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annotate prosail-master/R/Lib_PROSAIL_HybridInversion.R @ 1:9300a492b634 draft default tip

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planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit 0f331043178bbfbe5cda0e31d887971464b3071c
author ecology
date Fri, 07 Apr 2023 15:58:46 +0000
parents 79bcb8c6dff0
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79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
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1 # ============================================================================= =
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2 # prosail
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3 # Lib_PROSAIL_HybridInversion.R
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4 # ============================================================================= =
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5 # PROGRAMMERS:
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6 # Jean-Baptiste FERET <jb.feret@teledetection.fr>
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7 # Florian de BOISSIEU <fdeboiss@gmail.com>
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8 # Copyright 2019 / 11 Jean-Baptiste FERET
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9 # ============================================================================= =
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10 # This Library includes functions dedicated to PROSAIL inversion using hybrid
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11 # approach based on SVM regression
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12 # ============================================================================= =
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13
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
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14
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
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15 #" This function applies SVR model on raster data in order to estimate
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
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16 #" vegetation biophysical properties
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17 #"
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18 #" @param raster_path character. path for a raster file
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19 #" @param hybridmodel list. hybrid models produced from train_prosail_inversion
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20 #" each element of the list corresponds to a set of hybrid models for a vegetation parameter
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21 #" @param pathout character. path for directory where results are written
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22 #" @param selectedbands list. list of spectral bands to be selected from raster (identified by name of vegetation parameter)
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23 #" @param bandname character. spectral bands corresponding to the raster
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24 #" @param maskraster character. path for binary mask defining ON (1) and OFF (0) pixels in the raster
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25 #" @param multiplyingfactor numeric. multiplying factor used to write reflectance in the raster
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26 #" --> PROSAIL simulates reflectance between 0 and 1, and raster data expected in the same range
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27 #"
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28 #" @return None
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29 #" @importFrom progress progress_bar
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30 #" @importFrom stars read_stars
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31 #" @importFrom raster raster brick blockSize readStart readStop getValues writeStart writeStop writeValues
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32 #" @import rgdal
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33 #" @export
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34 apply_prosail_inversion <- function(raster_path, hybridmodel, pathout,
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35 selectedbands, bandname,
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36 maskraster = FALSE, multiplyingfactor = 10000) {
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37
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38 # explain which biophysical variables will be computed
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39 bpvar <- names(hybridmodel)
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40 print("The following biophysical variables will be computed")
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41 print(bpvar)
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42
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43 # get image dimensions
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44 if (attr(rgdal::GDALinfo(raster_path, returnStats = FALSE), "driver") == "ENVI") {
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45 hdr <- read_envi_header(get_hdr_name(raster_path))
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46 dimsraster <- list("rows" = hdr$lines, "cols" = hdr$samples, "bands" = hdr$bands)
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47 } else {
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48 dimsraster <- dim(read_stars(raster_path))
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49 dimsraster <- list("rows" = as.numeric(dimsraster[2]), "cols" = as.numeric(dimsraster[1]), "bands" = as.numeric(dimsraster[3]))
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50 }
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51
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52 # Produce a map for each biophysical property
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53 for (parm in bpvar) {
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54 print(paste("Computing", parm, sep = " "))
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55 # read by chunk to avoid memory problem
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56 blk <- blockSize(brick(raster_path))
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57 # reflectance file
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58 r_in <- readStart(brick(raster_path))
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59 # mask file
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60 r_inmask <- FALSE
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61 if (maskraster == FALSE) {
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62 selectpixels <- "ALL"
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63 } else if (!maskraster == FALSE) {
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64 if (file.exists(maskraster)) {
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65 r_inmask <- readStart(raster(maskraster))
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66 } else if (!file.exists(maskraster)) {
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67 message("WARNING: Mask file does not exist:")
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68 print(maskraster)
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69 message("Processing all image")
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70 selectpixels <- "ALL"
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71 }
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72 }
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73 # initiate progress bar
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74 pgbarlength <- length(hybridmodel[[parm]]) * blk$n
