foo:

metrics_stats.py

@@ -148,21 +148,46 @@ def calculate_phenocam_stats(phenocam_ts):
     }
 
 
-def _s2_kept_date_set(base: Path, strategy: str) -> set:
+def _s2_gcc_series_from_preselection(base: Path):
+    """Build the raw S2 GCC series from s2_preselection.json.
+
+    Uses the 3x3 site-window band means stored per raw S2 acquisition and
+    computes GCC = b03 / (b02 + b03 + b04). Scale cancels, so DN vs
+    reflectance is irrelevant. Returns (all_gcc, flags) where all_gcc maps
+    YYYY-MM-DD -> gcc for every row with a positive band sum, and flags maps
+    the same date key -> (excluded_aggressive, excluded_nonaggressive).
+    """
     path = base / "raw" / "preselection" / "s2_preselection.json"
     if not path.exists():
-        return set()
+        return {}, {}
     with open(path) as f:
         rows = json.load(f)
-    key = f"excluded_{strategy}"
+    all_gcc: dict = {}
-    out = set()
+    flags: dict = {}
     for e in rows:
-        if e.get(key):
-            continue
         nk = _norm_date_key(e.get("date"))
-        if nk:
+        if not nk:
-            out.add(nk)
+            continue
-    return out
+        try:
+            b02 = float(e.get("b02"))
+            b03 = float(e.get("b03"))
+            b04 = float(e.get("b04"))
+        except (TypeError, ValueError):
+            continue
+        total = b02 + b03 + b04
+        if not np.isfinite(total) or total <= 0:
+            continue
+        gcc = b03 / total
+        if not np.isfinite(gcc):
+            continue
+        if nk in all_gcc:
+            continue
+        all_gcc[nk] = float(gcc)
+        flags[nk] = (
+            bool(e.get("excluded_aggressive")),
+            bool(e.get("excluded_nonaggressive")),
+        )
+    return all_gcc, flags
 
 
 def _whittaker_smooth_dict(obs_dates, obs_values, lam: float, n_min: int = 3):
@@ -221,33 +246,27 @@ def calculate_all_metrics(season, site_name, site_position):
         results["phenocam_stats"] = phenocam_stats
 
     baseline = {}
-    s2_ts = {}
+    all_gcc, flags = _s2_gcc_series_from_preselection(base)
-    for sub in ("processed_aggressive_sigma20", "processed_nonaggressive_sigma20"):
+    if all_gcc:
-        p = base / sub / "gcc" / "s2" / "timeseries.json"
+        m0 = calculate_temporal_metrics(all_gcc, phenocam_ts)
-        if p.exists():
-            s2_ts = load_timeseries(p)
-            if s2_ts:
-                break
-    if s2_ts:
-        m0 = calculate_temporal_metrics(s2_ts, phenocam_ts)
         if m0:
             baseline["s2"] = m0
-        for strategy in ("aggressive", "nonaggressive"):
+        for strategy, flag_idx in (("aggressive", 0), ("nonaggressive", 1)):
-            kept = _s2_kept_date_set(base, strategy)
+            kept_items = sorted(
-            filtered = [
+                (
-                (k, v)
+                    (d, g)
-                for k, v in sorted(
+                    for d, g in all_gcc.items()
-                    s2_ts.items(), key=lambda x: _norm_date_key(x[0]) or ""
+                    if d in flags and not flags[d][flag_idx]
+                ),
+                key=lambda x: x[0],
             )
-                if _norm_date_key(k) in kept and v is not None
+            if not kept_items:
-            ]
-            if not filtered:
                 continue
-            sub_ts = dict(filtered)
+            kept_ts = dict(kept_items)
-            mcf = calculate_temporal_metrics(sub_ts, phenocam_ts)
+            mcf = calculate_temporal_metrics(kept_ts, phenocam_ts)
             if mcf:
                 baseline.setdefault("s2_cloudfree", {})[strategy] = mcf
-            obs_d, obs_v = zip(*filtered)
+            obs_d, obs_v = zip(*kept_items)
             smooth = _whittaker_smooth_dict(obs_d, obs_v, WHITTAKER_LAMBDA_DAYS_SQ)
             if smooth:
                 mw = calculate_temporal_metrics(smooth, phenocam_ts)

