Update app.py

app.py

@@ -1,177 +1,125 @@
 import streamlit as st
 import ee
-import geemap
+import geemap.foliumap as geemap
 import pandas as pd
-from datetime import datetime, timedelta
+import datetime
 import matplotlib.pyplot as plt
-import folium
+import geopandas as gpd
+import zipfile
 import os
+import requests
 
-# Constants
-NDRE_HARVEST_THRESHOLD = 0.3
-NDMI_HARVEST_THRESHOLD = 0.4
-CSV_URL = "https://huggingface.co/spaces/Esmaeilkiani/AppSugarcane/resolve/main/Farm_Details_Export.csv"
-PRIVATE_KEY_PATH = os.environ.get("ee-esmaeilkiani1387-1b2c5e812a1d.json")
-
-# Page configuration
-st.set_page_config(page_title="Sugarcane Field Monitoring", layout="wide")
-
-# GEE Authentication
-def authenticate_gee():
-    try:
-        credentials = ee.ServiceAccountCredentials(None, PRIVATE_KEY_PATH)
-        ee.Initialize(credentials)
-        return True
-    except Exception as e:
-        st.error(f"Failed to authenticate with Google Earth Engine: {str(e)}")
-        return False
-
-# Load farm data
-@st.cache_data
-def load_farm_data():
-    try:
-        df = pd.read_csv(CSV_URL)
-        if not all(col in df.columns for col in ["farm_name", "latitude", "longitude"]):
-            raise ValueError("CSV file is missing required columns")
-        return df
-    except Exception as e:
-        st.error(f"Error loading farm data: {str(e)}")
-        return None
-
-# Get indices data from GEE
-def get_indices_data(farm_coords, start_date, end_date):
-    point = ee.Geometry.Point(farm_coords)
-    s2 = ee.ImageCollection("COPERNICUS/S2_SR")
-    
-    filtered = s2.filterBounds(point).filterDate(start_date, end_date)
-    
-    def add_indices(image):
-        ndre = image.normalizedDifference(['B8', 'B5']).rename('NDRE')
-        ndmi = image.normalizedDifference(['B8A', 'B11']).rename('NDMI')
-        return image.addBands([ndre, ndmi])
-    
-    with_indices = filtered.map(add_indices)
-    
-    time_series = with_indices.select(['NDRE', 'NDMI']).getRegion(point, 500)
-    
-    return time_series
-
-# Extract index data from GEE results
-def extract_index_data(data, index_name):
-    try:
-        dates = [datetime.utcfromtimestamp(d[3] / 1000) for d in data[1:]]
-        values = [float(d[4]) if d[4] is not None else None for d in data[1:]]
-        return pd.DataFrame({
-            'date': dates,
-            index_name: values
-        }).dropna().set_index('date')
-    except Exception as e:
-        st.error(f"Error extracting {index_name} data: {str(e)}")
-        return pd.DataFrame()
-
-# Main application
-def main():
-    if not authenticate_gee():
-        return
-
-    st.title("Sugarcane Field Monitoring")
-
-    farm_data = load_farm_data()
-    if farm_data is None:
-        return
-
-    # Sidebar
-    st.sidebar.header("Settings")
-    farm_name = st.sidebar.selectbox("Select Farm", farm_data['farm_name'].tolist())
-    start_date = st.sidebar.date_input("Start Date", datetime.now() - timedelta(days=30))
-    end_date = st.sidebar.date_input("End Date", datetime.now())
+# اعتبار سنجی و اتصال به Google Earth Engine
+service_account = 'earth-engine-service-account@ee-esmaeilkiani1387.iam.gserviceaccount.com'
+credentials = ee.ServiceAccountCredentials(service_account, 'ee-esmaeilkiani1387-1b2c5e812a1d.json')
+ee.Initialize(credentials)
+
+# خواندن فایل CSV مزارع
+farms_data = pd.read_csv('Farm_Details_Export.csv')
+
+# تعریف ناحیه مورد مطالعه با مختصات جدید
+region = ee.Geometry.Polygon(
+    [[[48.681879, 31.417603], [48.721447, 31.413209], [48.724279, 31.420826], [48.726768, 31.427418],
+      [48.728228, 31.435694], [48.736382, 31.42837], [48.739557, 31.435657], [48.742261, 31.441772],
+      [48.752303, 31.452243], [48.75226, 31.459784], [48.759127, 31.473657], [48.766809, 31.472413],
+      [48.773203, 31.491188], [48.77758, 31.534579], [48.785563, 31.540797], [48.792601, 31.59696],
+      [48.694668, 31.60756], [48.691921, 31.603466], [48.697586, 31.534067], [48.69381, 31.507727],
+      [48.685226, 31.468496], [48.681879, 31.417603]]]
+)
+
+# تابع برای دانلود و استخراج شیپ‌فایل
+def download_and_extract_shapefile(zip_url, extract_to='.'):
+    zip_path = os.path.join(extract_to, 'shapefile.zip')
     