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75 pb <- progress_bar$new(
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76 format = "Hybrid inversion on raster [:bar] :percent in :elapsedfull, estimated time remaining :eta",
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77 total = pgbarlength, clear = FALSE, width = 100)
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78
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79 # output files
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80 bpvarpath <- file.path(pathout, paste(basename(raster_path), parm, sep = "_"))
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81 bpvarsdpath <- file.path(pathout, paste(basename(raster_path), parm, "STD", sep = "_"))
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82 r_outmean <- writeStart(raster(raster_path), filename = bpvarpath, format = "ENVI", overwrite = TRUE)
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83 r_outsd <- writeStart(raster(raster_path), filename = bpvarsdpath, format = "ENVI", overwrite = TRUE)
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84 selbands <- match(selectedbands[[parm]], bandname)
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85
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86 # loop over blocks
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87 for (i in seq_along(blk$row)) {
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88 # read values for block
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89 # format is a matrix with rows the cells values and columns the layers
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90 blockval <- getValues(r_in, row = blk$row[i], nrows = blk$nrows[i])
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91 fulllength <- dim(blockval)[1]
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92
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93 if (typeof(r_inmask) == "logical") {
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94 blockval <- blockval[, selbands]
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95 # automatically filter pixels corresponding to negative values
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96 selectpixels <- which(blockval[, 1] > 0)
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97 blockval <- blockval[selectpixels, ]
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98 } else if (typeof(r_inmask) == "S4") {
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99 maskval <- getValues(r_inmask, row = blk$row[i], nrows = blk$nrows[i])
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100 selectpixels <- which(maskval == 1)
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101 blockval <- blockval[selectpixels, selbands]
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102 }
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103 mean_estimatefull <- NA * vector(length = fulllength)
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104 std_estimatefull <- NA * vector(length = fulllength)
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105 if (length(selectpixels) > 0) {
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106 blockval <- blockval / multiplyingfactor
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107 modelsvr_estimate <- list()
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108 for (modind in 1:seq_along(hybridmodel[[parm]])) {
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109 pb$tick()
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110 modelsvr_estimate[[modind]] <- predict(hybridmodel[[parm]][[modind]], blockval)
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111 }
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112 modelsvr_estimate <- do.call(cbind, modelsvr_estimate)
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113 # final estimated value = mean parm value for all models
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114 mean_estimate <- rowMeans(modelsvr_estimate)
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115 # "uncertainty" = STD value for all models
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116 std_estimate <- rowSds(modelsvr_estimate)
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117 mean_estimatefull[selectpixels] <- mean_estimate
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118 std_estimatefull[selectpixels] <- std_estimate
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119 } else {
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120 for (modind in 1:seq_along(hybridmodel[[parm]])) {
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121 pb$tick()
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122 }
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123 }
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124 r_outmean <- writeValues(r_outmean, mean_estimatefull, blk$row[i], format = "ENVI", overwrite = TRUE)
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125 r_outsd <- writeValues(r_outsd, std_estimatefull, blk$row[i], format = "ENVI", overwrite = TRUE)
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126 }
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127 # close files
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128 r_in <- readStop(r_in)
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129 if (typeof(r_inmask) == "S4") {
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130 r_inmask <- readStop(r_inmask)
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131 }
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132 r_outmean <- writeStop(r_outmean)
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133 r_outsd <- writeStop(r_outsd)
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134 # write biophysical variable name in headers
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135 hdr <- read_envi_header(get_hdr_name(bpvarpath))
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136 hdr$`band names` <- paste("{", parm, "}", sep = "")
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137 write_envi_header(hdr, get_hdr_name(bpvarpath))
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138 }
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139 print("processing completed")
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140 return(invisible())
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141 }
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142
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143 #" get hdr name from image file name, assuming it is BIL format
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144 #"
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145 #" @param impath path of the image
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146 #"
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147 #" @return corresponding hdr
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148 #" @importFrom tools file_ext file_path_sans_ext
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149 #" @export
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150 get_hdr_name <- function(impath) {
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151 if (tools::file_ext(impath) == "") {
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152 impathhdr <- paste(impath, ".hdr", sep = "")
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153 } else if (tools::file_ext(impath) == "bil") {
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154 impathhdr <- gsub(".bil", ".hdr", impath)
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155 } else if (tools::file_ext(impath) == "zip") {
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156 impathhdr <- gsub(".zip", ".hdr", impath)
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157 } else {
