SmartCane/r_app/02_ci_extraction.R

# 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()
}