example0.RmdThe Validation Table is crucial when validating the simulated Results to the measured samples. ARTMO requires this Table for the LUT. It requires to have the first Line(s) containing the measured value you want to model (e.g. LAI, Angle, Chlorophyll etc). The following rows are then reserved for the Spectral signatures. The exact location of the spectral information as well as the measured variable is specified in ARTMO.
Assuming that you have a tidy dataframe as the following:
artmo## # A tibble: 126 x 16
## Station OP1 Date LAI MTA Sunzenith S.Band_1 S.Band_2
## <chr> <chr> <date> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 Domef1~ ID1 2017-05-17 2.13 79.1 28.6 0.0204 0.0494
## 2 Domef1~ ID2 2017-05-17 2.12 83.5 28.6 0.0188 0.0492
## 3 Domef1~ ID3 2017-05-17 2.51 79.9 28.6 0.0188 0.0492
## 4 Domef1~ ID4 2017-05-17 1.71 86.8 28.6 0.0219 0.0518
## 5 Domef1~ ID2 2017-05-24 3.14 67.1 26.9 0.0189 0.047
## 6 Domef1~ ID3 2017-05-24 2.22 76.4 26.9 0.0189 0.047
## 7 Domef1~ ID4 2017-05-24 3.79 61.3 26.9 0.0294 0.0679
## 8 Domef1~ ID2 2017-05-31 3.69 63.7 27.1 0.0119 0.0592
## 9 Domef1~ ID3 2017-05-31 3.04 69.3 27.1 0.0112 0.0604
## 10 Domef1~ ID4 2017-05-31 4.96 59.8 27.1 0.0129 0.0545
## # ... with 116 more rows, and 8 more variables: S.Band_3 <dbl>,
## # S.Band_4 <dbl>, S.Band_5 <dbl>, S.Band_6 <dbl>, S.Band_7 <dbl>,
## # S.Band_8 <dbl>, S.Band_9 <dbl>, S.Band_10 <dbl>with the following columns:
* Station and OP1 are spatial locations and sub location
* Date the Date of the acquisition
* LAI, MTA, Sunzenith the variables for the Model
* The following columns contain the reflectance value as detected by Sentinel-2 sensors with the Prefix S_Band_.
The measured Variables in this case are LAI, MTA and the solar zenith angle. The response are the reflectance values as collected by Sentinel-2 MSI. In order to retain the proper format we have to apply the following code reducing and reversing the Code.
artmo1<-artmo %>%
group_by(Station,Date,OP1) %>%
nest
cnames<-artmo1$data[[1]] %>% colnames
artmo2<- map(artmo1$data,t)
artmo3<- do.call(cbind,artmo2)
artmo4<- cbind(cnames,artmo3) %>% as_tibble
print(artmo4)## # A tibble: 13 x 127
## cnames V2 V3 V4 V5 V6 V7 V8 V9 V10 V11 V12
## <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
## 1 LAI 2.127 2.11~ 2.507 1.70~ 3.14~ 2.219 3.79~ 3.694 3.042 4.965 4.845
## 2 MTA 79.1~ 83.5~ 79.9~ 86.7~ 67.1~ 76.3~ 61.3~ 63.71 69.3~ 59.78 57.59
## 3 Sunze~ 28.6~ 28.6~ 28.6~ 28.6~ 26.9~ 26.9~ 26.9~ 27.1~ 27.1~ 27.1~ 27.1~
## 4 S.Ban~ 0.02~ 0.01~ 0.01~ 0.02~ 0.01~ 0.01~ 0.02~ 0.01~ 0.01~ 0.01~ 0.01
## 5 S.Ban~ 0.04~ 0.04~ 0.04~ 0.05~ 0.047 0.047 0.06~ 0.05~ 0.06~ 0.05~ 0.05~
## 6 S.Ban~ 0.02~ 0.02~ 0.02~ 0.02~ 0.01~ 0.01~ 0.02~ 0.02~ 0.02~ 0.02~ 0.02~
## 7 S.Ban~ 0.11~ 0.09~ 0.09~ 0.10~ 0.10~ 0.10~ 0.10~ 0.10~ 0.10~ 0.10~ 0.10~
## 8 S.Ban~ 0.34~ 0.34~ 0.34~ 0.33~ 0.35~ 0.35~ 0.35~ 0.41~ 0.41~ 0.41~ 0.41~
## 9 S.Ban~ 0.41~ 0.41~ 0.41~ 0.42~ 0.45~ 0.45~ 0.45~ 0.527 0.527 0.527 0.527
## 10 S.Ban~ 0.44~ 0.45~ 0.45~ 0.44~ 0.49~ 0.49~ 0.497 0.553 0.55~ 0.54~ 0.54~
## 11 S.Ban~ 0.44~ 0.45~ 0.45~ 0.45~ 0.46~ 0.46~ 0.46~ 0.53~ 0.53~ 0.53~ 0.53~
## 12 S.Ban~ 0.181 0.18~ 0.18~ 0.185 0.17~ 0.17~ 0.17~ 0.18~ 0.18~ 0.18~ 0.18~
## 13 S.Ban~ 0.08~ 0.07~ 0.07~ 0.08~ 0.08~ 0.08~ 0.08~ 0.09~ 0.09~ 0.09~ 0.09~
## # ... with 115 more variables: V13 <chr>, V14 <chr>, V15 <chr>, V16 <chr>,
## # V17 <chr>, V18 <chr>, V19 <chr>, V20 <chr>, V21 <chr>, V22 <chr>,
## # V23 <chr>, V24 <chr>, V25 <chr>, V26 <chr>, V27 <chr>, V28 <chr>,
## # V29 <chr>, V30 <chr>, V31 <chr>, V32 <chr>, V33 <chr>, V34 <chr>,
## # V35 <chr>, V36 <chr>, V37 <chr>, V38 <chr>, V39 <chr>, V40 <chr>,
## # V41 <chr>, V42 <chr>, V43 <chr>, V44 <chr>, V45 <chr>, V46 <chr>,
## # V47 <chr>, V48 <chr>, V49 <chr>, V50 <chr>, V51 <chr>, V52 <chr>,
## # V53 <chr>, V54 <chr>, V55 <chr>, V56 <chr>, V57 <chr>, V58 <chr>,
## # V59 <chr>, V60 <chr>, V61 <chr>, V62 <chr>, V63 <chr>, V64 <chr>,
## # V65 <chr>, V66 <chr>, V67 <chr>, V68 <chr>, V69 <chr>, V70 <chr>,
## # V71 <chr>, V72 <chr>, V73 <chr>, V74 <chr>, V75 <chr>, V76 <chr>,
## # V77 <chr>, V78 <chr>, V79 <chr>, V80 <chr>, V81 <chr>, V82 <chr>,
## # V83 <chr>, V84 <chr>, V85 <chr>, V86 <chr>, V87 <chr>, V88 <chr>,
## # V89 <chr>, V90 <chr>, V91 <chr>, V92 <chr>, V93 <chr>, V94 <chr>,
## # V95 <chr>, V96 <chr>, V97 <chr>, V98 <chr>, V99 <chr>, V100 <chr>,
## # V101 <chr>, V102 <chr>, V103 <chr>, V104 <chr>, V105 <chr>,
## # V106 <chr>, V107 <chr>, V108 <chr>, V109 <chr>, V110 <chr>,
## # V111 <chr>, V112 <chr>, ...