Update app.py

app.py

@@ -743,123 +743,118 @@ if "active_site" not in st.session_state:
 
 
 # -------------------- LANDING PAGE --------------------
-def landing_page():
-
-# Background hero with placeholder image (replace BACKGROUND_URL with your image path or URL)
-
-    BACKGROUND_URL = "/app/background_placeholder.jpg"  # <- replace this (or provide URL)
-
-    st.markdown(f"""
-
-    <div style="
-
-    background-image: url('{BACKGROUND_URL}');
-
-    background-size: cover;
-
-    background-position: center;
-
-    padding: 48px 28px;
-
-    border-radius: 12px;
-
-    margin-bottom: 18px;
-
-    position: relative;
-
-    ">
-
-    <div style="background: rgba(11,11,11,0.55); padding:22px; border-radius:10px; max-width:900px;">
-
-    <h1 style='color:#FF8C00; margin:0'>GeoMate V2</h1>
-
-    <p style='color:#e8eef6; margin:6px 0 0; font-size:16px'>
-
-      AI geotechnical copilot — soil recognition, classification, locator (EE), RAG-powered Q&A, and dynamic reports.
-
-    </p>
-
-    <div style='margin-top:8px; color:#cfcfcf; font-size:13px'>
-
-      Quick: Classifier • GSD • Locator • RAG • Reports
-
-    </div>
-
-  </div>
-
-</div>
-
-""", unsafe_allow_html=True)
-
-
-
-st.markdown("<div style='display:flex;align-items:center;gap:12px'>"
-
-            "<div style='width:76px;height:76px;border-radius:14px;background:linear-gradient(135deg,#ff7a00,#ff3a3a);display:flex;align-items:center;justify-content:center;box-shadow:0 8px 24px rgba(0,0,0,0.6)'>"
-
-            "<span style='font-size:34px'>🛰️</span></div>"
-
-            "<div><h1 style='margin:0;color:#FF8C00'>GeoMate V2</h1>"
-
-            "<div class='small-muted'>AI geotechnical copilot — soil recognition, classification, locator, RAG, and reports</div></div></div>", unsafe_allow_html=True)
-
-st.markdown("---")
-
-col1, col2 = st.columns([2,1])
-
-with col1:
-
-    st.markdown("<div class='gm-card'>", unsafe_allow_html=True)
-
-    st.write("GeoMate is built to help geotechnical engineers: classify soils (USCS/AASHTO), plot GSD, fetch Earth Engine data, chat with a RAG-backed LLM, and generate professional geotechnical reports.")
-
-    st.markdown("</div>", unsafe_allow_html=True)
-
-    st.markdown("### Quick Actions")
-
-    c1, c2, c3 = st.columns(3)
-
-    if c1.button("🧪 Classifier"):
-
-        st.session_state["page"] = "Classifier"; st.rerun()
-
-    if c2.button("📈 GSD Curve"):
-
-        st.session_state["page"] = "GSD"; st.rerun()
-
-    if c3.button("🌍 Locator"):
-
-        st.session_state["page"] = "Locator"; st.rerun()
-
-    c4, c5, c6 = st.columns(3)
-
-    if c4.button("🤖 GeoMate Ask"):
-
-        st.session_state["page"] = "RAG"; st.rerun()
-
-    if c5.button("📷 OCR"):
-
-        st.session_state["page"] = "OCR"; st.rerun()
-
-    if c6.button("📑 Reports"):
-
-        st.session_state["page"] = "Reports"; st.rerun()
-
-with col2:
-
-    st.markdown("<div class='gm-card' style='text-align:center'>", unsafe_allow_html=True)
-
-    st.markdown("<h3 style='color:#FF8C00'>Live Site Summary</h3>", unsafe_allow_html=True)
-
-    site = st.session_state["sites"][st.session_state["active_site"]]
-
-    st.write(f"Site: **{site.get('Site Name')}**")
-
-    st.write(f"USCS: {site.get('USCS')}, AASHTO: {site.get('AASHTO')}")
+import streamlit as st
 