requirements.txt

@@ -4,6 +4,7 @@ openeo
 python-dotenv
 netCDF4
 numpy
+timesat
 requests
 scipy
 matplotlib

run.py

@@ -17,6 +17,7 @@ from preparation import (
 )
 from metrics_indices import create_prepared_fusion_timeseries
 from metrics_stats import calculate_all_metrics
+from phenology_timesat import write_phenocam_phenology_for_site
 
 
 def run_pipeline(season, site_position, site_name):
@@ -27,6 +28,9 @@ def run_pipeline(season, site_position, site_name):
         # download_s3(season, site_position, site_name)
         # download_phenocam(season, site_position, site_name)
 
+        print(f"PhenoCam phenology (50 % amplitude): {site_name}, {season}")
+        write_phenocam_phenology_for_site(site_name, season)
+
         print(f"Creating preselection timeseries: {site_name}, {season}")
         create_timeseries(season, site_position, site_name)
 

webapp/fusion.html

@@ -44,6 +44,7 @@
                 <a href="fusion.html" class="active">Fusion</a>
                 <a href="postprocessed.html">Postprocessed</a>
                 <a href="metrics.html">Metrics</a>
+                <a href="phenology.html">Phenology</a>
             </div>
             <h1 id="siteName">Innsbruck</h1>
             <div class="season-row"><h2 id="season">2024</h2><span class="download-links" id="downloadLinks"></span></div>

webapp/index.html

@@ -25,6 +25,7 @@
         .site-info h2 { margin: 0 0 20px 0; font-size: 18px; color: #666; }
         .phenocam-label { font-size: 12px; margin-bottom: 5px; color: #666; }
         .phenocam-date { font-size: 11px; margin-top: 5px; color: #999; }
+        .timeseries-phenology { font-size: 11px; color: #444; line-height: 1.45; margin-top: 6px; white-space: pre-line; }
         .phenocam-image { width: 100%; height: 200px; object-fit: contain; border: 1px solid #ccc; }
         .sitemap { height: 200px; border: 1px solid #ccc; margin-top: 32px; }
         #greennesstimeseries { margin-top: 0; }
@@ -54,6 +55,7 @@
             <a href="fusion.html">Fusion</a>
             <a href="postprocessed.html">Postprocessed</a>
             <a href="metrics.html">Metrics</a>
+            <a href="phenology.html">Phenology</a>
         </div>
         <div class="slider-container">
             <input type="range" id="dateSlider" min="0" max="365" value="0">
@@ -70,6 +72,7 @@
             <div class="header-col">
                 <div class="timeseries-label">Greenness Index Timeseries</div>
                 <canvas id="greennesstimeseries" class="timeseries"></canvas>
+                <div id="phenocamPhenology" class="timeseries-phenology"></div>
             </div>
             <div class="header-col">
                 <div id="sitemap" class="sitemap"></div>
@@ -172,6 +175,8 @@
         let timeseries = { s2: [], fusion: [], s3: [] };
         let greennessTimeseries = { s2: [], fusion: [], s3: [] };
         let phenocamGreennessTimeseries = [];
+        /** @type {{ green_up_50pct_date: string | null, green_down_50pct_date: string | null } | null} */
+        let phenocamPhenology = null;
         
         // Add site marker to all maps
         for (const source of ["s2", "fusion", "s3"]) {
@@ -180,6 +185,39 @@
         
