Update app.py

app.py

@@ -1924,25 +1924,24 @@ def GlobalSurfaceWater_page():
 
 #-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
 def GlobalSurfaceWater():
+
     with st.expander("How to use this app"):
-        st.markdown("""
+
+        markdown = """
         This interactive app allows you to explore and compare different datasets of Global Surface Water Extent (GSWE). How to use this web app?    
         - **Step 1:** Select a basemap from the dropdown menu on the right. The default basemap is `HYBRID`, a Google Satellite basemap with labels.   
         - **Step 2:** Select a region of interest (ROI) from the country dropdown menu or upload an ROI. The default ROI is the entire globe. 
         - **Step 3:** Select surface water datasets from the dropdown menu. You can select multiple datasets to display on the map.
-        """)
+        """
+        st.markdown(markdown)
 
     col1, col2 = st.columns([3, 1])
-    
-    # Initialize a Folium map
-    map_instance = folium.Map(location=[25.5973518, 65.54495724], zoom_start=7)
-
-    # Initialize the Draw plugin
-    draw = Draw(export=True)
-    draw.add_to(map_instance)
 
+    Map = geemap.Map(Draw_export=False, locate_control=True, plugin_LatLngPopup=True)
+    
     roi = ee.FeatureCollection("users/giswqs/public/countries")
-    countries = sorted(roi.aggregate_array("name").getInfo())
+    # countries = roi.aggregate_array("name").getInfo()
+    # countries.sort()
     countries = ["United States of America"]
 
     lc_basemaps = [
@@ -1957,89 +1956,353 @@ def GlobalSurfaceWater():
         "Google " + b for b in list(geemap.basemaps.keys())[1:5]
     ]
     basemaps = google_basemaps + lc_basemaps
-
     with col2:
+
         latitude = st.number_input("Map center latitude", -90.0, 90.0, 40.0, step=0.5)
-        longitude = st.number_input("Map center longitude", -180.0, 180.0, -100.0, step=0.5)
+        longitude = st.number_input(
+            "Map center longitude", -180.0, 180.0, -100.0, step=0.5
+        )
         zoom = st.slider("Map zoom level", 1, 22, 4)
 
-        select_country = st.checkbox("Select a country")
-        if select_country:
-            country = st.selectbox("Select a country from dropdown list", countries)
+        select = st.checkbox("Select a country")
+        if select:
+            country = st.selectbox(
+                "Select a country from dropdown list",
+                countries,
+                index=countries.index("United States of America"),
+            )
             st.session_state["ROI"] = roi.filter(ee.Filter.eq("name", country))
         else:
+
             with st.expander("Click here to upload an ROI", False):
-                upload = st.file_uploader("Upload a GeoJSON, KML or Shapefile (as a zip file) to use as an ROI. 😇👇", type=["geojson", "kml", "zip"])
+                upload = st.file_uploader(
+                    "Upload a GeoJSON, KML or Shapefile (as a zif file) to use as an ROI. 😇👇",
+                    type=["geojson", "kml", "zip"],
+                )
+
                 if upload:
-                    with tempfile.NamedTemporaryFile(delete=False) as tmp:
-                        tmp.write(upload.read())
-                        tmp.seek(0)  # Reset file pointer
-                        gdf = gpd.read_file(tmp.name)
-                        st.session_state["ROI"] = geemap.gdf_to_ee(gdf, geodesic=False)
+                    gdf = uploaded_file_to_gdf(upload)
+                    st.session_state["ROI"] = geemap.gdf_to_ee(gdf, geodesic=False)
+                    # Map.add_gdf(gdf, "ROI")
                 else:
                     st.session_state["ROI"] = roi
 
