berne.grid: Berne - very small extract of prediction grid
In geoGAM: Select Sparse Geoadditive Models for Spatial Prediction
berne.grid R Documentation
Berne – very small extract of prediction grid
Description
The Berne grid dataset contains values of spatial covariates on the nodes of a 20 m grid. The dataset is intended for spatial continouous predictions of soil properties modelled from the sampling locations in berne dataset.
Usage
data("berne")
Format
A data frame with 4594 observations on the following 228 variables.
idnode identifier number.
xeasting, Swiss grid in m, EPSG: 21781 (CH1903/LV03)
ynorthing, Swiss grid in m, EPSG: 21781 (CH1903/LV03)
cl_mt_etap_pecolumns 4 to 228 contain environmental covariates representing soil forming factors. For more information see Details in berne.
cl_mt_etap_rocl_mt_gh_1cl_mt_gh_10cl_mt_gh_11cl_mt_gh_12cl_mt_gh_2cl_mt_gh_3cl_mt_gh_4cl_mt_gh_5cl_mt_gh_6cl_mt_gh_7cl_mt_gh_8cl_mt_gh_9cl_mt_gh_ycl_mt_pet_pecl_mt_pet_rocl_mt_rr_1cl_mt_rr_10cl_mt_rr_11cl_mt_rr_12cl_mt_rr_2cl_mt_rr_3cl_mt_rr_4cl_mt_rr_5cl_mt_rr_6cl_mt_rr_7cl_mt_rr_8cl_mt_rr_9cl_mt_rr_ycl_mt_swb_pecl_mt_swb_rocl_mt_td_1cl_mt_td_10cl_mt_td_11cl_mt_td_12cl_mt_td_2cl_mt_tt_1cl_mt_tt_11cl_mt_tt_12cl_mt_tt_3cl_mt_tt_4cl_mt_tt_5cl_mt_tt_6cl_mt_tt_7cl_mt_tt_8cl_mt_tt_9cl_mt_tt_yge_caco3ge_geo500h1idge_geo500h3idge_gt_ch_filge_lgmge_vszonesl_nutr_filsl_physio_neusl_retention_filsl_skelett_r_filsl_wet_filtr_be_gwn25_hdisttr_be_gwn25_vdisttr_be_twi2m_7s_tcilowtr_be_twi2m_s60_tcilowtr_ch_3_80_10tr_ch_3_80_10str_ch_3_80_20str_cindx10_25tr_cindx50_25tr_curv_alltr_curv_plantr_curv_proftr_enessktr_es25tr_flowlength_uptr_global_rad_chtr_lsftr_mrrtf25tr_mrvbf25tr_ndom_veg2m_fmtr_negotr_nnessktr_ns25tr_ns25_145mntr_ns25_145sdtr_ns25_75mntr_ns25_75sdtr_posotr_protindxtr_se_alti10m_ctr_se_alti25m_ctr_se_alti2m_fmean_10ctr_se_alti2m_fmean_25ctr_se_alti2m_fmean_50ctr_se_alti2m_fmean_5ctr_se_alti2m_std_10ctr_se_alti2m_std_25ctr_se_alti2m_std_50ctr_se_alti2m_std_5ctr_se_alti50m_ctr_se_alti6m_ctr_se_conv2mtr_se_curv10mtr_se_curv25mtr_se_curv2mtr_se_curv2m_s15tr_se_curv2m_s30tr_se_curv2m_s60tr_se_curv2m_s7tr_se_curv2m_std_10ctr_se_curv2m_std_25ctr_se_curv2m_std_50ctr_se_curv2m_std_5ctr_se_curv50mtr_se_curv6mtr_se_curvplan10mtr_se_curvplan25mtr_se_curvplan2mtr_se_curvplan2m_grass_17ctr_se_curvplan2m_grass_45ctr_se_curvplan2m_grass_9ctr_se_curvplan2m_s15tr_se_curvplan2m_s30tr_se_curvplan2m_s60tr_se_curvplan2m_s7tr_se_curvplan2m_std_10ctr_se_curvplan2m_std_25ctr_se_curvplan2m_std_50ctr_se_curvplan2m_std_5ctr_se_curvplan50mtr_se_curvplan6mtr_se_curvprof10mtr_se_curvprof25mtr_se_curvprof2mtr_se_curvprof2m_grass_17ctr_se_curvprof2m_grass_45ctr_se_curvprof2m_grass_9ctr_se_curvprof2m_s15tr_se_curvprof2m_s30tr_se_curvprof2m_s60tr_se_curvprof2m_s7tr_se_curvprof2m_std_10ctr_se_curvprof2m_std_25ctr_se_curvprof2m_std_50ctr_se_curvprof2m_std_5ctr_se_curvprof50mtr_se_curvprof6mtr_se_diss2m_10ctr_se_diss2m_25ctr_se_diss2m_50ctr_se_diss2m_5ctr_se_e_aspect10mtr_se_e_aspect25mtr_se_e_aspect2mtr_se_e_aspect2m_10ctr_se_e_aspect2m_25ctr_se_e_aspect2m_50ctr_se_e_aspect2m_5ctr_se_e_aspect2m_grass_17ctr_se_e_aspect2m_grass_45ctr_se_e_aspect2m_grass_9ctr_se_e_aspect50mtr_se_e_aspect6mtr_se_mrrtf2mtr_se_mrvbf2mtr_se_n_aspect10mtr_se_n_aspect25mtr_se_n_aspect2mtr_se_n_aspect2m_10ctr_se_n_aspect2m_25ctr_se_n_aspect2m_50ctr_se_n_aspect2m_5ctr_se_n_aspect2m_grass_17ctr_se_n_aspect2m_grass_45ctr_se_n_aspect2m_grass_9ctr_se_n_aspect50mtr_se_n_aspect6mtr_se_no2m_r500tr_se_po2m_r500tr_se_rough2m_10ctr_se_rough2m_25ctr_se_rough2m_50ctr_se_rough2m_5ctr_se_rough2m_rect3ctr_se_sar2mtr_se_sca2mtr_se_slope10mtr_se_slope25mtr_se_slope2mtr_se_slope2m_grass_17ctr_se_slope2m_grass_45ctr_se_slope2m_grass_9ctr_se_slope2m_s15tr_se_slope2m_s30tr_se_slope2m_s60tr_se_slope2m_s7tr_se_slope2m_std_10ctr_se_slope2m_std_25ctr_se_slope2m_std_50ctr_se_slope2m_std_5ctr_se_slope50mtr_se_slope6mtr_se_toposcale2m_r3_r50_i10str_se_tpi_2m_10ctr_se_tpi_2m_25ctr_se_tpi_2m_50ctr_se_tpi_2m_5ctr_se_tri2m_altern_3ctr_se_tsc10_2mtr_se_twi2mtr_se_twi2m_s15tr_se_twi2m_s30tr_se_twi2m_s60tr_se_twi2m_s7tr_se_vrm2mtr_se_vrm2m_r10ctr_slope25_l2gtr_terrtexturtr_tpi2000ctr_tpi5000ctr_tpi500ctr_tsc25_18tr_tsc25_40tr_twi2tr_twi_normaltr_vdcn25
Details
Due to CRAN file size restrictions the grid for spatial predictions only shows a very small excerpt of the original study area.
The environmental covariates for prediction of soil properties from dataset berne were extracted at the nodes of a 20 m grid. For higher resolution geodata sets no averaging over the area of the 20x20 pixel was done. Berne.grid therefore has the same spatial support for each covariate as berne.
For more information on the environmental covariates see berne.
References
Nussbaum, M., Spiess, K., Baltensweiler, A., Grob, U., Keller, A., Greiner, L., Schaepman, M. E., and Papritz, A.: Evaluation of digital soil mapping approaches with large sets of environmental covariates, SOIL, 4, 1-22, doi:10.5194/soil-4-1-2018, 2018.
