In the context of the EU-funded project DIONE (No. 870378), VNIR topsoil reflectance was captured with DIONE’s Soil Scanning System and transformed through Machine Learning modelling to a set of soil properties that are meaningful for the assessment of soil health. The captured reflectance measurements correspond to locations distributed within the pilot areas of Lithuania and are indicated after the analysis of EO multispectral imagery, aiming to create a collection of point locations that well represent the soil characteristics of the area, and provide valuable information about soil condition through the estimations of the following soil properties: Sand % Clay % Silt % Electrical Conductivity (mS/m) pH Calcium carbonate % Soil Organic Carbon % The dataset is delivered in a shapefile format (DIONE_LT_point_estimations_2021.shp - EPSG:4326 - WGS 84) containing the following fields: Description of the information contained in the corresponding "LTH points estimations" dataset Field Type Description Sample_ID String Unique ID lat Real Latitude lon Real Longitude Sand Real Sand fraction Clay Real Clay fraction Silt Real Silt fraction EC Real Electrical Conductivity pH_H20 Real pH CaCO3 Real Calcium Carbonate SOC Real Soil Organic Carbon