of Land Suitability Potential Using Ensemble Approaches of Advanced Multi-Criteria Decision Models and Machine Learning for Wheat Cultivation Remote Sensing 4 High-performance soil class delineation via UMAP coupled with machine learning in Kurdistan Province, Iran Geoderma Regional 5 Spatial prediction of soil properties through hybridized random forest model and combination of reflectance spectroscopy and environmental covariates Geocarto International 6 Land Use and Soil Organic Carbon Stocks—Change Detection over Time Using Digital Soil Assessment: A Case Study from Kamyaran Region, Iran (1988–2018) Agronomy-Basel 7 Assessing agricultural salt-affected land using digital soil mapping and hybridized random forests GEODERMA 8 Land Suitability Assessment and Agricultural Production Sustainability Using Machine Learning Models Agronomy-Basel