-    st.write(f"GSD saved: {'Yes' if site.get('GSD') else 'No'}")
+def landing_page():
+    # Fixed gradient background (no slideshow)
+    st.markdown("""
+        <style>
+        .stApp {
+            background: linear-gradient(135deg, #000000 0%, #1c1c1c 50%, #2e004f 100%);
+            color: #ffffff;
+            font-family: 'Segoe UI', sans-serif;
+        }
+        .gm-hero {
+            padding: 48px 28px;
+            border-radius: 16px;
+            margin-bottom: 22px;
+            background: linear-gradient(135deg, rgba(11,11,11,0.8) 0%, rgba(20,0,40,0.75) 100%);
+            box-shadow: 0 8px 28px rgba(0,0,0,0.65);
+            text-align: center;
+            animation: fadeIn 1.8s ease-in-out;
+        }
+        .gm-hero h1 {
+            font-size: 3.5rem;
+            font-weight: 900;
+            margin: 0;
+            background: linear-gradient(90deg,#FF8C00,#a020f0);
+            -webkit-background-clip: text;
+            -webkit-text-fill-color: transparent;
+        }
+        .gm-hero p {
+            font-size: 1.2rem;
+            margin-top: 10px;
+            color: #e0e0e0;
+        }
+        .gm-card {
+            background: rgba(25,25,25,0.85);
+            padding: 18px;
+            border-radius: 12px;
+            box-shadow: 0 6px 18px rgba(0,0,0,0.5);
+        }
+        .quick-btn {
+            display: inline-block;
+            margin: 6px;
+            padding: 12px 24px;
+            border-radius: 50px;
+            background: linear-gradient(90deg, #ff4d00, #a020f0);
+            color: white !important;
+            font-weight: 600;
+            text-decoration: none;
+            transition: all 0.3s ease;
+        }
+        .quick-btn:hover {
+            background: linear-gradient(90deg, #a020f0, #ff4d00);
+            transform: translateY(-3px);
+            box-shadow: 0 6px 16px rgba(0,0,0,0.4);
+        }
+        @keyframes fadeIn {
+            from { opacity:0; transform: translateY(40px);}
+            to { opacity:1; transform: translateY(0);}
+        }
+        </style>
+    """, unsafe_allow_html=True)
+
+    # Hero Section
+    st.markdown("""
+        <div class="gm-hero">
+            <h1>GeoMate V2</h1>
+            <p>AI Geotechnical Copilot — soil recognition, classification, 
+            Earth Engine locator, RAG-powered Q&A, OCR, and dynamic reports.</p>
+        </div>
+    """, unsafe_allow_html=True)
+
+    # Content layout
+    col1, col2 = st.columns([2, 1])
+
+    with col1:
+        st.markdown("<div class='gm-card'>", unsafe_allow_html=True)
+        st.write(
+            "GeoMate helps geotechnical engineers: classify soils (USCS/AASHTO), "
+            "plot grain size distributions (GSD), fetch Earth Engine data, chat with a RAG-backed LLM, "
+            "run OCR on site logs, and generate professional reports."
+        )
+        st.markdown("</div>", unsafe_allow_html=True)
+
+        st.markdown("### 🚀 Quick Actions")
+        c1, c2, c3 = st.columns(3)
+        if c1.button("🧪 Classifier"):
+            st.session_state["page"] = "Classifier"; st.rerun()
+        if c2.button("📈 Soil Recognizer"):
+            st.session_state["page"] = "Soil recognizer"; st.rerun()
+        if c3.button("🌍 Locator"):
+            st.session_state["page"] = "Locator"; st.rerun()
+
+        c4, c5, c6 = st.columns(3)
+        if c4.button("🤖 Ask GeoMate"):
+            st.session_state["page"] = "RAG"; st.rerun()
+        if c5.button("📷 OCR"):
+            st.session_state["page"] = "OCR"; st.rerun()
+        if c6.button("📑 Reports"):
+            st.session_state["page"] = "Reports"; st.rerun()
+
+    with col2:
+        st.markdown("<div class='gm-card' style='text-align:center'>", unsafe_allow_html=True)
+        st.markdown("<h3 style='color:#FF8C00'>📊 Live Site Summary</h3>", unsafe_allow_html=True)
+        if "sites" in st.session_state and st.session_state.get("active_site") is not None:
+            site = st.session_state["sites"][st.session_state["active_site"]]
+            st.write(f"**Site:** {site.get('Site Name','N/A')}")
+            st.write(f"USCS: {site.get('USCS','-')} | AASHTO: {site.get('AASHTO','-')}")
+            st.write(f"GSD Saved: {'✅' if site.get('GSD') else '❌'}")
+        else:
+            st.info("No active site selected.")
+        st.markdown("</div>", unsafe_allow_html=True)
 
-    st.markdown("</div>", unsafe_allow_html=True)
     
 # Soil Classifier page (conversational, step-by-step)
 def soil_classifier_page():
@@ -1068,20 +1063,16 @@ import geemap.foliumap as geemap
 import ee
 import matplotlib.pyplot as plt
 from datetime import datetime
-from io import BytesIO
-import base64
-import folium
-
 import tempfile
+from streamlit_folium import st_folium
+import folium
 
+# =====================================================
+# Map snapshot export
+# =====================================================
 def export_map_snapshot(m, width=800, height=600):
-    """
-    Export geemap Map object to PNG snapshot (returns bytes).
-    - m: geemap.Map
-    - width, height: dimensions of snapshot
-    """
+    """Export geemap Map object to PNG snapshot (returns bytes)."""
     try:
-        # geemap has a built-in screenshot method
         tmpfile = tempfile.NamedTemporaryFile(delete=False, suffix=".png")
         m.screenshot(filename=tmpfile.name, region=None, dimensions=(width, height))
         with open(tmpfile.name, "rb") as f:
@@ -1090,16 +1081,10 @@ def export_map_snapshot(m, width=800, height=600):
         st.warning(f"Map snapshot failed: {e}")
         return None
 
-
+# =====================================================
+# Locator page
+# =====================================================
 def locator_page():
-    """
-    Robust locator page:
-    - Uses initialize_ee() auth routine (expects EARTHENGINE_TOKEN / SERVICE_ACCOUNT in env)
-    - Shows interactive map with basemaps and overlays
-    - Captures ROI drawn on the map
-    - Computes summaries and saves them into active site and soil_json
-    """
-
     st.title("🌍 GeoMate Interactive Earth Explorer")
     st.markdown(
         "Draw a polygon (or rectangle) on the map using the drawing tool. "
@@ -1180,191 +1165,71 @@ def locator_page():
     # ----------------------------
     m = geemap.Map(center=[28.0, 72.0], zoom=5, plugin_Draw=True, draw_export=True, locate_control=True)
 
-    basemaps = [
-        "HYBRID", "ROADMAP", "TERRAIN", "SATELLITE",
-        "Esri.WorldImagery", "Esri.WorldTopoMap", "Esri.WorldShadedRelief",
-        "Esri.NatGeoWorldMap", "Esri.OceanBasemap",
-        "CartoDB.Positron", "CartoDB.DarkMatter",
-        "Stamen.Terrain", "Stamen.Watercolor",
-        "OpenStreetMap", "Esri.WorldGrayCanvas", "Esri.WorldStreetMap"
-    ]
-    for b in basemaps:
+    # Restore ROI (if available) as polygon on the map
+    if "roi_geojson" in st.session_state:
         try:
-            m.add_basemap(b)
-        except Exception:
-            pass
+            saved = st.session_state["roi_geojson"]
+            folium.GeoJson(saved, name="Saved ROI",
+                           style_function=lambda x: {"color": "red", "weight": 2, "fillOpacity": 0.1}).add_to(m)
+        except Exception as e:
+            st.warning(f"Could not re-add saved ROI: {e}")
 