-    if end_date > datetime.now().date():
-        st.sidebar.error("End date cannot be in the future.")
-        return
+    # دانلود فایل زیپ
+    with requests.get(zip_url, stream=True) as r:
+        r.raise_for_status()
+        with open(zip_path, 'wb') as f:
+            for chunk in r.iter_content(chunk_size=8192):
+                f.write(chunk)
     
-    indices = st.sidebar.multiselect("Select Indices", ["NDRE", "NDMI"], default=["NDRE", "NDMI"])
+    # استخراج فایل زیپ
+    with zipfile.ZipFile(zip_path, 'r') as zip_ref:
+        zip_ref.extractall(extract_to)
+
+    # یافتن فایل .shp
+    for file in os.listdir(extract_to):
+        if file.endswith('.shp'):
+            return os.path.join(extract_to, file)
+
+    return None
+
+# تابع برای خواندن و نمایش شیپ‌فایل
+def load_and_display_shapefile(shapefile_path):
+    gdf = gpd.read_file(shapefile_path)
+    geojson = gdf.to_json()
     
-    if st.sidebar.button("Submit"):
-        farm_row = farm_data[farm_data['farm_name'] == farm_name].iloc[0]
-        farm_coords = [farm_row['longitude'], farm_row['latitude']]
-        
-        with st.spinner("Fetching data..."):
-            gee_data = get_indices_data(farm_coords, start_date, end_date)
-            
-            if gee_data:
-                ndre_data = extract_index_data(gee_data.getInfo(), "NDRE")
-                ndmi_data = extract_index_data(gee_data.getInfo(), "NDMI")
-                
-                # Plotting
-                fig, ax = plt.subplots(figsize=(12, 6))
-                
-                if "NDRE" in indices and not ndre_data.empty:
-                    ax.plot(ndre_data.index, ndre_data["NDRE"], label="NDRE")
-                    ax.axhline(y=NDRE_HARVEST_THRESHOLD, color='r', linestyle='--', label="NDRE Harvest Threshold")
-                
-                if "NDMI" in indices and not ndmi_data.empty:
-                    ax.plot(ndmi_data.index, ndmi_data["NDMI"], label="NDMI")
-                    ax.axhline(y=NDMI_HARVEST_THRESHOLD, color='g', linestyle='--', label="NDMI Harvest Threshold")
-                
-                ax.set_xlabel("Date")
-                ax.set_ylabel("Index Value")
-                ax.set_title(f"Time Series for {farm_name}")
-                ax.legend()
-                
-                st.pyplot(fig)
-                
-                # Harvest Analysis
-                if "NDRE" in indices and not ndre_data.empty:
-                    if ndre_data["NDRE"].iloc[-1] > NDRE_HARVEST_THRESHOLD:
-                        st.success("NDRE indicates the field may be ready for harvest.")
-                    else:
-                        st.info("NDRE suggests the field is not yet ready for harvest.")
-                
-                if "NDMI" in indices and not ndmi_data.empty:
-                    if ndmi_data["NDMI"].iloc[-1] > NDMI_HARVEST_THRESHOLD:
-                        st.success("NDMI indicates good moisture content for harvest.")
-                    else:
-                        st.info("NDMI suggests suboptimal moisture content for harvest.")
-                
-                # Map
-                m = geemap.Map(center=farm_coords, zoom=12)
-                m.add_basemap("OpenStreetMap")
-                
-                if "NDRE" in indices:
-                    ndre_layer = geemap.ee_tile_layer(
-                        with_indices.select('NDRE').mean(),
-                        {'min': 0, 'max': 1, 'palette': ['red', 'yellow', 'green']},
-                        'NDRE'
-                    )
-                    m.add_layer(ndre_layer)
-                
-                if "NDMI" in indices:
-                    ndmi_layer = geemap.ee_tile_layer(
-                        with_indices.select('NDMI').mean(),
-                        {'min': -1, 'max': 1, 'palette': ['red', 'white', 'blue']},
