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IMAN_GEE.json

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+{
+  "type": "service_account",
+  "project_id": "ee-imanebakhshipoor",
+  "private_key_id": "3427cebd25c3557f7c2d92b7ebea71efc0990385",
+  "private_key": "-----BEGIN PRIVATE KEY-----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\nsqhqS6UDKNaiDesbs482yg==\n-----END PRIVATE KEY-----\n",
+  "client_email": "[email protected]",
+  "client_id": "105704822098506259560",
+  "auth_uri": "https://accounts.google.com/o/oauth2/auth",
+  "token_uri": "https://oauth2.googleapis.com/token",
+  "auth_provider_x509_cert_url": "https://www.googleapis.com/oauth2/v1/certs",
+  "client_x509_cert_url": "https://www.googleapis.com/robot/v1/metadata/x509/iman-gee2%40ee-imanebakhshipoor.iam.gserviceaccount.com",
+  "universe_domain": "googleapis.com"
+}

app.py

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+import streamlit as st
+import geopandas as gpd
+import ee
+import json
+import os
+import tempfile
+import geemap.foliumap as geemap
+from io import BytesIO
+from datetime import datetime
+from io import StringIO
+from PIL import Image
+from google.oauth2 import service_account
+
+import streamlit as st
+from PIL import Image
+
+# بارگذاری تصویر
+image = Image.open("ABK.jpg")  # مسیر تصویر محلی خود را وارد کنید
+
+# streamlisاستفاده از Sidebar برای نمایش تصویر در بالای آن
+with st.sidebar:
+    st.image(image, use_container_width=True)
+    st.markdown('<h2 style="color: green;">شرکت مهندسین مشاور آسمان برج کارون</h2>', unsafe_allow_html=True)
+
+# مقداردهی اولیه GEE
+
+# # مقداردهی اولیه GEE
+service_account = "[email protected]"
+credentials = ee.ServiceAccountCredentials(service_account, "IMAN_GEE.json")
+ee.Initialize(credentials)
+
+# آپلود فایل ZIP شامل Shapefile
+uploaded_file = st.file_uploader("آپلود یک شیپ فایل فشرده ‌شده (.zip)", type=["zip"])
+
+# استفاده از Sidebar برای انتخاب تاریخ و مقیاس
+with st.sidebar:
+    start_date = st.date_input("تاریخ شروع", value=datetime(2025, 1, 1), min_value=datetime(2000, 1, 1),
+                               max_value=datetime.today())
+    end_date = st.date_input("تاریخ پایان", value=datetime(2025, 2, 15), min_value=datetime(2000, 1, 1),
+                             max_value=datetime.today())
+    scale = st.number_input("مقیاس (Scale)", min_value=10, max_value=100, value=10, step=10)
+
+if uploaded_file:
+    try:
+        gdf = gpd.read_file(BytesIO(uploaded_file.getvalue()))
+        if gdf.crs is not None and gdf.crs.to_epsg() != 4326:
+            gdf = gdf.to_crs(epsg=4326)
+        st.write("CRS Shapefile (converted):", gdf.crs)
+        st.write(" Shapefile:", gdf.geometry)
+
+        geojson = json.loads(gdf.to_json())
+        features = [ee.Feature(feature) for feature in geojson["features"]]
+        region = ee.FeatureCollection(features)
+
+        start_date_ee = ee.Date.fromYMD(start_date.year, start_date.month, start_date.day)
+        end_date_ee = ee.Date.fromYMD(end_date.year, end_date.month, end_date.day)
+
+        image = ee.ImageCollection("COPERNICUS/S2_SR_HARMONIZED") \
+            .filterBounds(region) \
+            .filterDate(start_date_ee, end_date_ee).median() \
+            .clip(region)
+
+        if image is None:
+            st.error("هیچ تصویری از Sentinel-2 برای این منطقه و بازه زمانی یافت نشد.")
+        else:
+            ndvi = image.normalizedDifference(["B8", "B4"]).rename("NDVI")
+            savi = image.expression(
+                "((B8 - B4) / (B8 + B4 + 0.5)) * (1.5)",
+                {
+                    'B8': image.select('B8'),
+                    'B4': image.select('B4')
+                }
+            ).rename("SAVI")
+            mndwi = image.normalizedDifference(["B3", "B11"]).rename("MNDWI")
+            gcvi = image.expression("B8 / B3 - 1", {
+                'B8': image.select('B8'),
+                'B3': image.select('B3')
+            }).rename("GCVI")
+
+            composite = ndvi.addBands([savi, mndwi, gcvi])
+
+            Map = geemap.Map(center=[gdf.geometry.centroid.y.mean(), gdf.geometry.centroid.x.mean()], zoom=8)
+            Map.add_basemap("OpenStreetMap")
+            Map.add_basemap("HYBRID")
+            Map.addLayer(ndvi, {'min': 0, 'max': 1, 'palette': ['white', 'green']}, "Crop Detect", False)
+            # Map.addLayer(savi, {'min': 0, 'max': 1, 'palette': ['white', 'yellow', 'green']}, "SAVI", False)
+            Map.addLayer(mndwi, {'min': -1, 'max': 1, 'palette': ['red', 'blue']}, "Water Body", False)
+            # Map.addLayer(gcvi, {'palette': ['#ffffff', '#ffff00', '#008000'], 'min': 0.347, 'max': 3.704}, "GCVI",
+            #              False)
+            Map.addLayer(image, {'min': 0, 'max': 3000, 'bands': ["B4", "B3", "B2"]}, "True Color", True)
+            Map.addLayer(region, {}, " Shapefile")
+
+            Map.to_streamlit(height=600)
+
+
+            def download_image(image, filename):
+                with st.spinner(f"در حال تولید {filename}... ⏳"):
+                    temp_dir = tempfile.gettempdir()
+                    temp_path = os.path.join(temp_dir, filename)
+                    geemap.ee_export_image(image, filename=temp_path, scale=scale, region=region.geometry().bounds())
+                    with open(temp_path, "rb") as f:
+                        st.download_button(label=f"download  {filename}", data=f, file_name=filename, mime="image/tiff")
+
+
+            st.subheader("download image")
+            download_image(ndvi, "Crop Detect.tif")
+            # download_image(savi, "savi_image.tif")
+            download_image(mndwi, "Water Body.tif")
+            # download_image(gcvi, "gcvi_image.tif")
+    except Exception as e:
+        st.error(f"خطا در پردازش Shapefile یا محاسبه شاخص‌ها: {str(e)}")
+
+
+
+

requirements.txt

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+streamlit
+geopandas
+earthengine-api
+geemap
+numpy
+pandas
+setuptools