     # ----------------------------
     # Datasets (DEM, Soil, Seismic, Flood, Landcover, NDVI)
     # ----------------------------
-    
-    # --- DEM ---
+    # DEM
     try:
-        dem = ee.Image("NASA/NASADEM_HGT/001")  # NASADEM ~30m global
-        dem_band_name = "elevation"
-        st.info("Using NASADEM dataset for elevation (30m).")
+        dem = ee.Image("NASA/NASADEM_HGT/001"); dem_band_name = "elevation"
     except Exception:
         try:
-            dem = ee.Image("USGS/SRTMGL1_003")  # SRTM ~30m fallback
-            dem_band_name = "elevation"
-            st.warning("Fallback to SRTM DEM (30m).")
+            dem = ee.Image("USGS/SRTMGL1_003"); dem_band_name = "elevation"
         except Exception:
-            dem = None
-            dem_band_name = None
-            st.error("No DEM dataset available.")
-    
-    # --- Soil Clay Fraction ---
-    soil_img = None
-    soil_band = None
-    chosen_soil_band = None
+            dem = None; dem_band_name = None
+
+    # Soil
+    soil_img = None; chosen_soil_band = None
     try:
         soil_img = ee.Image("OpenLandMap/SOL/SOL_CLAY-WFRACTION_USDA-3A1A1A_M/v02")
         bands = soil_img.bandNames().getInfo()
-        # interactive soil band selector
-        chosen_soil_band = st.selectbox(
-            "Select soil depth / clay band",
-            options=bands,
-            index=bands.index("b200") if "b200" in bands else 0
-        )
-        st.info(f"Using OpenLandMap Clay Fraction — Band: {chosen_soil_band}")
+        chosen_soil_band = st.selectbox("Select soil depth / clay band", options=bands, index=bands.index("b200") if "b200" in bands else 0)
     except Exception:
         try:
             soil_img = ee.Image("projects/soilgrids-isric/clay_mean")
             bands = soil_img.bandNames().getInfo()
-            chosen_soil_band = st.selectbox(
-                "Select soil depth (SoilGrids)",
-                options=bands,
-                index=0
-            )
-            st.warning(f"Fallback to SoilGrids Clay dataset — Band: {chosen_soil_band}")
+            chosen_soil_band = st.selectbox("Select soil depth (SoilGrids)", options=bands, index=0)
         except Exception:
-            soil_img = None
-            chosen_soil_band = None
-            st.error("No soil dataset available.")
-    
-    # --- Seismic Hazard ---
+            soil_img = None; chosen_soil_band = None
+
+    # Seismic
     try:
-        seismic_img = ee.Image("SEDAC/GSHAPSeismicHazard")
-        seismic_band = "gshap"
-        st.info("Using SEDAC Global Seismic Hazard dataset.")
+        seismic_img = ee.Image("SEDAC/GSHAPSeismicHazard"); seismic_band = "gshap"
     except Exception:
-        seismic_img = None
-        seismic_band = None
-        st.error("No seismic hazard dataset available.")
-    
-    # --- Flood Occurrence ---
+        seismic_img = None; seismic_band = None
+
+    # Flood
     try:
-        water = ee.Image("JRC/GSW1_4/GlobalSurfaceWater")
-        water_band = "occurrence"
-        st.info("Using JRC Global Surface Water Occurrence (1984–2020).")
+        water = ee.Image("JRC/GSW1_4/GlobalSurfaceWater"); water_band = "occurrence"
     except Exception:
-        water = None
-        water_band = None
-        st.error("No flood dataset available.")
-    
-    # --- Landcover ---
+        water = None; water_band = None
+
+    # Landcover
     try:
-        landcover = ee.Image("ESA/WorldCover/v200")
-        lc_band = "Map"
-        st.info("Using ESA WorldCover v200 (2020, 10m).")
+        landcover = ee.Image("ESA/WorldCover/v200"); lc_band = "Map"
     except Exception:
-        landcover = None
-        lc_band = None
-        st.error("No landcover dataset available.")
-    
-    # --- NDVI ---
+        landcover = None; lc_band = None
+
+    # NDVI
     try:
         ndvi_col = ee.ImageCollection("MODIS/061/MOD13A2").select("NDVI")
-        st.info("Using MODIS NDVI (16-day, 1km, global).")
     except Exception:
         ndvi_col = None
-        st.error("No NDVI dataset available.")
-    
-    # ----------------------------
-    # Add Layers to Map
+
     # ----------------------------
-    if dem:
-        try:
-            m.addLayer(
-                dem,
-                {"min": 0, "max": 4000, "palette": ["blue", "green", "brown", "white"]},
-                "DEM / Elevation"
-            )
-        except Exception:
-            pass
-    
-    if soil_img and chosen_soil_band:
-        try:
-            m.addLayer(
-                soil_img.select(chosen_soil_band),
-                {"min": 0.0, "max": 0.6, "palette": ["#ffffcc", "#c2e699", "#78c679", "#31a354"]},
-                f"Soil Clay Fraction ({chosen_soil_band})"
-            )
-        except Exception:
-            pass
-    
-    if seismic_img:
-        try:
-            m.addLayer(
-                seismic_img,
-                {"min": 0, "max": 1, "palette": ["white", "yellow", "red"]},
-                "Seismic Hazard"
-            )
-        except Exception:
-            pass
-    
-    if water:
-        try:
-            m.addLayer(
-                water.select(water_band),
-                {"min": 0, "max": 100, "palette": ["white", "blue"]},
-                "Flood Occurrence (%)"
-            )
-        except Exception:
-            pass
-    
-    if landcover:
-        try:
-            m.addLayer(
-                landcover,
-                {
-                    "min": 10,
-                    "max": 100,
-                    "palette": [
-                        "#006400", "#ffbb22", "#ffff4c", "#f096ff", "#fa0000",
-                        "#b4b4b4", "#f0f0f0", "#0064c8", "#0096a0", "#00cf75"
-                    ]
-                },
-                "Landcover (ESA WorldCover)"
-            )
-        except Exception:
-            pass
-    
-    try:
-        countries = ee.FeatureCollection("USDOS/LSIB_SIMPLE/2017")
-        m.addLayer(
-            countries.style(**{"color": "black", "fillColor": "00000000", "width": 1}),
-            {},
-            "Country Boundaries"
-        )
-    except Exception:
-        pass
-    
+    # Render map + capture draw ROI (only once with st_folium)
     # ----------------------------
-    from streamlit_folium import st_folium
-    import json
+    result = st_folium(m, width=800, height=600, returned_objects=["last_active_drawing"])
+    roi, coords, flat_coords = None, None, None
 
