Refactor risk assessment terminology in reports; replace 'Weed Risk' with 'Patchiness Risk' and update related calculations and alerts for consistency

r_app/80_utils_cane_supply.R

@@ -138,28 +138,28 @@ categorize_cv_trend_long_term <- function(cv_slope) {
 
 #' Determine status alert based on harvest probability and crop health
 #' Priority order:
-#' 1. Ready for harvest-check (imminent + mature ≥12 months)
-#' 2. Strong decline in crop health (drop ≥2 points but still >1.5)
-#' 3. Harvested/bare (Mean CI < 1.5)
+#' 1. harvest_ready (imminent + mature ≥12 months)
+#' 2. decline_stress (drop ≥2 points but still >1.5)
+#' 3. harvested_bare (Mean CI < 1.5)
 #' @param imminent_prob Numeric harvest probability
 #' @param age_week Numeric age in weeks
 #' @param weekly_ci_change Numeric weekly CI change
 #' @param mean_ci Numeric mean CI value
-#' @return Character status alert or NA
+#' @return Character status alert code or NA
 calculate_status_alert <- function(imminent_prob, age_week, weekly_ci_change, mean_ci) {
   # Priority 1: Ready for harvest-check
   if (!is.na(imminent_prob) && imminent_prob > 0.5 && !is.na(age_week) && age_week >= 52) {
-    return("Ready for harvest-check")
+    return("harvest_ready")
   }
   
   # Priority 2: Strong decline
   if (!is.na(weekly_ci_change) && weekly_ci_change <= -2.0 && !is.na(mean_ci) && mean_ci > 1.5) {
-    return("Strong decline in crop health")
+    return("decline_stress")
   }
   
   # Priority 3: Harvested/bare
   if (!is.na(mean_ci) && mean_ci < 1.5) {
-    return("Harvested/bare")
+    return("harvested_bare")
   }
   
   # Fallback: no alert

r_app/90_CI_report_with_kpis_agronomic_support.Rmd

@@ -199,7 +199,7 @@ if (dir.exists(kpi_data_dir)) {
           c("Gap_Score", "Gap_Score"),  # Keep as-is
           c("Growth Uniformity", "Growth_Uniformity"),
           c("Decline Risk", "Decline_Risk"),
-          c("Weed Risk", "Weed_Risk"),
+          c("Patchiness Risk", "Patchiness_Risk"),
           c("Moran's I", "Morans_I")
         )
         
@@ -539,15 +539,15 @@ if (exists("summary_tables") && !is.null(summary_tables) && length(summary_table
     }
   }
   
-  # 4. Weed pressure insights - group by weed_pressure_risk
-  if (!is.null(summary_tables$weed_pressure) && nrow(summary_tables$weed_pressure) > 0) {
-    cat("\n**Weed/Pest Pressure Risk:**\n")
-    weed_counts <- summary_tables$weed_pressure %>%
-      dplyr::select(weed_pressure_risk, count = field_count)
+  # 4. Patchiness insights - group by patchiness_risk
+  if (!is.null(summary_tables$patchiness) && nrow(summary_tables$patchiness) > 0) {
+    cat("\n**Field Patchiness Risk:**\n")
+    patchiness_counts <- summary_tables$patchiness %>%
+      dplyr::select(patchiness_risk, count = field_count)
     
-    for (i in seq_len(nrow(weed_counts))) {
-      risk <- weed_counts$weed_pressure_risk[i]
-      count <- weed_counts$count[i]
+    for (i in seq_len(nrow(patchiness_counts))) {
+      risk <- patchiness_counts$patchiness_risk[i]
+      count <- patchiness_counts$count[i]
       if (!is.na(risk) && !is.na(count) && count > 0) {
         cat("- ", count, " field(s) at ", risk, " risk\n", sep="")
       }
@@ -684,7 +684,7 @@ generate_field_alerts <- function(field_details_table) {
   
   # Check for required columns
   required_cols <- c("Field", "Field Size (acres)", "Growth Uniformity", "Yield Forecast (t/ha)", 
-                     "Gap Score", "Decline Risk", "Weed Risk", "Mean CI", "CV Value", "Moran's I")
+                     "Gap Score", "Decline Risk", "Patchiness Risk", "Mean CI", "CV Value", "Moran's I")
   missing_cols <- setdiff(required_cols, colnames(field_details_table))
   
   if (length(missing_cols) > 0) {
@@ -714,10 +714,10 @@ generate_field_alerts <- function(field_details_table) {
           any(`Decline Risk` == "Low") ~ "Low",
           TRUE ~ "Unknown"
         ),
-        highest_weed_risk = case_when(
-          any(`Weed Risk` == "High") ~ "High",
-          any(`Weed Risk` == "Moderate") ~ "Moderate",
-          any(`Weed Risk` == "Low") ~ "Low",
+        highest_patchiness_risk = case_when(
+          any(`Patchiness Risk` == "High") ~ "High",
+          any(`Patchiness Risk` == "Medium") ~ "Medium",
+          any(`Patchiness Risk` == "Minimal") ~ "Minimal",
           TRUE ~ "Unknown"
         ),
         avg_mean_ci = mean(`Mean CI`, na.rm = TRUE),
@@ -743,12 +743,12 @@ generate_field_alerts <- function(field_details_table) {
     }
     # Priority 3: No alert (no stress)
     
