# CI_EXTRACTION.R # ============== # This script processes satellite imagery to extract Canopy Index (CI) values for agricultural fields. # It handles image processing, masking, and extraction of statistics by field/sub-field. # Supports both 4-band and 8-band PlanetScope data with automatic band detection and cloud masking. # # Usage: Rscript 02_ci_extraction.R [end_date] [offset] [project_dir] [data_source] # - end_date: End date for processing (YYYY-MM-DD format) # - offset: Number of days to look back from end_date # - project_dir: Project directory name (e.g., "angata", "aura", "chemba") # - data_source: Data source directory - "merged_tif_8b" (default) or "merged_tif" (4-band) or "merged_final_tif" # # Examples: # # Angata 8-band data (with UDM cloud masking) # Rscript 02_ci_extraction.R 2025-12-02 7 angata merged_tif_8b # # # Aura 4-band data # Rscript 02_ci_extraction.R 2025-11-26 7 aura merged_tif # 1. Load required packages # ----------------------- suppressPackageStartupMessages({ library(sf) library(terra) library(tidyverse) library(lubridate) library(exactextractr) library(readxl) library(here) }) # 2. Process command line arguments # ------------------------------ main <- function() { # Capture command line arguments args <- commandArgs(trailingOnly = TRUE) # Process end_date argument if (length(args) >= 1 && !is.na(args[1])) { end_date <- as.Date(args[1]) if (is.na(end_date)) { warning("Invalid end_date provided. Using default (current date).") end_date <- Sys.Date() #end_date <- "2023-10-01" } } else { end_date <- Sys.Date() #end_date <- "2023-10-01" } # Process offset argument if (length(args) >= 2 && !is.na(args[2])) { offset <- as.numeric(args[2]) if (is.na(offset) || offset <= 0) { warning("Invalid offset provided. Using default (7 days).") offset <- 7 } } else { offset <- 7 } # Process project_dir argument if (length(args) >= 3 && !is.na(args[3])) { project_dir <- as.character(args[3]) } else if (exists("project_dir", envir = .GlobalEnv)) { project_dir <- get("project_dir", envir = .GlobalEnv) } else { project_dir <- "aura" # Changed default from "aura" to "esa" } # Process data_source argument (optional, for specifying merged_tif_8b vs merged_tif vs merged_final_tif) if (length(args) >= 4 && !is.na(args[4])) { data_source <- as.character(args[4]) # Validate data_source is a recognized option if (!data_source %in% c("merged_tif_8b", "merged_tif", "merged_final_tif")) { warning(paste("Data source", data_source, "not in standard list. Using as-is.")) } } else if (exists("data_source", envir = .GlobalEnv)) { data_source <- get("data_source", envir = .GlobalEnv) } else { data_source <- "merged_tif_8b" # Default to 8-band (newer data with cloud masking) } # Make project_dir and data_source available globally assign("project_dir", project_dir, envir = .GlobalEnv) assign("data_source", data_source, envir = .GlobalEnv) cat(sprintf("CI Extraction: project=%s, end_date=%s, offset=%d days, data_source=%s\n", project_dir, format(end_date, "%Y-%m-%d"), offset, data_source)) # Set flag to use pivot_2.geojson for ESA (extra fields for yield prediction) ci_extraction_script <- TRUE assign("ci_extraction_script", ci_extraction_script, envir = .GlobalEnv) # 3. Initialize project configuration # -------------------------------- new_project_question <- TRUE cat("[DEBUG] Attempting to source r_app/parameters_project.R\n") tryCatch({ source("r_app/parameters_project.R") cat("[DEBUG] Successfully sourced r_app/parameters_project.R\n") }, error = function(e) { cat("[ERROR] Failed to source r_app/parameters_project.R:\n", e$message, "\n") stop(e) }) cat("[DEBUG] Attempting to source r_app/ci_extraction_utils.R\n") tryCatch({ source("r_app/ci_extraction_utils.R") cat("[DEBUG] Successfully sourced r_app/ci_extraction_utils.R\n") }, error = function(e) { cat("[ERROR] Failed to source r_app/ci_extraction_utils.R:\n", e$message, "\n") stop(e) }) # 4. Generate date list for processing # --------------------------------- dates <- date_list(end_date, offset) log_message(paste("Processing data for week", dates$week, "of", dates$year)) # 5. Find and filter raster files by date # ----------------------------------- log_message("Searching for raster files") tryCatch({ # Use the new utility function to find satellite images existing_files <- find_satellite_images(planet_tif_folder, dates$days_filter) log_message(paste("Found", length(existing_files), "raster files for processing")) # 6. Process raster files and create VRT # ----------------------------------- # Use the new utility function for batch processing vrt_list <- process_satellite_images(existing_files, field_boundaries, merged_final, daily_vrt) # 7. Process and combine CI values # ------------------------------ # Call the process_ci_values function from utils with all required parameters process_ci_values(dates, field_boundaries, merged_final, field_boundaries_sf, daily_CI_vals_dir, cumulative_CI_vals_dir) }, error = function(e) { log_message(paste("Error in main processing:", e$message), level = "ERROR") stop(e$message) }) } if (sys.nframe() == 0) { main() }