-    # --- Render geemap map ---
-    m.to_streamlit(height=600, responsive=True)
-
-    # Capture drawn ROI
-    result = st_folium(m, width=700, height=600, returned_objects=["last_active_drawing"])
-
-    roi = None
-    coords = None
-    flat_coords = None
-
-    # --- Get ROI from drawn feature ---
     if result and "last_active_drawing" in result and result["last_active_drawing"]:
         feat = result["last_active_drawing"]
         geom = feat.get("geometry")
@@ -1373,24 +1238,18 @@ def locator_page():
                 roi = ee.Geometry(geom)
                 coords = geom.get("coordinates", None)
                 st.session_state["roi_geojson"] = feat
-
-                # Flatten coordinates
                 if coords:
                     if geom["type"] in ["Polygon", "MultiPolygon"]:
                         flat_coords = [(lat, lon) for ring in coords for lon, lat in ring]
                     elif geom["type"] == "Point":
-                        lon, lat = coords
-                        flat_coords = [(lat, lon)]
+                        lon, lat = coords; flat_coords = [(lat, lon)]
                     elif geom["type"] == "LineString":
                         flat_coords = [(lat, lon) for lon, lat in coords]
-
-                if flat_coords:
-                    st.session_state["roi_coords"] = flat_coords  # ✅ Save for reuse
+                if flat_coords: st.session_state["roi_coords"] = flat_coords
                 st.success("✅ ROI captured!")
             except Exception as e:
-                st.error(f"Failed to convert drawn geometry to ee.Geometry: {e}")
+                st.error(f"Failed to convert geometry: {e}")
 
