Existing Input Features: Sentinel2 BANDS (0 - 12) and GM, GNDVI, IRECI, NDI45, NDVINB, RECHI, REM, REPLI, RVI, S2REP; Existing annotations: Point_ID, Revisited_point, Coarse, Clay, Sand, Silt, pH(CaCl2), pH(H2O), EC, OC, CaCO3, P, N, K, Elevation, LC1_x, LU1_x, Soil_Stones, NUTS_0, NUTS_1, NUTS_2, NUTS_3, LC1_Desc, LU1_Desc, ID, POINT_ID, YEAR, NUTS0, NUTS1, NUTS2, NUTS3, TH_LAT, TH_LONG, OFFICE_PI, EX_ANTE, SURVEY_DATE, CAR_LATITUDE, CAR_EW, CAR_LONGITUDE, GPS_PROJ, GPS_PREC, GPS_ALTITUDE, GPS_LAT, GPS_EW, GPS_LONG, OBS_DIST, OBS_DIRECT, OBS_TYPE, OBS_RADIUS, LETTER_GROUP, LC1_y, LC1_LABEL, LC1_SPEC, LC1_SPEC_LABEL, LC1_PERC, LC2, LC2_LABEL, LC2_SPEC, LC2_SPEC_LABEL, LC2_PERC, LU1_y, LU1_LABEL, LU1_TYPE, LU1_TYPE_LABEL, LU1_PERC, LU2, LU2_LABEL, LU2_TYPE, LU2_TYPE_LABEL, LU2_PERC, PARCEL_AREA_HA, TREE_HEIGHT_MATURITY, TREE_HEIGHT_SURVEY, FEATURE_WIDTH, LM_STONE_WALLS, CROP_RESIDUES, LM_GRASS_MARGINS, GRAZING, SPECIAL_STATUS, LC_LU_SPECIAL_REMARK, CPRN_CANDO, CPRN_LC, CPRN_LC_LABEL, CPRN_LC1N, CPRNC_LC1E, CPRNC_LC1S, CPRNC_LC1W, CPRN_LC1N_BRDTH, CPRN_LC1E_BRDTH, CPRN_LC1S_BRDTH, CPRN_LC1W_BRDTH, CPRN_LC1N_NEXT, CPRN_LC1S_NEXT, CPRN_LC1E_NEXT, CPRN_LC1W_NEXT, CPRN_URBAN, CPRN_IMPERVIOUS_PERC, INSPIRE_PLCC1, INSPIRE_PLCC2, INSPIRE_PLCC3, INSPIRE_PLCC4, INSPIRE_PLCC5, INSPIRE_PLCC6, INSPIRE_PLCC7, INSPIRE_PLCC8, EUNIS_COMPLEX, GRASSLAND_SAMPLE, GRASS_CANDO, WM, WM_SOURCE, WM_TYPE, WM_DELIVERY, EROSION_CANDO, SOIL_STONES_PERC, BIO_SAMPLE, SOIL_BIO_TAKEN, BULK0_10_SAMPLE, SOIL_BLK_0_10_TAKEN, BULK10_20_SAMPLE, SOIL_BLK_10_20_TAKEN, BULK20_30_SAMPLE, SOIL_BLK_20_30_TAKEN, STANDARD_SAMPLE, SOIL_STD_TAKEN, ORGANIC_SAMPLE, SOIL_ORG_DEPTH_CANDO, SOIL_TAKEN, SOIL_CROP, PHOTO_POINT, PHOTO_NORTH, PHOTO_SOUTH, PHOTO_EAST, PHOTO_WEST, TRANSECT, REVISIT, TH_GPS_DIST, FILE_PATH_GISCO_NORTH, FILE_PATH_GISCO_SOUTH, FILE_PATH_GISCO_EAST, FILE_PATH_GISCO_WEST, FILE_PATH_GISCO_POINT, CPRN_LC_SAME_LC1, LUCAS_CORE_INTERSECT, COPERNICUS_CLEANED, geometry, pop_est, name, iso_a3, gdp_md_est

Dataset used in TerraSenseTK - Towards Reproducible Machine-Learning and Remote Sensing Research. Nutrient Estimation in Common wheat Case Study available in the notebook Documentation is available in here.