-        basemap = st.selectbox("Select a basemap", basemaps, index=basemaps.index("Google HYBRID"))
-
-    if basemap in google_basemaps:
-        geemap.add_basemap(map_instance, basemap.replace("Google ", ""))
-    elif basemap in lc_basemaps:
-        if basemap == "ESA Global Land Cover 2020":
-            dataset = ee.ImageCollection("ESA/WorldCover/v100").first()
-        elif basemap == "ESRI Global Land Cover 2020":
-            dataset = ee.ImageCollection("projects/sat-io/open-datasets/landcover/ESRI_Global-LULC_10m").mosaic()
-        elif basemap == "US NLCD 2019":
-            dataset = ee.Image("USGS/NLCD_RELEASES/2019_REL/NLCD/2019").select("landcover")
-        elif basemap == "USDA NASS Cropland 2020":
-            dataset = ee.ImageCollection("USDA/NASS/CDL").filterDate("2010-01-01", "2020-01-01").first().select("cropland")
-        
-        if st.session_state["ROI"] is not None:
-            dataset = dataset.clipToCollection(st.session_state["ROI"])
-        
-        geemap.add_ee_layer(map_instance, dataset, {}, basemap)
-    
-    # Manage dataset selection
-    datasets = st.multiselect("Select surface water datasets", [
-        "ESA Land Use",
-        "JRC Max Water Extent",
-        "OpenStreetMap",
-        "HydroLakes",
-        "LAGOS",
-        "US NED Depressions",
-        "Global River Width",
-    ])
-
-    # Styles dictionary for datasets
+        basemap = st.selectbox(
+            "Select a basemap",
+            basemaps,
+            index=basemaps.index("Google HYBRID"),
+        )
+        if basemap in google_basemaps:
+            Map.add_basemap(basemap.replace("Google ", ""))
+        elif basemap in lc_basemaps:
+
+            if basemap == "ESA Global Land Cover 2020":
+                dataset = ee.ImageCollection("ESA/WorldCover/v100").first()
+                if st.session_state["ROI"] is not None:
+                    dataset = dataset.clipToCollection(st.session_state["ROI"])
+
+                Map.addLayer(dataset, {}, "ESA Landcover")
+                Map.add_legend(title="ESA Landcover", builtin_legend="ESA_WorldCover")
+            elif basemap == "ESRI Global Land Cover 2020":
+
+                esri_lulc10 = ee.ImageCollection(
+                    "projects/sat-io/open-datasets/landcover/ESRI_Global-LULC_10m"
+                )
+                legend_dict = {
+                    "names": [
+                        "Water",
+                        "Trees",
+                        "Grass",
+                        "Flooded Vegetation",
+                        "Crops",
+                        "Scrub/Shrub",
+                        "Built Area",
+                        "Bare Ground",
+                        "Snow/Ice",
+                        "Clouds",
+                    ],
+                    "colors": [
+                        "#1A5BAB",
+                        "#358221",
+                        "#A7D282",
+                        "#87D19E",
+                        "#FFDB5C",
+                        "#EECFA8",
+                        "#ED022A",
+                        "#EDE9E4",
+                        "#F2FAFF",
+                        "#C8C8C8",
+                    ],
+                }
+
+                vis_params = {"min": 1, "max": 10, "palette": legend_dict["colors"]}
+                esri_lulc10 = esri_lulc10.mosaic()
+
+                if st.session_state["ROI"] is not None:
+                    esri_lulc10 = esri_lulc10.clipToCollection(st.session_state["ROI"])
+                Map.addLayer(esri_lulc10, vis_params, "ESRI Global Land Cover")
+                Map.add_legend(title="ESRI Landcover", builtin_legend="ESRI_LandCover")
+
+            elif basemap == "US NLCD 2019":
+                nlcd = ee.Image("USGS/NLCD_RELEASES/2019_REL/NLCD/2019").select(
+                    "landcover"
+                )
+                if st.session_state["ROI"] is not None:
+                    nlcd = nlcd.clipToCollection(st.session_state["ROI"])
+                Map.addLayer(nlcd, {}, "US NLCD 2019")
+                Map.add_legend(title="NLCD Land Cover", builtin_legend="NLCD")
+
