Mercurial > repos > ecology > srs_global_indices
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planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7
author | ecology |
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date | Mon, 09 Jan 2023 13:36:33 +0000 |
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#Rscript ########################################### ## Mapping alpha and beta diversity ## ########################################### #####Packages : expint, # pracma, # R.utils, # raster, # sp, # matrixStats, # ggplot2, # expandFunctions, # stringr, # XML, # rgdal, # stars, #####Load arguments args <- commandArgs(trailingOnly = TRUE) #####Import the S2 data if (length(args) < 1) { stop("This tool needs at least 1 argument") }else { data_raster <- args[1] data_header <- args[2] data <- args[3] source(args[4]) source(args[5]) source(args[6]) indice_choice <- strsplit(args[7], ",")[[1]] source(args[8]) output_raster <- as.character(args[9]) } ######################################################################## ## COMPUTE SPECTRAL INDEX : NDVI ## ######################################################################## if (data != "") { #Create a directory where to unzip your folder of data dir.create("data_dir") unzip(data, exdir = "data_dir") # Read raster data_raster <- list.files("data_dir/results/Reflectance", pattern = "_Refl") data_raster <- file.path("data_dir/results/Reflectance", data_raster[1]) refl <- raster::brick(data_raster) refl2 <- raster::raster(data_raster) } else { # Read raster refl <- raster::brick(data_raster) refl2 <- raster::raster(data_raster) } # get raster band name and clean format. Expecting band name and wav # reflFactor = 10000 when reflectance is coded as INT16 refl <- raster::aggregate(refl, fact = 10) # Convert raster to SpatialPointsDataFrame refl2 <- raster::aggregate(refl2, fact = 10) r_pts <- convert_raster(refl2) table_ind <- r_pts # create directory for Spectralelength to be documented in image hdr_refl <- read_envi_header(get_hdr_name(data_raster)) sensorbands <- hdr_refl$wavelength # compute a set of spectral indices defined by indexlist from S2 data indices si_path <- file.path("SpectralIndices") dir.create(path = si_path, showWarnings = FALSE, recursive = TRUE) # Save spectral indices indices <- lapply(indice_choice, function(x) { indices_list <- computespectralindices_raster(refl = refl, sensorbands = sensorbands, sel_indices = x, reflfactor = 10000, stackout = FALSE) index_path <- file.path(si_path, paste(basename(data_raster), "_", x, sep = "")) spec_indices <- stars::write_stars(stars::st_as_stars(indices_list$spectralindices[[1]]), dsn = index_path, driver = "ENVI", type = "Float32") # write band name in HDR hdr <- read_envi_header(get_hdr_name(index_path)) hdr$`band names` <- x write_envi_header(hdr = hdr, hdrpath = get_hdr_name(index_path)) # Writting the tabular and the plot r_pts[, x] <- as.data.frame(sapply(spec_indices, c)) plot_indices(data = r_pts, titre = x) return(r_pts) }) new_table <- as.data.frame(indices) new_table <- new_table[, !grepl("longitude", names(new_table))] new_table <- new_table[, !grepl("latitude", names(new_table))] new_table <- new_table[, !grepl(basename(data_raster), names(new_table))] table_ind <- cbind(table_ind, new_table) if (length(indice_choice) == 1) { colnames(table_ind) <- c(basename(data_raster), "longitude", "latitude", indice_choice) } write.table(table_ind, file = "Spec_Index.tabular", sep = "\t", dec = ".", na = " ", row.names = FALSE, col.names = TRUE, quote = FALSE) # Get the raster layer of the indice as an output