Results of ensemble model fitting 'ranger', 'xgboost', 'glmnet', 'deepnet': Variable: log.p_mehlich3 R-square: 0.486 Fitted values sd: 0.687 RMSE: 0.707 Random forest model: Call: stats::lm(formula = f, data = d) Residuals: Min 1Q Median 3Q Max -3.2892 -0.3942 -0.0637 0.2614 4.9466 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 3.378801 3.143200 1.075 0.282 regr.ranger 0.861655 0.011099 77.631 < 2e-16 *** regr.xgboost 0.066139 0.013091 5.052 4.38e-07 *** regr.cubist 0.157674 0.008886 17.744 < 2e-16 *** regr.nnet -1.649621 1.442240 -1.144 0.253 regr.cvglmnet 0.013628 0.010407 1.310 0.190 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 0.7066 on 53493 degrees of freedom Multiple R-squared: 0.486, Adjusted R-squared: 0.486 F-statistic: 1.012e+04 on 5 and 53493 DF, p-value: < 2.2e-16 Variable importance: variable importance 14 clm_precipitation_sm2rain.jun_m_1km_s0..0cm_2007..2018_v0.2.tif 2864.4507 336 hzn_depth 1302.1635 227 dtm_rough.magnitude_merit.dem_m_250m_s0..0cm_2018_v1.0.tif 1050.8439 325 dtm_vertical.depth_aw3d30.nasadem.100m_m_30m_s0..0cm_2017_v0.1.tif 972.4168 160 clm_bioclim.var_chelsa.14_m_1km_s0..0cm_1979..2013_v1.0.tif 892.9976 164 clm_bioclim.var_chelsa.3_m_1km_s0..0cm_1979..2013_v1.0.tif 884.0819 165 clm_bioclim.var_chelsa.4_m_1km_s0..0cm_1979..2013_v1.0.tif 775.3970 1 clm_precipitation_sm2rain.annual_m_1km_s0..0cm_2007..2018_v0.2.tif 718.7164 168 clm_bioclim.var_chelsa.7_m_1km_s0..0cm_1979..2013_v1.0.tif 682.3064 22 clm_precipitation_sm2rain.oct_m_1km_s0..0cm_2007..2018_v0.2.tif 550.2259 85 lcv_surf.refl.b02_mod09a1.pc3_m_500m_s0..0cm_2001_v1.0.tif 550.1456 277 clm_cloud.fraction_earthenv.modis.may_p_1km_s0..0cm_2000..2015_v1.0.tif 542.4723 274 clm_cloud.fraction_earthenv.modis.jul_p_1km_s0..0cm_2000..2015_v1.0.tif 530.8185 30 clm_lst_mod11a2.apr.day_sd_1km_s0..0cm_2000..2017_v1.0.tif 497.0550 283 lcv_landsat.nir_wri.forestwatch_m_30m_s0..0cm_2018_v1.0.tif 487.3369 31 clm_lst_mod11a2.apr.daynight_m_1km_s0..0cm_2000..2017_v1.0.tif 439.1131 329 lcv_b12_sentinel.s2l2a_iqr_30m_s0..0cm_2018..2019.s12_v0.1.tif 436.5929 184 clm_diffuse.irradiation_solar.atlas.kwhm2.100_m_1km_s0..0cm_2016_v1.tif 431.1487 27 clm_lst_mod11a2.annual.day_sd_1km_s0..0cm_2000..2017_v1.0.tif 415.0181 4 clm_precipitation_sm2rain.aug_m_1km_s0..0cm_2007..2018_v0.2.tif 388.7653 59 clm_lst_mod11a2.mar.daynight_m_1km_s0..0cm_2000..2017_v1.0.tif 388.5768 333 veg_f02dar.hv_alos.palsar_m_30m_s0..0cm_2017_v1.0.tif 388.0191 321 lcv_b09_sentinel.s2l2a_iqr_30m_s0..0cm_2018..2019.s22_v0.1.tif 387.2811 163 clm_bioclim.var_chelsa.2_m_1km_s0..0cm_1979..2013_v1.0.tif 380.3644 39 clm_lst_mod11a2.dec.daynight_m_1km_s0..0cm_2000..2017_v1.0.tif 376.1103 229 dtm_roughness_merit.dem_m_250m_s0..0cm_2018_v1.0.tif 375.9394 20 clm_precipitation_sm2rain.nov_m_1km_s0..0cm_2007..2018_v0.2.tif 374.3861 208 dtm_vbf_merit.dem_m_1km_s0..0cm_2017_v1.0.tif 369.5684 281 veg_f02dar.hh_alos.palsar_m_30m_s0..0cm_2007_v1.0.tif 368.8913 129 veg_fapar_proba.v.jul_r_250m_s0..0cm_2014..2019_v1.0.tif 364.5444 114 veg_fapar_proba.v.aug_l.025_250m_s0..0cm_2014..2019_v1.0.tif 363.7978 38 clm_lst_mod11a2.dec.day_sd_1km_s0..0cm_2000..2017_v1.0.tif 361.3844 43 clm_lst_mod11a2.feb.daynight_m_1km_s0..0cm_2000..2017_v1.0.tif 360.1045 34 clm_lst_mod11a2.aug.day_sd_1km_s0..0cm_2000..2017_v1.0.tif 357.4737 6 clm_precipitation_sm2rain.dec_m_1km_s0..0cm_2007..2018_v0.2.tif 354.1600 19 clm_precipitation_sm2rain.may_sd.10_10km_s0..0cm_2007..2018_v1.0.tif 351.1124 331 dtm_uplocal_aw3d30.nasadem.100m_m_30m_s0..0cm_2017_v0.1.tif 350.8357 192 dtm_dvm2_merit.dem_m_1km_s0..0cm_2017_v1.0.tif 350.3820 80 lcv_surf.refl.b01_mod09a1.pc4_m_500m_s0..0cm_2001_v1.0.tif 344.6165 272 clm_cloud.fraction_earthenv.modis.feb_p_1km_s0..0cm_2000..2015_v1.0.tif 341.1547 89 lcv_surf.refl.b05_mod09a1.pc1_m_500m_s0..0cm_2001_v1.0.tif 335.4151 288 dtm_devmean_aw3d30.nasadem.100m_m_30m_s0..0cm_2017_v0.1.tif 334.3574 53 clm_lst_mod11a2.jun.day_m_1km_s0..0cm_2000..2017_v1.0.tif 332.1994 300 lcv_b11_sentinel.s2l2a_d_30m_s0..0cm_2018..2019.s12_v0.1.tif 328.5600 231 dtm_tcurv_merit.dem_m_250m_s0..0cm_2018_v1.0.tif 327.6651 327 lcv_b8a_sentinel.s2l2a_d_30m_s0..0cm_2018..2019.s22_v0.1.tif 327.3327 313 dtm_devmean2_aw3d30.nasadem.100m_m_30m_s0..0cm_2017_v0.1.tif 326.0274 273 clm_cloud.fraction_earthenv.modis.jan_p_1km_s0..0cm_2000..2015_v1.0.tif 324.3382 191 dtm_dvm_merit.dem_m_2km_s0..0cm_2017_v1.0.tif 321.2799 54 clm_lst_mod11a2.jun.day_sd_1km_s0..0cm_2000..2017_v1.0.tif 317.4992