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158 impathhdr <- paste(tools::file_path_sans_ext(impath), ".hdr", sep = "")
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159 }
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160
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161 if (!file.exists(impathhdr)) {
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162 message("WARNING : COULD NOT FIND hdr FILE")
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163 print(impathhdr)
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164 message("Process may stop")
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165 }
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166 return(impathhdr)
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167 }
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168
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169 #" This function applies the regression models trained with prosail_hybrid_train
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170 #"
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171 #" @param regressionmodels list. List of regression models produced by prosail_hybrid_train
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172 #" @param refl numeric. LUT of bidirectional reflectances factors used for training
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173 #"
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174 #" @return hybridres list. Estimated values corresponding to refl. Includes
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175 #" - meanestimate = mean value for the ensemble regression model
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176 #" - stdestimate = std value for the ensemble regression model
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177 #" @importFrom stats predict
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178 #" @importFrom matrixStats rowSds
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179 #" @importFrom progress progress_bar
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180 #" @export
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181
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182 prosail_hybrid_apply <- function(regressionmodels, refl) {
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183
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184 # make sure refl is right dimensions
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185 refl <- t(refl)
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186 nbfeatures <- regressionmodels[[1]]$dim
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187 if (!ncol(refl) == nbfeatures && nrow(refl) == nbfeatures) {
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188 refl <- t(refl)
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189 }
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190 nbensemble <- length(regressionmodels)
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191 estimatedval <- list()
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192 pb <- progress_bar$new(
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193 format = "Applying SVR models [:bar] :percent in :elapsed",
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194 total = nbensemble, clear = FALSE, width = 100)
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195 for (i in 1:nbensemble) {
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196 pb$tick()
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197 estimatedval[[i]] <- predict(regressionmodels[[i]], refl)
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198 }
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199 estimatedval <- do.call(cbind, estimatedval)
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200 meanestimate <- rowMeans(estimatedval)
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201 stdestimate <- rowSds(estimatedval)
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202 hybridres <- list("meanestimate" = meanestimate, "stdestimate" = stdestimate)
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203 return(hybridres)
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204 }
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205
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206 #" This function trains a suppot vector regression for a set of variables based on spectral data
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207 #"
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208 #" @param brf_lut numeric. LUT of bidirectional reflectances factors used for training
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209 #" @param inputvar numeric. biophysical parameter corresponding to the reflectance
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210 #" @param figplot Boolean. Set to TRUE if you want a scatterplot
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211 #" @param nbensemble numeric. Number of individual subsets should be generated from brf_lut
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212 #" @param withreplacement Boolean. should subsets be generated with or without replacement?
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213 #"
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214 #" @return modelssvr list. regression models trained for the retrieval of inputvar based on brf_lut
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215 #" @importFrom liquidSVM svmRegression
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216 #" @importFrom stats predict
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217 #" @importFrom progress progress_bar
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218 #" @importFrom graphics par
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219 #" @importFrom expandFunctions reset.warnings
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220 #" @importFrom stringr str_split
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221 #" @importFrom simsalapar tryCatch.W.E
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222 #" @import dplyr
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223 #" @import ggplot2
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224 # @" @import caret
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225 #" @export
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226
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227 prosail_hybrid_train <- function(brf_lut, inputvar, figplot = FALSE, nbensemble = 20, withreplacement = FALSE) {
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228
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229 x <- y <- ymean <- ystdmin <- ystdmax <- NULL
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230 # split the LUT into nbensemble subsets
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231 nbsamples <- length(inputvar)
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232 if (dim(brf_lut)[2] == nbsamples) {
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233 brf_lut <- t(brf_lut)
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234 }
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235
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236 # if subsets are generated from brf_lut with replacement
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237 if (withreplacement == TRUE) {
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238 subsets <- list()
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239 samples_per_run <- round(nbsamples / nbensemble)
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240 for (run in (1:nbensemble)) {
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241 subsets[[run]] <- sample(seq(1, nbsamples), samples_per_run, replace = TRUE)
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242 }
