update

pages/10_🌍_Earth_Engine_Datasets.py

@@ -1,157 +0,0 @@
-import ee
-import streamlit as st
-import geemap.foliumap as geemap
-
-st.set_page_config(layout="wide")
-
-st.sidebar.info(
-    """
-    - Web App URL: <https://streamlit.gishub.org>
-    - GitHub repository: <https://github.com/giswqs/streamlit-geospatial>
-    """
-)
-
-st.sidebar.title("Contact")
-st.sidebar.info(
-    """
-    Qiusheng Wu at [wetlands.io](https://wetlands.io) | [GitHub](https://github.com/giswqs) | [Twitter](https://twitter.com/giswqs) | [YouTube](https://www.youtube.com/c/QiushengWu) | [LinkedIn](https://www.linkedin.com/in/qiushengwu)
-    """
-)
-
-
-def nlcd():
-
-    # st.header("National Land Cover Database (NLCD)")
-
-    row1_col1, row1_col2 = st.columns([3, 1])
-    width = 950
-    height = 600
-
-    Map = geemap.Map(center=[40, -100], zoom=4)
-
-    # Select the seven NLCD epoches after 2000.
-    years = ["2001", "2004", "2006", "2008", "2011", "2013", "2016", "2019"]
-
-    # Get an NLCD image by year.
-    def getNLCD(year):
-        # Import the NLCD collection.
-        dataset = ee.ImageCollection("USGS/NLCD_RELEASES/2019_REL/NLCD")
-
-        # Filter the collection by year.
-        nlcd = dataset.filter(ee.Filter.eq("system:index", year)).first()
-
-        # Select the land cover band.
-        landcover = nlcd.select("landcover")
-        return landcover
-
-    with row1_col2:
-        selected_year = st.multiselect("Select a year", years)
-        add_legend = st.checkbox("Show legend")
-
-    if selected_year:
-        for year in selected_year:
-            Map.addLayer(getNLCD(year), {}, "NLCD " + year)
-
-        if add_legend:
-            Map.add_legend(
-                legend_title="NLCD Land Cover Classification", builtin_legend="NLCD"
-            )
-        with row1_col1:
-            Map.to_streamlit(width=width, height=height)
-
-    else:
-        with row1_col1:
-            Map.to_streamlit(width=width, height=height)
-
-
-def search_data():
-
-    # st.header("Search Earth Engine Data Catalog")
-
-    Map = geemap.Map()
-
-    if "ee_assets" not in st.session_state:
-        st.session_state["ee_assets"] = None
-    if "asset_titles" not in st.session_state:
-        st.session_state["asset_titles"] = None
-
-    col1, col2 = st.columns([2, 1])
-
-    dataset = None
-    with col2:
-        keyword = st.text_input(
-            "Enter a keyword to search (e.g., elevation)", "")
-        if keyword:
-            ee_assets = geemap.search_ee_data(keyword)
-            asset_titles = [x["title"] for x in ee_assets]
-            asset_types = [x["type"] for x in ee_assets]
-
-            translate = {
-                "image_collection": "ee.ImageCollection('",
-                "image": "ee.Image('",
-                "table": "ee.FeatureCollection('",
-                "table_collection": "ee.FeatureCollection('",
-            }
-
-            dataset = st.selectbox("Select a dataset", asset_titles)
-            if len(ee_assets) > 0:
-                st.session_state["ee_assets"] = ee_assets
-                st.session_state["asset_titles"] = asset_titles
-
-            if dataset is not None:
-                with st.expander("Show dataset details", True):
-                    index = asset_titles.index(dataset)
-
-                    html = geemap.ee_data_html(
-                        st.session_state["ee_assets"][index])
-                    html = html.replace("\n", "")
-                    st.markdown(html, True)
-
-                ee_id = ee_assets[index]["id"]
-                uid = ee_assets[index]["uid"]
-                st.markdown(f"""**Earth Engine Snippet:** `{ee_id}`""")
-                ee_asset = f"{translate[asset_types[index]]}{ee_id}')"
-                vis_params = st.text_input(
-                    "Enter visualization parameters as a dictionary", {}
-                )
-                layer_name = st.text_input("Enter a layer name", uid)
-                button = st.button("Add dataset to map")
-                if button:
-                    vis = {}
-                    try:
-                        if vis_params.strip() == "":
-                            # st.error("Please enter visualization parameters")
-                            vis_params = "{}"
-                        vis = eval(vis_params)
-                        if not isinstance(vis, dict):
-                            st.error(
-                                "Visualization parameters must be a dictionary")
-                        try:
-                            Map.addLayer(eval(ee_asset), vis, layer_name)
-                        except Exception as e:
-                            st.error(f"Error adding layer: {e}")
-                    except Exception as e:
-                        st.error(f"Invalid visualization parameters: {e}")
-
-            with col1:
-                Map.to_streamlit()
-        else:
-            with col1:
-                Map.to_streamlit()
-
-
-def app():
-    st.title("Earth Engine Data Catalog")
-
-    apps = ["Search Earth Engine Data Catalog",
-            "National Land Cover Database (NLCD)"]
-
-    selected_app = st.selectbox("Select an app", apps)
-
-    if selected_app == "National Land Cover Database (NLCD)":
-        nlcd()
-    elif selected_app == "Search Earth Engine Data Catalog":
-        search_data()
-
-
-app()