-    # --- Restore ROI from session if none drawn ---
     if roi is None and "roi_geojson" in st.session_state:
         saved = st.session_state["roi_geojson"]
         try:
@@ -1402,81 +1261,81 @@ def locator_page():
                     if geom["type"] in ["Polygon", "MultiPolygon"]:
                         flat_coords = [(lat, lon) for ring in coords for lon, lat in ring]
                     elif geom["type"] == "Point":
-                        lon, lat = coords
-                        flat_coords = [(lat, lon)]
+                        lon, lat = coords; flat_coords = [(lat, lon)]
                     elif geom["type"] == "LineString":
                         flat_coords = [(lat, lon) for lon, lat in coords]
-
-                if flat_coords:
-                    st.session_state["roi_coords"] = flat_coords  # ✅ Restore saved
-            st.info("♻️ ROI restored from earlier session")
+                if flat_coords: st.session_state["roi_coords"] = flat_coords
+            st.info("♻️ ROI restored from session")
         except Exception as e:
             st.warning(f"Could not restore ROI: {e}")
 
-    # --- Show coordinates below the map ---
+    # Show coordinates
     if "roi_coords" in st.session_state:
         st.markdown("### 📍 ROI Coordinates (Lat, Lon)")
         st.write(st.session_state["roi_coords"])
 