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243 # if subsets are generated from brf_lut without replacement
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244 } else if (withreplacement == FALSE) {
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245 subsets <- split(sample(seq(1, nbsamples, by = 1)), seq(1, nbensemble, by = 1))
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246 }
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247
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248 # run training for each subset
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249 modelssvr <- list()
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250 predictedyall <- list()
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251 tunedmodelyall <- list()
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252 pb <- progress_bar$new(
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253 format = "Training SVR on subsets [:bar] :percent in :elapsed",
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254 total = nbensemble, clear = FALSE, width = 100)
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255 for (i in 1:nbensemble) {
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256 pb$tick()
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257 Sys.sleep(1 / 100)
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258 trainingset <- list()
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259 trainingset$X <- brf_lut[subsets[i][[1]], ]
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260 trainingset$Y <- inputvar[subsets[i][[1]]]
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261 # liquidSVM
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262 r1 <- tryCatch.W.E(tunedmodel <- liquidSVM::svmRegression(trainingset$X, trainingset$Y))
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263 if (!is.null(r1$warning)) {
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264 msg <- r1$warning$message
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265 valgamma <- str_split(string = msg, pattern = "gamma=")[[1]][2]
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266 vallambda <- str_split(string = msg, pattern = "lambda=")[[1]][2]
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267 if (!is.na(as.numeric(valgamma))) {
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268 message("Adjusting Gamma accordingly")
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269 valgamma <- as.numeric(valgamma)
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270 tunedmodel <- liquidSVM::svmRegression(trainingset$X, trainingset$Y, min_gamma = valgamma)
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271 }
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272 if (!is.na(as.numeric(vallambda))) {
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273 message("Adjusting Lambda accordingly")
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274 vallambda <- as.numeric(vallambda)
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275 tunedmodel <- liquidSVM::svmRegression(trainingset$X, trainingset$Y, min_lambda = vallambda)
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276 }
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277 }
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278 modelssvr[[i]] <- tunedmodel
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279 }
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280
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281 # if scatterplots needed
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282 if (figplot == TRUE) {
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283 # predict for full brf_lut
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284 for (i in 1:nbensemble) {
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285 tunedmodely <- stats::predict(modelssvr[[i]], brf_lut)
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286 tunedmodelyall <- cbind(tunedmodelyall, matrix(tunedmodely, ncol = 1))
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287 }
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288 # plot prediction
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289 df <- data.frame(x = rep(1:nbsamples, nbensemble), y = as.numeric(matrix(tunedmodelyall, ncol = 1)))
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290 df_summary <- df %>%
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291 dplyr::group_by(x) %>%
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292 summarize(ymin = min(y), ystdmin = mean(y) - sd(y),
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293 ymax = max(y), ystdmax = mean(y) + sd(y),
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294 ymean = mean(y))
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295 par(mar = rep(.1, 4))
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296 p <- ggplot(df_summary, aes(x = inputvar, y = ymean)) +
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297 geom_point(size = 2) +
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298 geom_errorbar(aes(ymin = ystdmin, ymax = ystdmax))
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299 meanpredict <- rowMeans(matrix(as.numeric(tunedmodelyall), ncol = nbensemble))
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300 print(p)
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301 }
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302 return(modelssvr)
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303 }
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304
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305 #" Reads ENVI hdr file
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306 #"
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307 #" @param hdrpath Path of the hdr file
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308 #"
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309 #" @return list of the content of the hdr file
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310 #" @export
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311 read_envi_header <- function(hdrpath) {
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312 if (!grepl(".hdr$", hdrpath)) {
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313 stop("File extension should be .hdr")
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314 }
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315 hdr <- readLines(hdrpath)
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316 ## check ENVI at beginning of file
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317 if (!grepl("ENVI", hdr[1])) {
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318 stop("Not an ENVI header (ENVI keyword missing)")
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319 } else {
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320 hdr <- hdr [-1]
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321 }
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322 ## remove curly braces and put multi-line key-value-pairs into one line
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323 hdr <- gsub("\\{([^}]*)\\}", "\\1", hdr)
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324 l <- grep("\\{", hdr)
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325 r <- grep("\\}", hdr)
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326
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327 if (length(l) != length(r)) {
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328 stop("Error matching curly braces in header (differing numbers).")
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329 }
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330
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331 if (any(r <= l)) {
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332 stop("Mismatch of curly braces in header.")