         let syncing = false;
         const allMaps = Object.values(maps);
+        function updatePhenocamPhenologyText() {
+            const el = document.getElementById("phenocamPhenology");
+            if (!el) return;
+            if (!phenocamPhenology || (phenocamPhenology.green_up_50pct_date == null && phenocamPhenology.green_down_50pct_date == null)) {
+                el.textContent = "";
+                return;
+            }
+            const up = phenocamPhenology.green_up_50pct_date || "—";
+            const dn = phenocamPhenology.green_down_50pct_date || "—";
+            el.textContent = `* Green-up: ${up}\n* Green-down: ${dn}`;
+        }
+
+        const PHENOLOGY_VLINE = "rgba(150, 200, 255, 0.95)";
+
+        function strokePhenologyVlines(ctx, minDate, maxDate, dateRange, plotW, pad, plotH) {
+            if (!phenocamPhenology) return;
+            for (const iso of [phenocamPhenology.green_up_50pct_date, phenocamPhenology.green_down_50pct_date]) {
+                if (!iso) continue;
+                const d = new Date(iso);
+                if (isNaN(d.getTime()) || d < minDate || d > maxDate) continue;
+                const px = pad + ((d - minDate) / dateRange) * plotW;
+                ctx.save();
+                ctx.setLineDash([4, 3]);
+                ctx.strokeStyle = PHENOLOGY_VLINE;
+                ctx.lineWidth = 1.5;
+                ctx.beginPath();
+                ctx.moveTo(px, pad);
+                ctx.lineTo(px, pad + plotH);
+                ctx.stroke();
+                ctx.restore();
+            }
+        }
+
         const syncMaps = (sourceMap) => {
             if (syncing) return;
             syncing = true;
@@ -197,18 +235,21 @@
         async function loadTimeseries() {
             metricsData = null;
             const fusionPath = getFusionPath();
-            const [s2, fusion, s3, s2gcc, fusiongcc, s3gcc, phenocam] = await Promise.all([
+            const [s2, fusion, s3, s2gcc, fusiongcc, s3gcc, phenocam, phenPhen] = await Promise.all([
                 fetch(`data/${siteName}/${season}/processed_${strategy}_sigma${sigma}/ndvi/s2/timeseries.json`).then(r => r.json()).catch(() => []),
                 fetch(`data/${siteName}/${season}/${fusionPath}/ndvi/fusion/timeseries.json`).then(r => r.json()).catch(() => []),
                 fetch(`data/${siteName}/${season}/processed_${strategy}_sigma${sigma}/ndvi/s3/timeseries.json`).then(r => r.json()).catch(() => []),
                 fetch(`data/${siteName}/${season}/processed_${strategy}_sigma${sigma}/gcc/s2/timeseries.json`).then(r => r.json()).catch(() => []),
                 fetch(`data/${siteName}/${season}/${fusionPath}/gcc/fusion/timeseries.json`).then(r => r.json()).catch(() => []),
                 fetch(`data/${siteName}/${season}/processed_${strategy}_sigma${sigma}/gcc/s3/timeseries.json`).then(r => r.json()).catch(() => []),
-                fetch(`data/${siteName}/${season}/raw/phenocam/phenocam_gcc.json`).then(r => r.json()).catch(() => [])
+                fetch(`data/${siteName}/${season}/raw/phenocam/phenocam_gcc.json`).then(r => r.json()).catch(() => []),
+                fetch(`data/${siteName}/${season}/raw/phenocam/phenocam_phenology.json`).then(r => r.ok ? r.json() : null).catch(() => null)
             ]);
             timeseries = { s2, fusion, s3 };
             greennessTimeseries = { s2: s2gcc, fusion: fusiongcc, s3: s3gcc };
             phenocamGreennessTimeseries = phenocam;
+            phenocamPhenology = phenPhen && (phenPhen.green_up_50pct_date != null || phenPhen.green_down_50pct_date != null) ? phenPhen : null;
+            updatePhenocamPhenologyText();
             
