update app.py

app.py

@@ -8,9 +8,10 @@ import pandas as pd
 import geopandas as gpd
 from shapely.geometry import Point
 
+# Set the page layout
 st.set_page_config(layout="wide")
 
-# Custom styling for the button
+# Custom button styling
 m = st.markdown(
     """
     <style>
@@ -25,7 +26,7 @@ m = st.markdown(
 # Authenticate and initialize Earth Engine
 earthengine_credentials = os.environ.get("EE_Authentication")
 
-# Initialize Earth Engine with the secret credentials
+# Initialize Earth Engine with secret credentials
 os.makedirs(os.path.expanduser("~/.config/earthengine/"), exist_ok=True)
 with open(os.path.expanduser("~/.config/earthengine/credentials"), "w") as f:
     f.write(earthengine_credentials)
@@ -36,13 +37,12 @@ ee.Initialize(project='ee-yashsacisro24')
 with open("sentinel_datasets.json") as f:
     data = json.load(f)
 
-# Display title and dataset selection
+# Display the title and dataset selection
 st.title("Sentinel Dataset and Index Calculator")
 
-# Step 1: Select main dataset category
+# Select dataset category and subcategory
 main_selection = st.selectbox("Select Sentinel Dataset Category", list(data.keys()))
 
-# Step 2: Display sub-options based on main selection
 if main_selection:
     sub_options = data[main_selection]["sub_options"]
     sub_selection = st.selectbox("Select Specific Dataset ID", list(sub_options.keys()))
@@ -50,93 +50,88 @@ if main_selection:
 # Earth Engine Index Calculator Section
 st.header("Earth Engine Index Calculator")
 
-# Step 3: Choose Index or Custom Formula
+# Choose Index or Custom Formula
 index_choice = st.selectbox("Select an Index or Enter Custom Formula", ['NDVI', 'NDWI', 'Average NO₂', 'Custom Formula'])
 
-# Step 4: Enter Custom Formula if selected
+# Enter custom formula if selected
 custom_formula = ""
 if index_choice == 'Custom Formula':
     custom_formula = st.text_input("Enter Custom Formula (e.g., 'B5 - B4 / B5 + B4')")
 
-# Step 5: Select Geometry Type (Point or Polygon)
+# Select Geometry Type (Point or Polygon)
 geometry_type = st.selectbox("Select Geometry Type", ['Point', 'Polygon'])
 
-# Step 6: File Upload Based on Geometry Type
+# File uploader for Point or Polygon geometry
 if geometry_type == 'Point':
     uploaded_file = st.file_uploader("Upload a CSV, GeoJSON, or KML file with Point Data", type=["csv", "geojson", "kml"])
 else:
     uploaded_file = st.file_uploader("Upload a GeoJSON or KML file with Polygon Data", type=["geojson", "kml"])
 
-# Function to get geometry points from uploaded file
+# Function to get user points from CSV, GeoJSON, or KML file
 def get_user_points(uploaded_file):
     points = []
     if uploaded_file.name.endswith('.csv'):
-        # Read CSV file
         df = pd.read_csv(uploaded_file)
         for _, row in df.iterrows():
             lat = row['latitude']
             lon = row['longitude']
             # Check for NaN values
             if pd.isna(lat) or pd.isna(lon):
-                continue  # Skip this point if latitude or longitude is NaN
-            name = row.get('name', f"Location {len(points) + 1}")  # Default name if not provided
+                continue
+            name = row.get('name', f"Location {len(points) + 1}")
             points.append({"geometry": ee.Geometry.Point([lon, lat]), "name": name})
-    
+
     elif uploaded_file.name.endswith('.geojson'):
-        # Read GeoJSON file
         geojson_data = json.load(uploaded_file)
         for feature in geojson_data['features']:
             lat, lon = feature['geometry']['coordinates']
             # Check for NaN values
             if lat is None or lon is None:
-                continue  # Skip this point if latitude or longitude is NaN
+                continue
             name = feature.get('properties', {}).get('Name', f"Location {len(points) + 1}")
             points.append({"geometry": ee.Geometry.Point([lon, lat]), "name": name})
-    
+
     elif uploaded_file.name.endswith('.kml'):
-        # Read KML file
         gdf = gpd.read_file(uploaded_file)
         for _, row in gdf.iterrows():
             lat = row.geometry.y
             lon = row.geometry.x
             # Check for NaN values
             if pd.isna(lat) or pd.isna(lon):
-                continue  # Skip this point if latitude or longitude is NaN
+                continue
             name = row.get('name', f"Location {len(points) + 1}")
             points.append({"geometry": ee.Geometry.Point([lon, lat]), "name": name})
-    
+
     return points
 
-# Function to get geometry polygons from uploaded file
+# Function to get user polygons from GeoJSON or KML file
 def get_user_polygons(uploaded_file):
     polygons = []
     if uploaded_file.name.endswith('.geojson'):
-        # Read GeoJSON file
         geojson_data = json.load(uploaded_file)
         for feature in geojson_data['features']:
             if feature['geometry']['type'] in ['Polygon', 'MultiPolygon']:
                 geom = ee.Geometry(feature['geometry'])
                 name = feature.get('properties', {}).get('Name', f"Polygon {len(polygons) + 1}")
                 polygons.append({"geometry": geom, "name": name})
-    
+
     elif uploaded_file.name.endswith('.kml'):
-        # Read KML file
         gdf = gpd.read_file(uploaded_file)
         for _, row in gdf.iterrows():
             geom = row.geometry
             if geom.geom_type in ['Polygon', 'MultiPolygon']:
                 name = row.get('name', f"Polygon {len(polygons) + 1}")
                 polygons.append({"geometry": ee.Geometry(geom), "name": name})
-    
+
     return polygons
 
-# Step 7: Parse the file and get geometries (points or polygons)
+# Parse the file and get geometries (points or polygons)
 if uploaded_file is not None:
     if geometry_type == 'Point':
         points = get_user_points(uploaded_file)
         if points:
             st.write(f"Loaded {len(points)} points.")
-            points_df = pd.DataFrame([{'Latitude': point['geometry'].coordinates().get(0), 
+            points_df = pd.DataFrame([{'Latitude': point['geometry'].coordinates().get(0),
                                        'Longitude': point['geometry'].coordinates().get(1),
                                        'Name': point['name']} for point in points])
             st.write("Points from file:", points_df)
@@ -154,17 +149,7 @@ if uploaded_file is not None:
 else:
     geometries = []
 
-# Visualization for Points
-if len(geometries) > 0 and geometry_type == 'Point':
-    # Show points on map using geemap
-    Map = geemap.Map()
-    Map.setCenter(-100.0, 40.0, 4)  # Adjusted for example
-    for point in points:
-        Map.add_marker(location=[point['geometry'].coordinates().get(1), point['geometry'].coordinates().get(0)],
-                       popup=point['name'])
-    Map.to_streamlit(height=600)
-
-# Define functions for index calculations
+# Function for index calculation
 def calculate_ndvi(image, geometry):
     return image.normalizedDifference(['B5', 'B4']).rename('NDVI').reduceRegion(
         reducer=ee.Reducer.mean(),
@@ -193,7 +178,7 @@ def calculate_custom_formula(image, geometry, formula):
         scale=30
     )
 
-# Step 8: Perform the calculation based on user choice
+# Step: Perform the calculation based on user choice
 if st.button("Calculate Index"):
     if geometries:
         try: