feat: GeoScene frontend POC + Docker deploy for remote host

Migrate maps to @geoscene/core, polish monitoring/alerts UX, fix timeline
basemap flicker and district alert regions, and ship compose/nginx Docker
deploy assets with CBPOA_ROOT data mounts.

Co-authored-by: Cursor <cursoragent@cursor.com>

backend/utils/daily_risk_avg.py

@@ -0,0 +1,81 @@
+"""Fast daily city-wide mean risk_1d with on-disk cache.
+
+Avoids re-parsing ~45MB GeoJSON on every /analysis/trend request.
+"""
+from __future__ import annotations
+
+import json
+import logging
+from functools import lru_cache
+from pathlib import Path
+
+from config import DATA_DIR, PROJECT_ROOT
+
+logger = logging.getLogger(__name__)
+
+_CACHE_PATH = PROJECT_ROOT / "processed" / "daily_avg_risk.json"
+
+
+def _read_disk_cache() -> dict[str, float]:
+    if not _CACHE_PATH.exists():
+        return {}
+    try:
+        raw = json.loads(_CACHE_PATH.read_text(encoding="utf-8"))
+        return {str(k): float(v) for k, v in raw.items()}
+    except (OSError, json.JSONDecodeError, TypeError, ValueError):
+        return {}
+
+
+def _write_disk_cache(cache: dict[str, float]) -> None:
+    try:
+        _CACHE_PATH.parent.mkdir(parents=True, exist_ok=True)
+        _CACHE_PATH.write_text(
+            json.dumps(cache, ensure_ascii=False, separators=(",", ":")),
+            encoding="utf-8",
+        )
+    except OSError as e:
+        logger.warning("Failed to persist daily avg risk cache: %s", e)
+
+
+def _compute_mean_risk_1d(filepath: Path) -> float:
+    """Parse one risk GeoJSON and return mean risk_1d (0 if empty/missing)."""
+    try:
+        with open(filepath, "r", encoding="utf-8") as f:
+            geojson = json.load(f)
+    except (OSError, json.JSONDecodeError) as e:
+        logger.warning("Failed to parse %s: %s", filepath, e)
+        return 0.0
+
+    total = 0.0
+    n = 0
+    for feature in geojson.get("features", []):
+        props = feature.get("properties") or {}
+        r = props.get("risk_1d")
+        if r is None:
+            continue
+        total += float(r)
+        n += 1
+    return round(total / n, 4) if n else 0.0
+
+
+@lru_cache(maxsize=64)
+def daily_avg_risk(date_yyyymmdd: str) -> float:
+    """Mean risk_1d for YYYYMMDD. Memory + disk cached."""
+    disk = _read_disk_cache()
+    if date_yyyymmdd in disk:
+        return disk[date_yyyymmdd]
+
+    filepath = DATA_DIR / f"risk_{date_yyyymmdd}.geojson"
+    if not filepath.exists():
+        return 0.0
+
+    avg = _compute_mean_risk_1d(filepath)
+    disk[date_yyyymmdd] = avg
+    _write_disk_cache(disk)
+    return avg
+
+
+def warm_daily_avg_risk(dates: list[str]) -> None:
+    """Precompute missing dates into the disk cache (blocking)."""
+    for d in dates:
+        daily_avg_risk(d)