             // Load all scenario GCC timeseries for comparison
             const scenarios = [
@@ -289,10 +330,11 @@
                 ctx.fillStyle = "#888";
                 const axisY = pad + plotH;
                 for (const t of data) ctx.fillRect(x(t.date) - 1, axisY - 1, 2, 2);
-                
+                strokePhenologyVlines(ctx, minDate, maxDate, dateRange, plotW, pad, plotH);
                 const xPos = x(currentDate);
                 ctx.strokeStyle = "#f00";
                 ctx.lineWidth = 2;
+                ctx.setLineDash([]);
                 ctx.beginPath();
                 ctx.moveTo(xPos, pad);
                 ctx.lineTo(xPos, pad + plotH);
@@ -360,11 +402,12 @@
             ctx.fillStyle = "#888";
             const axisY = pad + plotH;
             for (const t of data) ctx.fillRect(x(t.date) - 1, axisY - 1, 2, 2);
-            
+            strokePhenologyVlines(ctx, minDate, maxDate, dateRange, plotW, pad, plotH);
             const currentDate = dateFromDays(parseInt(slider.value));
             const xPos = x(currentDate);
             ctx.strokeStyle = "#f00";
             ctx.lineWidth = 2;
+            ctx.setLineDash([]);
             ctx.beginPath();
             ctx.moveTo(xPos, pad);
             ctx.lineTo(xPos, pad + plotH);
@@ -460,17 +503,17 @@
             ctx.fillStyle = "#888";
             const axisY = pad + plotH;
             for (const t of [...s2data, ...fusiondata, ...phenocamdata]) ctx.fillRect(x(t.date) - 1, axisY - 1, 2, 2);
-            
+            strokePhenologyVlines(ctx, minDate, maxDate, dateRange, plotW, pad, plotH);
             const legendX = pad + plotW - 80, legendY = pad + 5;
             ctx.font = "9px sans-serif";
             if (s2data.length) { ctx.strokeStyle = "#ff6600"; ctx.beginPath(); ctx.moveTo(legendX, legendY); ctx.lineTo(legendX + 15, legendY); ctx.stroke(); ctx.fillStyle = "#000"; ctx.fillText("S2", legendX + 18, legendY + 3); }
             if (fusiondata.length) { ctx.strokeStyle = "#9900cc"; ctx.beginPath(); ctx.moveTo(legendX, legendY + 12); ctx.lineTo(legendX + 15, legendY + 12); ctx.stroke(); ctx.fillStyle = "#000"; ctx.fillText("Fusion", legendX + 18, legendY + 15); }
             if (phenocamdata.length) { ctx.strokeStyle = "#00aa00"; ctx.beginPath(); ctx.moveTo(legendX, legendY + 24); ctx.lineTo(legendX + 15, legendY + 24); ctx.stroke(); ctx.fillStyle = "#000"; ctx.fillText("PhenoCam", legendX + 18, legendY + 27); }
-            
             const currentDate = dateFromDays(parseInt(slider.value));
             const xPos = x(currentDate);
             ctx.strokeStyle = "#f00";
             ctx.lineWidth = 2;
+            ctx.setLineDash([]);
             ctx.beginPath();
             ctx.moveTo(xPos, pad);
             ctx.lineTo(xPos, pad + plotH);
@@ -545,6 +588,7 @@
                     ctx.fillText(name, legendX + 18, legendY + i * 12 + 3);
                 }
             });
+            strokePhenologyVlines(ctx, minDate, maxDate, dateRange, plotW, pad, plotH);
         }
         
         function drawMetricsTable() {

webapp/metrics.html

@@ -38,6 +38,7 @@
             <a href="fusion.html">Fusion</a>
             <a href="postprocessed.html">Postprocessed</a>
             <a href="metrics.html" class="active">Metrics</a>
+            <a href="phenology.html">Phenology</a>
         </div>
         <h1 id="siteName">Metrics</h1>
         <div class="selectors">

webapp/postprocessed.html

@@ -44,6 +44,7 @@
                 <a href="fusion.html">Fusion</a>
                 <a href="postprocessed.html" class="active">Postprocessed</a>
                 <a href="metrics.html">Metrics</a>
+                <a href="phenology.html">Phenology</a>
             </div>
             <h1 id="siteName">Innsbruck</h1>
             <div class="season-row"><h2 id="season">2024</h2><span class="download-links" id="downloadLinks"></span></div>

webapp/prepared.html

@@ -44,6 +44,7 @@
                 <a href="fusion.html">Fusion</a>
                 <a href="postprocessed.html">Postprocessed</a>
                 <a href="metrics.html">Metrics</a>
+                <a href="phenology.html">Phenology</a>
             </div>
             <h1 id="siteName">Innsbruck</h1>
             <div class="season-row"><h2 id="season">2024</h2><span class="download-links" id="downloadLinks"></span></div>

webapp/preselection.html

@@ -43,6 +43,7 @@
                 <a href="fusion.html">Fusion</a>
                 <a href="postprocessed.html">Postprocessed</a>
                 <a href="metrics.html">Metrics</a>
+                <a href="phenology.html">Phenology</a>
             </div>
             <h1 id="siteName">Innsbruck</h1>
             <div class="season-row"><h2 id="season">2024</h2><span class="download-links" id="downloadLinks"></span></div>