-    # Keep other alerts for decline risk, weed risk, gap score
+    # Keep other alerts for decline risk, patchiness risk, gap score
     if (field_summary$highest_decline_risk %in% c("High", "Very-high")) {
       field_alerts <- c(field_alerts, "Growth decline observed")
     }
-    if (field_summary$highest_weed_risk == "High") {
-      field_alerts <- c(field_alerts, "Increased weed presence")
+    if (field_summary$highest_patchiness_risk == "High") {
+      field_alerts <- c(field_alerts, "High patchiness detected - recommend scouting")
     }
     if (field_summary$max_gap_score > 20) {
       field_alerts <- c(field_alerts, "Gaps present - recommend review")
@@ -859,7 +859,7 @@ if (!exists("field_details_table") || is.null(field_details_table)) {
         TCH_Forecasted = NA_real_,
         Gap_Score = NA_real_,
         Decline_Risk = NA_character_,
-        Weed_Risk = NA_character_,
+        Patchiness_Risk = NA_character_,
         Mean_CI = NA_real_,
         CV = NA_real_,
         Morans_I = NA_real_
@@ -1410,7 +1410,7 @@ tryCatch({
           kpi_parts <- c(
             kpi_parts,
             sprintf("**Gap:** %.0f", field_kpi$Gap_Score),
-            sprintf("**Weed:** %s", field_kpi$Weed_Pressure_Risk),
+            sprintf("**Patchiness:** %s", field_kpi$Patchiness_Risk),
             sprintf("**Decline:** %s", field_kpi$Decline_Severity)
           )
           
@@ -1518,7 +1518,7 @@ if (!exists("field_details_table") || is.null(field_details_table) || nrow(field
     # Ensure all expected KPI columns exist; add as NA if missing
     expected_cols <- c("Field_id", "Mean_CI", "CV", "TCH_Forecasted", "Gap_Score", 
                        "Trend_Interpretation", "Weekly_CI_Change", "Uniformity_Interpretation",
-                       "Decline_Severity", "Weed_Pressure_Risk")
+                       "Decline_Severity", "Patchiness_Risk")
     for (col in expected_cols) {
       if (!col %in% names(field_details_table)) {
         field_details_table[[col]] <- NA
@@ -1553,7 +1553,7 @@ if (!exists("field_details_table") || is.null(field_details_table) || nrow(field
         `Yield Forecast (t/ha)` = TCH_Forecasted,
         `Gap Score` = Gap_Score,
         `Decline Risk` = Decline_Severity,
-        `Weed Risk` = Weed_Pressure_Risk,
+        `Patchiness Risk` = Patchiness_Risk,
         `CV Value` = CV
       )
   } else {
@@ -1566,7 +1566,7 @@ if (!exists("field_details_table") || is.null(field_details_table) || nrow(field
         `Yield Forecast (t/ha)` = TCH_Forecasted,
         `Gap Score` = Gap_Score,
         `Decline Risk` = Decline_Severity,
-        `Weed Risk` = Weed_Pressure_Risk,
+        `Patchiness Risk` = Patchiness_Risk,
         `CV Value` = CV
       )
   }
@@ -1634,11 +1634,11 @@ CI values typically range from 0 (bare soil or severely stressed vegetation) to
    
    - **TCH Forecasted:** Provides yield predictions (tons cane per hectare) for mature fields (typically over 240 days old), using a machine learning model trained on historical CI and yield data. Helps plan harvest timing and logistics.
    
-   - **Weed Presence Score:** Detects rapid CI increases between weeks as a proxy for weed outbreaks in young fields (< 8 months old). After 8 months, canopy closure prevents weed growth. Risk levels based on percentage of pixels showing rapid growth (> 2.0 CI units increase):
-     - **Low:** < 10% of field area (minimal weed presence)
-     - **Moderate:** 10–25% (monitor and scout)
-     - **High:** > 25% (requires immediate intervention)
-     - **Note:** Mature fields (≥ 8 months) show "Canopy closed - Low weed risk" as the closed canopy suppresses weed growth.
+   - **Field Patchiness Score:** Measures field heterogeneity using the Gini coefficient, detecting spatial variation in crop health. High patchiness (Gini > 0.12) may indicate irrigation, pest, or fertility issues requiring targeted scouting:
+     - **Low:** Gini < 0.08 (excellent uniformity, minimal intervention needed)
+     - **Medium:** Gini 0.08–0.12 (acceptable variation, routine monitoring)
+     - **High:** Gini > 0.12 (poor uniformity, recommend field scouting)
+     - **Note:** Young crops (< 3 months) naturally show higher patchiness as they establish; this decreases with canopy closure.
    
    - **Gap Filling Score:** Indicates the proportion of a field with low CI values (lowest 25% of the distribution), highlighting areas with poor crop establishment or gaps that may need replanting.