Examples
data(berne.grid)
geoGAM documentation built on Nov. 15, 2023, 1:09 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
| berne.grid | R Documentation |
Berne – very small extract of prediction grid
Description
The Berne grid dataset contains values of spatial covariates on the nodes of a 20 m grid. The dataset is intended for spatial continouous predictions of soil properties modelled from the sampling locations in berne dataset.
Usage
data("berne")Format
A data frame with 4594 observations on the following 228 variables.
idnode identifier number.
xeasting, Swiss grid in m, EPSG: 21781 (CH1903/LV03)
ynorthing, Swiss grid in m, EPSG: 21781 (CH1903/LV03)
cl_mt_etap_pecolumns 4 to 228 contain environmental covariates representing soil forming factors. For more information see
Detailsinberne.cl_mt_etap_rocl_mt_gh_1cl_mt_gh_10cl_mt_gh_11cl_mt_gh_12cl_mt_gh_2cl_mt_gh_3cl_mt_gh_4cl_mt_gh_5cl_mt_gh_6cl_mt_gh_7cl_mt_gh_8cl_mt_gh_9cl_mt_gh_ycl_mt_pet_pecl_mt_pet_rocl_mt_rr_1cl_mt_rr_10cl_mt_rr_11cl_mt_rr_12cl_mt_rr_2cl_mt_rr_3cl_mt_rr_4cl_mt_rr_5cl_mt_rr_6cl_mt_rr_7cl_mt_rr_8cl_mt_rr_9cl_mt_rr_ycl_mt_swb_pecl_mt_swb_rocl_mt_td_1cl_mt_td_10cl_mt_td_11cl_mt_td_12cl_mt_td_2cl_mt_tt_1cl_mt_tt_11cl_mt_tt_12cl_mt_tt_3cl_mt_tt_4cl_mt_tt_5cl_mt_tt_6cl_mt_tt_7cl_mt_tt_8cl_mt_tt_9cl_mt_tt_yge_caco3ge_geo500h1idge_geo500h3idge_gt_ch_filge_lgmge_vszonesl_nutr_filsl_physio_neusl_retention_filsl_skelett_r_filsl_wet_filtr_be_gwn25_hdisttr_be_gwn25_vdisttr_be_twi2m_7s_tcilowtr_be_twi2m_s60_tcilowtr_ch_3_80_10tr_ch_3_80_10str_ch_3_80_20str_cindx10_25tr_cindx50_25tr_curv_alltr_curv_plantr_curv_proftr_enessktr_es25tr_flowlength_uptr_global_rad_chtr_lsftr_mrrtf25tr_mrvbf25tr_ndom_veg2m_fmtr_negotr_nnessktr_ns25tr_ns25_145mntr_ns25_145sdtr_ns25_75mntr_ns25_75sdtr_posotr_protindxtr_se_alti10m_ctr_se_alti25m_ctr_se_alti2m_fmean_10ctr_se_alti2m_fmean_25ctr_se_alti2m_fmean_50ctr_se_alti2m_fmean_5ctr_se_alti2m_std_10ctr_se_alti2m_std_25ctr_se_alti2m_std_50ctr_se_alti2m_std_5ctr_se_alti50m_ctr_se_alti6m_ctr_se_conv2mtr_se_curv10mtr_se_curv25mtr_se_curv2mtr_se_curv2m_s15tr_se_curv2m_s30tr_se_curv2m_s60tr_se_curv2m_s7tr_se_curv2m_std_10ctr_se_curv2m_std_25ctr_se_curv2m_std_50ctr_se_curv2m_std_5ctr_se_curv50mtr_se_curv6mtr_se_curvplan10mtr_se_curvplan25mtr_se_curvplan2mtr_se_curvplan2m_grass_17ctr_se_curvplan2m_grass_45ctr_se_curvplan2m_grass_9ctr_se_curvplan2m_s15tr_se_curvplan2m_s30tr_se_curvplan2m_s60tr_se_curvplan2m_s7tr_se_curvplan2m_std_10ctr_se_curvplan2m_std_25ctr_se_curvplan2m_std_50ctr_se_curvplan2m_std_5ctr_se_curvplan50mtr_se_curvplan6mtr_se_curvprof10mtr_se_curvprof25mtr_se_curvprof2mtr_se_curvprof2m_grass_17ctr_se_curvprof2m_grass_45ctr_se_curvprof2m_grass_9ctr_se_curvprof2m_s15tr_se_curvprof2m_s30tr_se_curvprof2m_s60tr_se_curvprof2m_s7tr_se_curvprof2m_std_10ctr_se_curvprof2m_std_25ctr_se_curvprof2m_std_50ctr_se_curvprof2m_std_5ctr_se_curvprof50mtr_se_curvprof6mtr_se_diss2m_10ctr_se_diss2m_25ctr_se_diss2m_50ctr_se_diss2m_5ctr_se_e_aspect10mtr_se_e_aspect25mtr_se_e_aspect2mtr_se_e_aspect2m_10ctr_se_e_aspect2m_25ctr_se_e_aspect2m_50ctr_se_e_aspect2m_5ctr_se_e_aspect2m_grass_17ctr_se_e_aspect2m_grass_45ctr_se_e_aspect2m_grass_9ctr_se_e_aspect50mtr_se_e_aspect6mtr_se_mrrtf2mtr_se_mrvbf2mtr_se_n_aspect10mtr_se_n_aspect25mtr_se_n_aspect2mtr_se_n_aspect2m_10ctr_se_n_aspect2m_25ctr_se_n_aspect2m_50ctr_se_n_aspect2m_5ctr_se_n_aspect2m_grass_17ctr_se_n_aspect2m_grass_45ctr_se_n_aspect2m_grass_9ctr_se_n_aspect50mtr_se_n_aspect6mtr_se_no2m_r500tr_se_po2m_r500tr_se_rough2m_10ctr_se_rough2m_25ctr_se_rough2m_50ctr_se_rough2m_5ctr_se_rough2m_rect3ctr_se_sar2mtr_se_sca2mtr_se_slope10mtr_se_slope25mtr_se_slope2mtr_se_slope2m_grass_17ctr_se_slope2m_grass_45ctr_se_slope2m_grass_9ctr_se_slope2m_s15tr_se_slope2m_s30tr_se_slope2m_s60tr_se_slope2m_s7tr_se_slope2m_std_10ctr_se_slope2m_std_25ctr_se_slope2m_std_50ctr_se_slope2m_std_5ctr_se_slope50mtr_se_slope6mtr_se_toposcale2m_r3_r50_i10str_se_tpi_2m_10ctr_se_tpi_2m_25ctr_se_tpi_2m_50ctr_se_tpi_2m_5ctr_se_tri2m_altern_3ctr_se_tsc10_2mtr_se_twi2mtr_se_twi2m_s15tr_se_twi2m_s30tr_se_twi2m_s60tr_se_twi2m_s7tr_se_vrm2mtr_se_vrm2m_r10ctr_slope25_l2gtr_terrtexturtr_tpi2000ctr_tpi5000ctr_tpi500ctr_tsc25_18tr_tsc25_40tr_twi2tr_twi_normaltr_vdcn25
Details
Due to CRAN file size restrictions the grid for spatial predictions only shows a very small excerpt of the original study area.
The environmental covariates for prediction of soil properties from dataset berne were extracted at the nodes of a 20 m grid. For higher resolution geodata sets no averaging over the area of the 20x20 pixel was done. Berne.grid therefore has the same spatial support for each covariate as berne.
For more information on the environmental covariates see berne.
References
Nussbaum, M., Spiess, K., Baltensweiler, A., Grob, U., Keller, A., Greiner, L., Schaepman, M. E., and Papritz, A.: Evaluation of digital soil mapping approaches with large sets of environmental covariates, SOIL, 4, 1-22, doi:10.5194/soil-4-1-2018, 2018.
Examples
data(berne.grid)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.