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333 }
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334
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335 hdr[l] <- sub("\\{", "", hdr[l])
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336 hdr[r] <- sub("\\}", "", hdr[r])
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337
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338 for (i in rev(seq_along(l))) {
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339 hdr <- c(
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340 hdr [seq_len(l [i] - 1)],
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341 paste(hdr [l [i]:r [i]], collapse = "\n"),
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342 hdr [-seq_len(r [i])]
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343 )
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344 }
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345
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346 ## split key = value constructs into list with keys as names
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347 hdr <- sapply(hdr, split_line, " = ", USE.NAMES = FALSE)
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348 names(hdr) <- tolower(names(hdr))
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349
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350 ## process numeric values
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351 tmp <- names(hdr) %in% c(
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352 "samples", "lines", "bands", "header offset", "data type",
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353 "byte order", "default bands", "data ignore value",
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354 "wavelength", "fwhm", "data gain values"
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355 )
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356 hdr [tmp] <- lapply(hdr [tmp], function(x) {
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357 as.numeric(unlist(strsplit(x, ",")))
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358 })
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359
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360 return(hdr)
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361 }
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362
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363 #" ENVI functions
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364 #"
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365 #" based on https: / / github.com / cran / hyperSpec / blob / master / R / read.ENVI.R
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366 #" added wavelength, fwhm, ... to header reading
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367 #" Title
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368 #"
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369 #" @param x character.
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370 #" @param separator character
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371 #" @param trim_blank boolean.
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372 #"
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373 #" @return list.
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374 #" @export
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375 split_line <- function(x, separator, trim_blank = TRUE) {
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376 tmp <- regexpr(separator, x)
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377 key <- substr(x, 1, tmp - 1)
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378 value <- substr(x, tmp + 1, nchar(x))
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379 if (trim_blank) {
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380 blank_pattern <- "^[[:blank:]]*([^[:blank:]] + .*[^[:blank:]] + )[[:blank:]]*$"
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381 key <- sub(blank_pattern, "\\1", key)
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382 value <- sub(blank_pattern, "\\1", value)
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383 }
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384 value <- as.list(value)
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385 names(value) <- key
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386 return(value)
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387 }
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388
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389 #" This function performs full training for hybrid invrsion using SVR with
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390 #" values for default parameters
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391 #"
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392 #" @param minval list. minimum value for input parameters sampled to produce a training LUT
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393 #" @param maxval list. maximum value for input parameters sampled to produce a training LUT
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394 #" @param typedistrib list. Type of distribution. Either "Uniform" or "Gaussian"
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395 #" @param gaussiandistrib list. Mean value and STD corresponding to the parameters sampled with gaussian distribution
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396 #" @param parmset list. list of input parameters set to a specific value
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397 #" @param nbsamples numeric. number of samples in training LUT
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398 #" @param nbsamplesperrun numeric. number of training sample per individual regression model
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399 #" @param nbmodels numeric. number of individual models to be run for ensemble
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400 #" @param replacement bolean. is there replacement in subsampling?
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401 #" @param sailversion character. Either 4SAIL or 4SAIL2
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402 #" @param parms2estimate list. list of input parameters to be estimated
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403 #" @param bands2select list. list of bands used for regression for each input parameter
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404 #" @param noiselevel list. list of noise value added to reflectance (defined per input parm)
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405 #" @param specprospect list. Includes optical constants required for PROSPECT
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406 #" @param specsoil list. Includes either dry soil and wet soil, or a unique soil sample if the psoil parameter is not inverted
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407 #" @param specatm list. Includes direct and diffuse radiation for clear conditions
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408 #" @param path_results character. path for results
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409 #" @param figplot boolean. Set TRUE to get scatterplot of estimated biophysical variable during training step
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410 #" @param force4lowlai boolean. Set TRUE to artificially reduce leaf chemical constituent content for low LAI
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411 #"
