Handle cloud-coverage.

clouds.py

@@ -0,0 +1,43 @@
+import json
+from pathlib import Path
+from datetime import datetime
+
+
+def detect_clouds(year, site_name):
+    output_file = Path(f"data/{site_name}/{year}/clouds.json")
+    clouds = {"s2": [], "s3": []}
+    
+    for source in ["s2", "s3"]:
+        timeseries_file = Path(f"data/{site_name}/{year}/ndvi/{source}/timeseries.json")
+        if not timeseries_file.exists():
+            print(f"[CLOUDS-{source.upper()}] No timeseries.json found")
+            continue
+        
+        print(f"[CLOUDS-{source.upper()}] Processing {timeseries_file}...")
+        
+        with open(timeseries_file) as f:
+            timeseries = json.load(f)
+        
+        entries = [(e, datetime.fromisoformat(e["date"].replace("Z", "+00:00"))) for e in timeseries if e["ndvi"] is not None]
+        
+        for entry, entry_date in entries:
+            # Use 14-day window for seasonal context, require NDVI < 0.3 and >0.15 below max
+            window_ndvi = [e["ndvi"] for e, d in entries if abs((d - entry_date).days) <= 14]
+            
+            if len(window_ndvi) < 3:
+                continue
+            
+            max_ndvi = max(window_ndvi)
+            threshold = max_ndvi - 0.15
+            
+            if entry["ndvi"] < threshold and entry["ndvi"] < 0.3:
+                clouds[source].append(entry["filename"])
+        
+        print(f"[CLOUDS-{source.upper()}] Found {len(clouds[source])} cloud-covered files")
+    
+    output_file.parent.mkdir(parents=True, exist_ok=True)
+    with open(output_file, "w") as f:
+        json.dump(clouds, f, indent=2)
+    
+    print(f"[CLOUDS] Saved: {output_file}")
+