+            elif basemap == "USDA NASS Cropland 2020":
+                cropland = (
+                    ee.ImageCollection("USDA/NASS/CDL")
+                    .filterDate("2010-01-01", "2020-01-01")
+                    .first()
+                    .select("cropland")
+                )
+
+                if st.session_state["ROI"] is not None:
+                    cropland = cropland.clipToCollection(st.session_state["ROI"])
+
+                Map.addLayer(cropland, {}, "USDA NASS Cropland 2020")
+
+            # elif "HydroSHEDS" in datasets:
+            #     hydrolakes = ee.FeatureCollection(
+            #         "projects/sat-io/open-datasets/HydroLakes/lake_poly_v10"
+            #     )
+            #     if st.session_state["ROI"] is not None:
+            #         hydrolakes = hydrolakes.filterBounds(st.session_state["ROI"])
+            #     Map.addLayer(hydrolakes, {"color": "#00008B"}, "HydroSHEDS - HydroLAKES")
+
+    # roi = ee.FeatureCollection("users/giswqs/MRB/NWI_HU8_Boundary_Simplify")
+    style = {
+        "color": "000000ff",
+        "width": 1,
+        "lineType": "solid",
+        "fillColor": "00000000",
+    }
+
+    # select_holder = col2.empty()
+    with col2:
+        datasets = st.multiselect(
+            "Select surface water datasets",
+            [
+                "ESA Land Use",
+                "JRC Max Water Extent",
+                "OpenStreetMap",
+                "HydroLakes",
+                "LAGOS",
+                "US NED Depressions",
+                "Global River Width",
+            ],
+        )
+
+    # styles = {
+    #     "ESA Land Use": {
+    #         "color": "dca0dcff",
+    #         "width": width,
+    #         "fillColor": "e4bbe4ff",
+    #     },
+    #     "JRC Max Water Extent": {
+    #         "color": "ffc2cbff",
+    #         "width": width,
+    #         "fillColor": "fdd1d8ff",
+    #     },
+    #     "OpenStreetMap": {
+    #         "color": "bf03bfff",
+    #         "width": width,
+    #         "fillColor": "ebb2ebff",
+    #     },
+    #     "HydroLakes": {
+    #         "color": "4e0583ff",
+    #         "width": width,
+    #         "fillColor": "a47fbfff",
+    #     },
+    #     "LAGOS": {
+    #         "color": "8f228fff",
+    #         "width": width,
+    #         "fillColor": "cb99cbff",
+    #     },
+    #     "US NED Depressions": {
+    #         "color": "8d32e2ff",
+    #         "width": width,
+    #         "fillColor": "c394efff",
+    #     },
+    # }
+
+    width = 1
     styles = {
-        "ESA Land Use": {"color": "000000ff", "width": 1, "fillColor": "dca0dcff"},
-        "JRC Max Water Extent": {"color": "000000ff", "width": 1, "fillColor": "ffc2cbff"},
-        "OpenStreetMap": {"color": "000000ff", "width": 1, "fillColor": "bf03bfff"},
-        "HydroLakes": {"color": "000000ff", "width": 1, "fillColor": "4e0583ff"},
-        "LAGOS": {"color": "000000ff", "width": 1, "fillColor": "8f228fff"},
-        "US NED Depressions": {"color": "000000ff", "width": 1, "fillColor": "8d32e2ff"},
-        "Global River Width": {"color": "000000ff", "width": 1, "fillColor": "0000ffff"},
+        "ESA Land Use": {
+            "color": "000000ff",
+            "width": width,
+            "fillColor": "dca0dcff",
+        },
+        "JRC Max Water Extent": {
+            "color": "000000ff",
+            "width": width,
+            "fillColor": "ffc2cbff",
+        },
+        "OpenStreetMap": {
+            "color": "000000ff",
+            "width": width,
+            "fillColor": "bf03bfff",
+        },
+        "HydroLakes": {
+            "color": "000000ff",
+            "width": width,
+            "fillColor": "4e0583ff",
+        },
+        "LAGOS": {
+            "color": "000000ff",
+            "width": width,
+            "fillColor": "8f228fff",
+        },
+        "US NED Depressions": {
+            "color": "000000ff",
+            "width": width,
+            "fillColor": "8d32e2ff",
+        },
+        "Global River Width": {
+            "color": "000000ff",
+            "width": width,
+            "fillColor": "0000ffff",
+        },
     }
 