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412 #"
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413 #" @return modelssvr list. regression models trained for the retrieval of inputvar based on brf_lut
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414 #" @export
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415
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416 train_prosail_inversion <- function(minval = NULL, maxval = NULL,
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417 typedistrib = NULL, gaussiandistrib = NULL, parmset = NULL,
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418 nbsamples = 2000, nbsamplesperrun = 100, nbmodels = 20, replacement = TRUE,
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419 sailversion = "4SAIL",
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420 parms2estimate = "lai", bands2select = NULL, noiselevel = NULL,
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421 specprospect = NULL, specsoil = NULL, specatm = NULL,
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422 path_results = "./", figplot = FALSE, force4lowlai = TRUE) {
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423
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424 ###===================================================================###
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425 ### 1- PRODUCE A LUT TO TRAIN THE HYBRID INVERSION ###
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426 ###===================================================================###
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427 # Define sensor characteristics
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428 if (is.null(specprospect)) {
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429 specprospect <- prosail::specprospect
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430 }
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431 if (is.null(specsoil)) {
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432 specsoil <- prosail::specsoil
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433 }
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434 if (is.null(specprospect)) {
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435 specatm <- prosail::specatm
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436 }
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437 # define distribution for parameters to be sampled
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438 if (is.null(typedistrib)) {
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439 typedistrib <- data.frame("CHL" = "Uniform", "CAR" = "Uniform", "EWT" = "Uniform", "ANT" = "Uniform", "LMA" = "Uniform", "N" = "Uniform", "BROWN" = "Uniform",
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440 "psoil" = "Uniform", "LIDFa" = "Uniform", "lai" = "Uniform", "q" = "Uniform", "tto" = "Uniform", "tts" = "Uniform", "psi" = "Uniform")
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441 }
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442 if (is.null(gaussiandistrib)) {
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443 gaussiandistrib <- list("Mean" = NULL, "Std" = NULL)
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444 }
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445 if (is.null(minval)) {
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446 minval <- data.frame("CHL" = 10, "CAR" = 0, "EWT" = 0.01, "ANT" = 0, "LMA" = 0.005, "N" = 1.0, "psoil" = 0.0, "BROWN" = 0.0,
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447 "LIDFa" = 20, "lai" = 0.5, "q" = 0.1, "tto" = 0, "tts" = 20, "psi" = 80)
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448 }
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449 if (is.null(maxval)) {
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450 maxval <- data.frame("CHL" = 75, "CAR" = 15, "EWT" = 0.03, "ANT" = 2, "LMA" = 0.03, "N" = 2.0, "psoil" = 1.0, "BROWN" = 0.5,
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451 "LIDFa" = 70, "lai" = 7, "q" = 0.2, "tto" = 5, "tts" = 30, "psi" = 110)
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452 }
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453 # define min and max values
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454 # fixed parameters
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455 if (is.null(parmset)) {
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456 parmset <- data.frame("TypeLidf" = 2, "alpha" = 40)
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457 }
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458 # produce input parameters distribution
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459 if (sailversion == "4SAIL") {
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460 inputprosail <- get_distribution_input_prosail(minval, maxval, parmset, nbsamples,
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461 typedistrib = typedistrib,
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462 Mean = gaussiandistrib$Mean, Std = gaussiandistrib$Std,
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463 force4lowlai = force4lowlai)
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464 } else if (sailversion == "4SAIL2") {
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
465 inputprosail <- get_distribution_input_prosail2(minval, maxval, parmset, nbsamples,
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
466 typedistrib = typedistrib,
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
467 Mean = gaussiandistrib$Mean, Std = gaussiandistrib$Std,
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
468 force4lowlai = force4lowlai)
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
469 }
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
470 if (sailversion == "4SAIL2") {
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
471 # Definition of Cv && update LAI
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
472 maxlai <- min(c(maxval$lai), 4)
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
473 inputprosail$Cv <- NA * inputprosail$lai
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
474 inputprosail$Cv[which(inputprosail$lai > maxlai)] <- 1
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
475 inputprosail$Cv[which(inputprosail$lai <= maxlai)] <- (1 / maxlai) + inputprosail$lai[which(inputprosail$lai <= maxlai)] / (maxlai + 1)
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
476 inputprosail$Cv <- inputprosail$Cv * matrix(rnorm(length(inputprosail$Cv), mean = 1, sd = 0.1))
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
477 inputprosail$Cv[which(inputprosail$Cv < 0)] <- 0
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
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diff changeset
478 inputprosail$Cv[which(inputprosail$Cv > 1)] <- 1
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
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diff changeset
479 inputprosail$Cv[which(inputprosail$lai > maxlai)] <- 1
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
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diff changeset
480 inputprosail$fraction_brown <- 0 + 0 * inputprosail$lai
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
481 inputprosail$diss <- 0 + 0 * inputprosail$lai
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
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diff changeset
482 inputprosail$Zeta <- 0.2 + 0 * inputprosail$lai
