Mercurial > repos > ecology > srs_global_indices
diff biodiv_indices_global.r @ 0:5cae678042ec draft default tip
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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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/biodiv_indices_global.r Mon Jan 09 13:36:33 2023 +0000 @@ -0,0 +1,112 @@ +#Rscript + +########################################### +## Mapping biodiversity indicators ## +########################################### + +#####Packages : raster, +# rgdal, +# sp, +# rasterdiv, +# ggplot2, + +#####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] + alpha <- as.numeric(args[4]) + source(args[5]) + +} + +######################################################################## +## COMPUTE BIODIVERSITY INDICES ## +######################################################################## + +if (data_raster == "") { + #Create a directory where to unzip your folder of data + dir.create("data_dir") + unzip(data, exdir = "data_dir") + # Path to raster + data_raster <- list.files("data_dir/results/Reflectance", pattern = "_Refl") + data_raster <- file.path("data_dir/results/Reflectance", data_raster[1]) +} + +# Read raster +copndvi <- raster::raster(data_raster) + +copndvilr <- raster::reclassify(copndvi, cbind(252, 255, NA), right = TRUE) + +#Resample using raster::aggregate and a linear factor of 10 +copndvilr <- raster::aggregate(copndvilr, fact = 20) +#Set float numbers as integers to further speed up the calculation +storage.mode(copndvilr[]) <- "integer" + +# Convert raster to SpatialPointsDataFrame +r_pts <- convert_raster(copndvilr) + +#Shannon's Diversity +sha <- rasterdiv::Shannon(copndvilr, window = 9, np = 1) +sha_df <- data.frame(raster::rasterToPoints(sha, spatial = TRUE)) +sha_name <- "Shannon" +r_pts[, sha_name] <- sha_df[, 1] + +#Renyi's Index +ren <- rasterdiv::Renyi(copndvilr, window = 9, alpha = alpha, np = 1) +ren_df <- data.frame(raster::rasterToPoints(ren[[1]])) +ren_name <- "Renyi" +r_pts[, ren_name] <- ren_df[, 3] + +#Berger-Parker's Index +ber <- rasterdiv::BergerParker(copndvilr, window = 9, np = 1) +ber_df <- data.frame(raster::rasterToPoints(ber, spatial = TRUE)) +ber_name <- "Berger-Parker" +r_pts[, ber_name] <- ber_df[, 1] + +#Pielou's Evenness +pie <- rasterdiv::Pielou(copndvilr, window = 9, np = 1) +pie_df <- data.frame(raster::rasterToPoints(pie)) +if (length(pie_df[, 1]) == length(r_pts[, 1])) { + pie_name <- "Pielou" + r_pts[, pie_name] <- pie_df[, 1] +} + +#Hill's numbers +hil <- rasterdiv::Hill(copndvilr, window = 9, alpha = alpha, np = 1) +hil_df <- data.frame(raster::rasterToPoints(hil[[1]])) +hil_name <- "Hill" +r_pts[, hil_name] <- hil_df[, 3] + +#Parametric Rao's quadratic entropy with alpha ranging from 1 to 5 +prao <- rasterdiv::paRao(copndvilr, window = 9, alpha = alpha, dist_m = "euclidean", np = 1) +prao_df <- data.frame(raster::rasterToPoints(prao$window.9[[1]])) +prao_name <- "Prao" +r_pts[, prao_name] <- prao_df[, 3] + +#Cumulative Residual Entropy +cre <- rasterdiv::CRE(copndvilr, window = 9, np = 1) +cre_df <- data.frame(raster::rasterToPoints(cre)) +if (length(cre_df[, 1]) == length(r_pts[, 1])) { + cre_name <- "CRE" + r_pts[, cre_name] <- cre_df[, 1] +} + +if (length(cre_df[, 1]) == length(r_pts[, 1]) || length(pie_df[, 1]) == length(r_pts[, 1])) { +list_indice <- list("Shannon", "Renyi", "Berger-Parker", "Pielou", "Hill", "Prao", "CRE") +} else { +list_indice <- list("Shannon", "Renyi", "Berger-Parker", "Hill", "Prao") +} +## Plotting all the graph and writing a tabular +for (indice in list_indice) { + plot_indices(data = r_pts, titre = indice) +} + +write.table(r_pts, file = "BiodivIndex.tabular", sep = "\t", dec = ".", na = " ", row.names = FALSE, col.names = TRUE, quote = FALSE)