-    for dataset_name in datasets:
-        dataset = ee.FeatureCollection(f"users/giswqs/MRB/{dataset_name.replace(' ', '_').lower()}_entireus")
-        geemap.add_ee_layer(map_instance, dataset.style(**styles[dataset_name]), {}, dataset_name)
+    if "ESA Land Use" in datasets:
+        dataset = ee.FeatureCollection("users/giswqs/MRB/ESA_entireUS")
+        Map.addLayer(dataset.style(**styles["ESA Land Use"]), {}, "ESA Land Use")
+
+    if "JRC Max Water Extent" in datasets:
+        dataset = ee.FeatureCollection("users/giswqs/MRB/JRC_entireUS")
+        Map.addLayer(
+            dataset.style(**styles["JRC Max Water Extent"]), {}, "JRC Max Water Extent"
+        )
+
+    if "OpenStreetMap" in datasets:
+        dataset = ee.FeatureCollection("users/giswqs/MRB/OSM_entireUS")
+        Map.addLayer(dataset.style(**styles["OpenStreetMap"]), {}, "OpenStreetMap")
+
+    if "HydroLakes" in datasets:
+        dataset = ee.FeatureCollection("users/giswqs/MRB/HL_entireUS")
+        Map.addLayer(dataset.style(**styles["HydroLakes"]), {}, "HydroLakes")
+
+    if "LAGOS" in datasets:
+        dataset = ee.FeatureCollection("users/giswqs/MRB/LAGOS_entireUS")
+        Map.addLayer(dataset.style(**styles["LAGOS"]), {}, "LAGOS")
+
+    if "US NED Depressions" in datasets:
+        depressions = ee.FeatureCollection("users/giswqs/MRB/US_depressions")
+        Map.addLayer(
+            depressions.style(**styles["US NED Depressions"]), {}, "US NED Depressions"
+        )
+
+    if datasets:
+        legend_datasets = datasets[:]
+        # if "Global River Width" in legend_datasets:
+        #     legend_datasets.remove("Global River Width")
+        legend_dict = {}
+        for dataset in legend_datasets:
+            legend_dict[dataset] = styles[dataset]["fillColor"][:6]
+
+        if len(legend_datasets) > 0:
+
+            Map.add_legend(title="Surface Water", legend_dict=legend_dict)
+
+    # if "JRC Global Surface Water" in datasets:
+    #     jrc = ee.Image("JRC/GSW1_3/GlobalSurfaceWater")
+    #     vis = {
+    #         "bands": ["occurrence"],
+    #         "min": 0.0,
+    #         "max": 100.0,
+    #         "palette": cm.palettes.coolwarm_r,
+    #     }
+    #     Map.addLayer(jrc, vis, "JRC Global Surface Water")
+    #     Map.add_colorbar(vis, label="Surface water occurrence (%)")
+
+    if "Global River Width" in datasets:
+        water_mask = ee.ImageCollection(
+            "projects/sat-io/open-datasets/GRWL/water_mask_v01_01"
+        ).median()
+
+        grwl_summary = ee.FeatureCollection(
+            "projects/sat-io/open-datasets/GRWL/grwl_SummaryStats_v01_01"
+        )
+        grwl_water_vector = ee.FeatureCollection(
+            "projects/sat-io/open-datasets/GRWL/water_vector_v01_01"
+        )
+
+        if st.session_state["ROI"] is not None:
+            water_mask = water_mask.clipToCollection(st.session_state["ROI"])
+            grwl_summary = grwl_summary.filterBounds(st.session_state["ROI"])
+
+        Map.addLayer(water_mask, {"palette": "blue"}, "GRWL RIver Mask")
+        Map.addLayer(
+            grwl_water_vector.style(**{"fillColor": "00000000", "color": "FF5500"}),
+            {},
+            "GRWL Centerline",
+            False,
+        )
+        Map.addLayer(
+            grwl_summary.style(**{"fillColor": "00000000", "color": "EE5500"}),
+            {},
+            "GRWL Centerline Simplified",
+        )
 