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
483 inputprosail$lai <- inputprosail$lai * inputprosail$Cv
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
484 }
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
485
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
486 # generate LUT of BRF corresponding to inputprosail, for a sensor
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
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diff changeset
487 brf_lut <- Generate_LUT_BRF(sailversion = sailversion, inputprosail = inputprosail,
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
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diff changeset
488 specprospect = specprospect, specsoil = specsoil, specatm = specatm)
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
489
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
490 # write parameters LUT
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
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diff changeset
491 output <- matrix(unlist(inputprosail), ncol = length(inputprosail), byrow = FALSE)
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
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diff changeset
492 filename <- file.path(path_results, "PROSAIL_LUT_InputParms.txt")
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
493 write.table(x = format(output, digits = 3), file = filename, append = FALSE, quote = FALSE,
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
494 col.names = names(inputprosail), row.names = FALSE, sep = "\t")
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
495 # Write BRF LUT corresponding to parameters LUT
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
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diff changeset
496 filename <- file.path(path_results, "PROSAIL_LUT_reflectance.txt")
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
497 write.table(x = format(t(brf_lut), digits = 5), file = filename, append = FALSE, quote = FALSE,
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
498 col.names = specprospect$lambda, row.names = FALSE, sep = "\t")
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
499
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
500 # Which bands will be used for inversion?
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
501 if (is.null(bands2select)) {
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
502 bands2select <- list()
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
503 for (parm in parms2estimate) {
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
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diff changeset
504 bands2select[[parm]] <- seq(1, length(specprospect$lambda))
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
505 }
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
506 }
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
507 # Add gaussian noise to reflectance LUT: one specific LUT per parameter
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
508 if (is.null(noiselevel)) {
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
509 noiselevel <- list()
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
510 for (parm in parms2estimate) {
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
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diff changeset
511 noiselevel[[parm]] <- 0.01
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
512 }
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
513 }
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
514
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
515 # produce LIT with noise
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
516 brf_lut_noise <- list()
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
517 for (parm in parms2estimate) {
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
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diff changeset
518 brf_lut_noise[[parm]] <- brf_lut[bands2select[[parm]], ] + brf_lut[bands2select[[parm]], ] * matrix(rnorm(nrow(brf_lut[bands2select[[parm]], ]) * ncol(brf_lut[bands2select[[parm]], ]),
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
519 0, noiselevel[[parm]]), nrow = nrow(brf_lut[bands2select[[parm]], ]))
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
520 }
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
521
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
522 ###===================================================================###
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
523 ### PERFORM HYBRID INVERSION ###
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
524 ###===================================================================###
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
525 # train SVR for each variable and each run
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
526 modelsvr <- list()
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
527 for (parm in parms2estimate) {
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
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diff changeset
528 colparm <- which(parm == names(inputprosail))
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
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diff changeset
529 inputvar <- inputprosail[[colparm]]
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
530 modelsvr[[parm]] <- prosail_hybrid_train(brf_lut = brf_lut_noise[[parm]], inputvar = inputvar,
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
531 figplot = figplot, nbensemble = nbmodels, withreplacement = replacement)
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
532 }
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
533 return(modelsvr)
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
534 }
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
535
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
536 #" writes ENVI hdr file
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
537 #"
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
538 #" @param hdr content to be written
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
539 #" @param hdrpath Path of the hdr file
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
540 #"
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
541 #" @return None
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
542 #" @importFrom stringr str_count
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
543 #" @export
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
544 write_envi_header <- function(hdr, hdrpath) {
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
545 h <- lapply(hdr, function(x) {
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
546 if (length(x) > 1 || (is.character(x) && stringr::str_count(x, "\\w + ") > 1)) {
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
547 x <- paste0("{", paste(x, collapse = ","), "}")
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
548 }
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
549 # convert last numerics
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
550 x <- as.character(x)
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
551 })
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
552 writeLines(c("ENVI", paste(names(hdr), h, sep = "=")), con = hdrpath)
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
553 return(invisible())
79bcb8c6dff0 planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
ecology
parents:
diff changeset
554 }