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Preview the ordered feature importance results for datasets “HR” and “VI”.

# A tibble: 122 x 5
   feature importance wavelength numeric_id  rank
   <chr>        <dbl>      <dbl>      <dbl> <int>
 1 B69          1.57        724          69     1
 2 B70          1.28        729.         70     2
 3 B126         1.26        995.        126     3
 4 B115         1.11        942.        115     4
 5 B68          1.01        719.         68     5
 6 B7           0.953       430.          7     6
 7 B71          0.951       734.         71     7
 8 B67          0.874       714.         67     8
 9 B113         0.837       933         113     9
10 B124         0.773       985.        124    10
# … with 112 more rows
# A tibble: 89 x 3
   feature    importance  rank
   <chr>           <dbl> <int>
 1 Vogelmann2      1.79      1
 2 Vogelmann4      1.47      2
 3 Vogelmann       0.914     3
 4 NPCI            0.717     4
 5 Vogelmann3      0.707     5
 6 D2              0.657     6
 7 Datt3           0.637     7
 8 PWI             0.545     8
 9 SR7             0.526     9
10 SRPI            0.509    10
# … with 79 more rows

Create a virtual spectral signature of vegetation using PROSAIL.

PROSAIL is a algorithm simulating spectral signatures of vegetation, see ?hsdar::PROSAIL. Reflectance is scaled to 0-10 to be able to plot it in the same plot as the feature importance rankings -> the axis limits for the y and z axis needs to match.

PROSAIL returns a spectral signature from 400 nm to 2500 nm -> we take the values only and subset to 400 nm - 1000 nm. Because we order from 1 - 10 with 1 being the best rank, we have to reverse the scaling of the reflectance values.

Next we bind the simulated data with the feature importance rankings. To join both data.frames we need to round the reflectance centers of the bands to integers to match with the reflectance values created by PROSAIL.

To label only a subset of the data, a custom data.frame is created.

P1 Main plot

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Plots by dataset

HR

P2 Absolute permutation based Var Imp

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VI

P3 Absolute permutation based Var Imp

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Vogelmann2 \((R_{734}-R_{747})/(R_{715}+R_{726})\) Vogelmann et al. (1993)

Vogelmann4 \((R_{734}-R_{747})/(R_{715}+R_{720})\) Vogelmann et al. (1993)

Vogelmann3 \(D_{715}/D_{705}\) Vogelmann et al. (1993)

Vogelmann \(R_{740}/R_{720}\) Vogelmann et al. (1993)

NPCI \((R_{680}-R_{430})/(R_{680}+R_{430})\)

D2 \(D_{705}/D_{722}\)

Datt3 \(D_{754}/D_{704}\)

PWI \(R_{900}/R_{970}\)

SR7 \(R_{440}/R_{690}\)

SRPI \(R_{430}/R_{680}\)

Dxxx: First derivation of reflectance values at wavelength ‘xxx’. Rxxx: Reflectance at wavelength ‘xxx’.

Reference: ?hsdar::vegindex()

Combined

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ALE plots

ALE plots via package {iml}

P2 HR

Grid size: 100

Top ten HR features from permutation Vimp

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Grid size: 20

Top ten HR features from permutation Vimp

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P3 VI

Grid size: 100

Top ten VI features from permutation Vimp

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Grid size: 20

Top ten HR features from permutation Vimp

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R version 3.6.1 (2019-07-05)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: CentOS Linux 7 (Core)

Matrix products: default
BLAS:   /opt/spack/opt/spack/linux-centos7-x86_64/gcc-9.2.0/r-3.6.1-j25wr6zcofibs2zfjwg37357rjj26lqb/rlib/R/lib/libRblas.so
LAPACK: /opt/spack/opt/spack/linux-centos7-x86_64/gcc-9.2.0/r-3.6.1-j25wr6zcofibs2zfjwg37357rjj26lqb/rlib/R/lib/libRlapack.so

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] tidyselect_0.2.5 iml_0.10.0       patchwork_1.0.0  ggpmisc_0.3.3   
 [5] ggpubr_0.1.6     magrittr_1.5     dplyr_0.8.3      hsdar_0.5.2     
 [9] caret_6.0-81     ggplot2_3.2.1    lattice_0.20-38  signal_0.7-6    
[13] rootSolve_1.7    rgdal_1.4-8      raster_3.0-12    sp_1.3-1        
[17] drake_7.12.0    

loaded via a namespace (and not attached):
  [1] colorspace_1.4-0   smoof_1.5.1        class_7.3-15      
  [4] rprojroot_1.3-2    fs_1.3.1           listenv_0.8.0     
  [7] ParamHelpers_1.12  ggrepel_0.8.0      prodlim_2018.04.18
 [10] fansi_0.4.1        lubridate_1.7.4    codetools_0.2-16  
 [13] splines_3.6.1      knitr_1.23         mco_1.0-15.1      
 [16] zeallot_0.1.0      jsonlite_1.6       workflowr_1.6.1   
 [19] Metrics_0.1.4      kernlab_0.9-27     mlrMBO_1.1.2      
 [22] compiler_3.6.1     httr_1.4.0         backports_1.1.5   
 [25] assertthat_0.2.1   Matrix_1.2-15      lazyeval_0.2.1    
 [28] cli_2.0.1          later_1.0.0        htmltools_0.3.6   
 [31] prettyunits_1.0.2  tools_3.6.1        igraph_1.2.4.1    
 [34] misc3d_0.8-4       gtable_0.3.0       glue_1.3.1        
 [37] reshape2_1.4.3     fastmatch_1.1-0    Rcpp_1.0.3        
 [40] parallelMap_1.4    vctrs_0.2.1        RJSONIO_1.3-1.1   
 [43] nlme_3.1-142       iterators_1.0.10   timeDate_3043.102 
 [46] gower_0.1.2        xfun_0.5           mlr_2.17.0.9001   
 [49] stringr_1.4.0      globals_0.12.5     lifecycle_0.1.0   
 [52] future_1.16.0      MASS_7.3-51.4      scales_1.0.0      
 [55] ipred_0.9-8        hms_0.5.3          promises_1.0.1    
 [58] parallel_3.6.1     plot3D_1.1.1       RColorBrewer_1.1-2
 [61] BBmisc_1.11        yaml_2.2.0         gridExtra_2.3     
 [64] DiceKriging_1.5.6  rpart_4.1-13       stringi_1.3.1     
 [67] foreach_1.4.4      checkmate_2.0.0    lhs_1.0.1         
 [70] filelock_1.0.2     lava_1.6.5         storr_1.2.1       
 [73] rlang_0.4.4        pkgconfig_2.0.3    evaluate_0.13     
 [76] purrr_0.3.3        prediction_0.3.14  labeling_0.3      
 [79] recipes_0.1.4      htmlwidgets_1.3    plyr_1.8.4        
 [82] R6_2.4.1           generics_0.0.2     base64url_1.4     
 [85] txtq_0.1.4         pillar_1.4.3       whisker_0.3-2     
 [88] withr_2.1.2        survival_2.43-3    nnet_7.3-12       
 [91] future.apply_1.4.0 tibble_2.1.3       crayon_1.3.4      
 [94] utf8_1.1.4         plotly_4.8.0       rmarkdown_1.13    
 [97] progress_1.2.0     grid_3.6.1         data.table_1.12.8 
[100] git2r_0.26.1       ModelMetrics_1.2.2 digest_0.6.23     
[103] tidyr_1.0.0        httpuv_1.4.5.1     stats4_3.6.1      
[106] munsell_0.5.0      viridisLite_0.3.0