-                        'NDMI'
-                    )
-                    m.add_layer(ndmi_layer)
-                
-                marker = folium.Marker(
-                    location=farm_coords[::-1],
-                    popup=f"Farm: {farm_name}<br>Lat: {farm_coords[1]}<br>Lon: {farm_coords[0]}"
-                )
-                marker.add_to(m)
-                
-                m.to_streamlit(height=600)
-                
-                # Map Download
-                map_html = m.to_html()
-                st.download_button(
-                    label="Download Map",
-                    data=map_html,
-                    file_name="sugarcane_field_map.html",
-                    mime="text/html"
-                )
-            else:
-                st.error("Failed to retrieve data from Google Earth Engine.")
-
-if __name__ == "__main__":
-    main()
+    map_ = geemap.Map(center=[31.5, 48.7], zoom=10)
+    map_.add_geojson(geojson, layer_name="Shapefile Layer")
+    map_.to_streamlit(height=600)
+
+# آدرس شیپ‌فایل آپلود شده در هاگینگ فیس (لینک مستقیم فایل زیپ)
+zip_url = 'https://huggingface.co/spaces/Esmaeilkiani/AppSugarcane/raw/main/Dehkhodaa.rar'
+
+# دانلود و نمایش شیپ‌فایل
+shapefile_path = download_and_extract_shapefile(zip_url)
+if shapefile_path:
+    st.write("شیپ‌فایل با موفقیت بارگذاری شد!")
+    load_and_display_shapefile(shapefile_path)
+else:
+    st.write("خطا در بارگذاری شیپ‌فایل.")
+
+# انتخاب بازه زمانی با کلیدهای یکتا
+start_date = st.date_input("تاریخ شروع", datetime.date(2023, 1, 1), key="start_date")
+end_date = st.date_input("تاریخ پایان", datetime.date(2023, 12, 31), key="end_date")
+
+# انتخاب شاخص
+index_option = st.selectbox("شاخص مورد نظر را انتخاب کنید:", ["NDVI", "NDMI", "NDRE"])
+
+# انتخاب مزرعه از فایل CSV
+farm_name = st.sidebar.selectbox("نام مزرعه را انتخاب کنید:", farms_data['farm_name'].unique())
+
+# پیدا کردن مختصات مزرعه انتخاب شده
+selected_farm = farms_data[farms_data['farm_name'] == farm_name]
+latitude = selected_farm['latitude'].values[0]
+longitude = selected_farm['longitude'].values[0]
+farm_age = selected_farm['age'].values[0]
+farm_variety = selected_farm['variety'].values[0]
+
+# دکمه برای نمایش نقشه
+if st.button("نمایش نقشه"):
+    if index_option == "NDVI":
+        index_map, vis_params = get_ndvi_map(start_date.isoformat(), end_date.isoformat())
+    elif index_option == "NDMI":
+        index_map, vis_params = get_ndmi_map(start_date.isoformat(), end_date.isoformat())
+    else:
+        index_map, vis_params = get_ndre_map(start_date.isoformat(), end_date.isoformat())
+
+    # ایجاد نقشه با Geemap
+    map_ = geemap.Map(center=[latitude, longitude], zoom=14)
+    map_.addLayer(index_map.clip(region), vis_params, index_option)
+    map_.add_colorbar(vis_params, label=index_option)
+
+    # افزودن مزرعه به نقشه
+    map_.add_marker([latitude, longitude], popup=f"نام: {farm_name}<br>سن: {farm_age}<br>واریته: {farm_variety}")
+    map_.add_ee_layer(region, {'color': 'FF0000'}, 'منطقه مورد مطالعه')
+
+    # نمایش نقشه در Streamlit
+    map_.to_streamlit(height=600)
+
+    # محاسبه NDRE میانگین
+    ndre_image = get_ndre_map(start_date.isoformat(), end_date.isoformat())[0]
+    mean_ndre = ndre_image.reduceRegion(reducer=ee.Reducer.mean(), geometry=region, scale=30).get('NDRE').getInfo()
+
+    # نمودار تصمیم‌گیری برای برداشت
+    fig, ax = plt.subplots()
+    ax.bar(['NDRE', 'مناسب برای برداشت'], [mean_ndre, 0.5], color=['green', 'orange'])
+    ax.set_ylim(0, 1)
+    ax.set_title(f"شاخص NDRE برای مزرعه {farm_name}")
+    st.pyplot(fig)
+
+    # نمایش وضعیت برداشت
+    if mean_ndre > 0.5:
+        st.write(f"مزرعه {farm_name} به حد قابل قبول برای برداشت رسیده است (NDRE = {mean_ndre:.2f}).")
+    else:
+        st.write(f"مزرعه {farm_name} هنوز آماده برداشت نیست (NDRE = {mean_ndre:.2f}).")