-    # Add watershed boundaries selection
-    wbds = ["NHD-HUC2", "NHD-HUC4", "NHD-HUC6", "NHD-HUC8", "NHD-HUC10"]
-    wbd_selection = st.multiselect("Select watershed boundaries", wbds)
+    show = False
+    if select and country is not None:
+        name = country
+        style["color"] = "#000000"
+        style["width"] = 2
+        show = True
+    elif upload:
+        name = "ROI"
+        style["color"] = "#FFFF00"
+        style["width"] = 2
+        show = True
+    else:
+        name = "World"
 
-    for huc in wbd_selection:
-        huc_data = ee.FeatureCollection(f"USGS/WBD/2017/{huc}")
-        geemap.add_ee_layer(map_instance, huc_data.style(**{"fillColor": "00000000"}), {}, huc)
+    Map.addLayer(st.session_state["ROI"].style(**style), {}, name, show)
+    Map.centerObject(st.session_state["ROI"])
 
-    # Center and display the map
-    map_instance.set_center(longitude, latitude, zoom)
-    folium_static(map_instance, height=680)  # Use folium_static to display the map in Streamlit
+    with col2:
+        wbds = [
+            "NHD-HUC2",
+            "NHD-HUC4",
+            "NHD-HUC6",
+            "NHD-HUC8",
+            "NHD-HUC10",
+        ]
+        wbd = st.multiselect("Select watershed boundaries", wbds)
+
+        if "NHD-HUC2" in wbd:
+            huc2 = ee.FeatureCollection("USGS/WBD/2017/HUC02")
+            Map.addLayer(huc2.style(**{"fillColor": "00000000"}), {}, "NHD-HUC2")
+
+        if "NHD-HUC4" in wbd:
+            huc4 = ee.FeatureCollection("USGS/WBD/2017/HUC04")
+            Map.addLayer(huc4.style(**{"fillColor": "00000000"}), {}, "NHD-HUC4")
+
+        if "NHD-HUC6" in wbd:
+            huc6 = ee.FeatureCollection("USGS/WBD/2017/HUC06")
+            Map.addLayer(huc6.style(**{"fillColor": "00000000"}), {}, "NHD-HUC6")
+
+        if "NHD-HUC8" in wbd:
+            huc8 = ee.FeatureCollection("USGS/WBD/2017/HUC08")
+            Map.addLayer(huc8.style(**{"fillColor": "00000000"}), {}, "NHD-HUC8")
+
+        if "NHD-HUC10" in wbd:
+            huc10 = ee.FeatureCollection("USGS/WBD/2017/HUC10")
+            Map.addLayer(huc10.style(**{"fillColor": "00000000"}), {}, "NHD-HUC10")
+
+    with col1:
+        Map.set_center(longitude, latitude, zoom)
+        Map.to_streamlit(height=680)
 
-    # Data Sources Expander
     with col2:
         with st.expander("Data Sources"):
-            st.markdown("""
+
+            desc = """
                 - [ESA Global Land Cover](https://developers.google.com/earth-engine/datasets/catalog/ESA_WorldCover_v100?hl=en)
                 - [ESRI Global Land Cover](https://samapriya.github.io/awesome-gee-community-datasets/projects/esrilc2020/)
                 - [Global River Width Dataset](https://samapriya.github.io/awesome-gee-community-datasets/projects/grwl/)
@@ -2047,8 +2310,16 @@ def GlobalSurfaceWater():
                 - [HydroSHEDS - HydroLAKES](https://samapriya.github.io/awesome-gee-community-datasets/projects/hydrolakes/)
                 - [OSM Global Surface Water](https://samapriya.github.io/awesome-gee-community-datasets/projects/osm_water/)
                 - [US NLCD](https://developers.google.com/earth-engine/datasets/catalog/USGS_NLCD_RELEASES_2019_REL_NLCD)
-                - [US NED Depressions (10m)](https://developers.google.com/earth-engine/datasets/catalog/USGS_3DEP)
-            """)
+                - [US NED Depressions (10m)](https://developers.google.com/earth-engine/datasets/catalog/USGS_3DEP_10m)
+                - [USDA NASS Cropland](https://developers.google.com/earth-engine/datasets/catalog/USDA_NASS_CDL)
+                - [NHD Waterboday](https://samapriya.github.io/awesome-gee-community-datasets/projects/nhd)
+                - [NHD-HUC2](https://developers.google.com/earth-engine/datasets/catalog/USGS_WBD_2017_HUC02)
+                - [NHD-HUC4](https://developers.google.com/earth-engine/datasets/catalog/USGS_WBD_2017_HUC04)
+                - [NHD-HUC6](https://developers.google.com/earth-engine/datasets/catalog/USGS_WBD_2017_HUC06)
+                - [NHD-HUC8](https://developers.google.com/earth-engine/datasets/catalog/USGS_WBD_2017_HUC08)
+                - [NHD-HUC10](https://developers.google.com/earth-engine/datasets/catalog/USGS_WBD_2017_HUC10)
+            """
+            st.markdown(desc)
 
 #--------------------------------------------------------------------------------------------------------------------------------------------------------------------------
 def Morphometric_Analysis_for_Watershedstreams_page():