-    # --- Compute summaries ---
+    # ----------------------------
+    # Compute summaries
+    # ----------------------------
     if st.button("Compute Summaries"):
         if roi is None:
-            st.error("⚠️ No ROI found. Please draw a polygon/rectangle/circle and try again.")
+            st.error("⚠️ No ROI found. Please draw first.")
         else:
-            st.success("ROI ready — performing computations...")
-        # Here you can now use st.session_state["roi_coords"] for summaries
-        chosen_soil_band = None
-        if soil_img:
-            bands = soil_img.bandNames().getInfo()
-            chosen_soil_band = st.selectbox("Soil band to analyze", bands, index=bands.index(soil_band) if soil_band in bands else 0)
-
-        soil_val = safe_get_reduce(roi, soil_img.select(chosen_soil_band), chosen_soil_band, 1000) if soil_img and chosen_soil_band else None
-        elev_val = safe_get_reduce(roi, dem, dem_band_name, 1000)
-        seismic_val = safe_get_reduce(roi, seismic_img, seismic_band, 5000) if seismic_img else None
-        flood_val = safe_get_reduce(roi, water.select(water_band), water_band, 30) if water else None
-        lc_stats = safe_reduce_histogram(roi, landcover, lc_band, 30) if landcover else {}
-        ndvi_ts = []
-        if ndvi_col:
-            end = datetime.utcnow().strftime("%Y-%m-%d")
-            start = (datetime.utcnow().replace(year=datetime.utcnow().year-2)).strftime("%Y-%m-%d")
-            ndvi_ts = safe_time_series(roi, ndvi_col, "NDVI", start, end)
-
-        # Save results
-        active = st.session_state.get("active_site", 0)
-        if "sites" in st.session_state:
-            site = st.session_state["sites"][active]
-            site["ROI"] = roi.getInfo()
-            site["Soil Profile"] = f"{soil_val} ({chosen_soil_band})" if soil_val else "N/A"
-            site["Topo Data"] = f"{elev_val} m" if elev_val else "N/A"
-            site["Seismic Data"] = seismic_val
-            site["Flood Data"] = flood_val
-            site["Environmental Data"] = {"Landcover": lc_stats, "NDVI": ndvi_ts}
-        st.session_state["soil_json"] = {
-            "Soil": soil_val, "Soil Band": chosen_soil_band,
-            "Elevation": elev_val, "Seismic": seismic_val,
-            "Flood": flood_val, "Landcover Stats": lc_stats,
-            "NDVI TS": ndvi_ts
-        }
-        # --- Save map snapshot ---
-        map_bytes = export_map_snapshot(m)
-        if map_bytes:
-            st.session_state["last_map_snapshot"] = map_bytes
+            st.success("ROI ready — computing...")
+
+            soil_val = safe_get_reduce(roi, soil_img.select(chosen_soil_band), chosen_soil_band, 1000) if soil_img and chosen_soil_band else None
+            elev_val = safe_get_reduce(roi, dem, dem_band_name, 1000) if dem else None
+            seismic_val = safe_get_reduce(roi, seismic_img, seismic_band, 5000) if seismic_img else None
+            flood_val = safe_get_reduce(roi, water.select(water_band), water_band, 30) if water else None
+            lc_stats = safe_reduce_histogram(roi, landcover, lc_band, 30) if landcover else {}
+            ndvi_ts = []
+            if ndvi_col:
+                end = datetime.utcnow().strftime("%Y-%m-%d")
+                start = (datetime.utcnow().replace(year=datetime.utcnow().year-2)).strftime("%Y-%m-%d")
+                ndvi_ts = safe_time_series(roi, ndvi_col, "NDVI", start, end)
+
+            # Save results
+            active = st.session_state.get("active_site", 0)
             if "sites" in st.session_state:
-                st.session_state["sites"][active]["map_snapshot"] = map_bytes
-            st.image(map_bytes, caption="Map Snapshot", use_column_width=True)
-
-        # Display
-        st.subheader("📊 Summary")
-        st.write(f"**Soil:** {soil_val}")
-        st.write(f"**Elevation:** {elev_val}")
-        st.write(f"**Seismic:** {seismic_val}")
-        st.write(f"**Flood:** {flood_val}")
-        st.json(lc_stats)
-        if ndvi_ts:
-            d,v = zip(*ndvi_ts)
-            fig, ax = plt.subplots()
-            ax.plot(d, v, marker="o"); ax.set_title("NDVI"); ax.set_xlabel("Date")
-            st.pyplot(fig)
+                site = st.session_state["sites"][active]
+                if roi:
+                    try:
+                        site["ROI"] = roi.getInfo()
+                    except Exception:
+                        site["ROI"] = "Not available"
+                site["Soil Profile"] = f"{soil_val} ({chosen_soil_band})" if soil_val else "N/A"
+                site["Topo Data"] = f"{elev_val} m" if elev_val else "N/A"
+                site["Seismic Data"] = seismic_val if seismic_val else "N/A"
+                site["Flood Data"] = flood_val if flood_val else "N/A"
+                site["Environmental Data"] = {"Landcover": lc_stats, "NDVI": ndvi_ts}
+
+            st.session_state["soil_json"] = {
+                "Soil": soil_val, "Soil Band": chosen_soil_band,
+                "Elevation": elev_val, "Seismic": seismic_val,
+                "Flood": flood_val, "Landcover Stats": lc_stats,
+                "NDVI TS": ndvi_ts
+            }
+
+            # Map snapshot
+            map_bytes = export_map_snapshot(m)
+            if map_bytes:
+                st.session_state["last_map_snapshot"] = map_bytes
+                if "sites" in st.session_state:
+                    st.session_state["sites"][active]["map_snapshot"] = map_bytes
+                st.image(map_bytes, caption="Map Snapshot", use_column_width=True)
+
+            # Display
+            st.subheader("📊 Summary")
+            st.write(f"**Soil:** {soil_val}")
+            st.write(f"**Elevation:** {elev_val}")
+            st.write(f"**Seismic:** {seismic_val}")
+            st.write(f"**Flood:** {flood_val}")
+            st.json(lc_stats)
+            if ndvi_ts:
+                d, v = zip(*ndvi_ts)
+                fig, ax = plt.subplots()
+                ax.plot(d, v, marker="o"); ax.set_title("NDVI"); ax.set_xlabel("Date")
+                st.pyplot(fig)
 
 # GeoMate Ask (RAG) — simple chat with memory per site and auto-extract numeric values
 import re, json, pickle