pages/11_🧱_Ordnance_Survey.py

@@ -1,108 +0,0 @@
-import folium
-import pandas as pd
-import streamlit as st
-import leafmap.foliumap as leafmap
-import folium.plugins as plugins
-
-st.set_page_config(layout="wide")
-
-st.sidebar.info(
-    """
-    - Web App URL: <https://streamlit.gishub.org>
-    - GitHub repository: <https://github.com/giswqs/streamlit-geospatial>
-    """
-)
-
-st.sidebar.title("Contact")
-st.sidebar.info(
-    """
-    Qiusheng Wu at [wetlands.io](https://wetlands.io) | [GitHub](https://github.com/giswqs) | [Twitter](https://twitter.com/giswqs) | [YouTube](https://www.youtube.com/c/QiushengWu) | [LinkedIn](https://www.linkedin.com/in/qiushengwu)
-    """
-)
-
-st.title("National Library of Scotland XYZ Layers")
-df = pd.read_csv("data/scotland_xyz.tsv", sep="\t")
-basemaps = leafmap.basemaps
-names = df["Name"].values.tolist() + list(basemaps.keys())
-links = df["URL"].values.tolist() + list(basemaps.values())
-
-col1, col2, col3, col4, col5, col6, col7 = st.columns([3, 3, 1, 1, 1, 1.5, 1.5])
-with col1:
-    left_name = st.selectbox(
-        "Select the left layer",
-        names,
-        index=names.index("Great Britain - Bartholomew Half Inch, 1897-1907"),
-    )
-
-with col2:
-    right_name = st.selectbox(
-        "Select the right layer",
-        names,
-        index=names.index("HYBRID"),
-    )
-
-with col3:
-    # lat = st.slider('Latitude', -90.0, 90.0, 55.68, step=0.01)
-    lat = st.text_input("Latitude", " 55.68")
-
-with col4:
-    # lon = st.slider('Longitude', -180.0, 180.0, -2.98, step=0.01)
-    lon = st.text_input("Longitude", "-2.98")
-
-with col5:
-    # zoom = st.slider('Zoom', 1, 24, 6, step=1)
-    zoom = st.text_input("Zoom", "6")
-
-with col6:
-    checkbox = st.checkbox("Add OS 25 inch")
-
-# with col7:
-with st.expander("Acknowledgements"):
-    markdown = """
-    The map tile access is by kind arrangement of the National Library of Scotland on the understanding that re-use is for personal purposes. They host most of the map layers except these:
-- The Roy Maps are owned by the British Library.
-- The Great Britain – OS maps 1:25,000, 1937-61 and One Inch 7th series, 1955-61 are hosted by MapTiler.
-
-If you wish you use these layers within a website, or for a commercial or public purpose, please view the [National Library of Scotland Historic Maps Subscription API](https://maps.nls.uk/projects/subscription-api/) or contact them at maps@nls.uk.
-    """
-    st.markdown(markdown, unsafe_allow_html=True)
-
-m = leafmap.Map(
-    center=[float(lat), float(lon)],
-    zoom=int(zoom),
-    locate_control=True,
-    draw_control=False,
-    measure_control=False,
-)
-measure = plugins.MeasureControl(position="bottomleft", active_color="orange")
-measure.add_to(m)
-
-if left_name in basemaps:
-    left_layer = basemaps[left_name]
-else:
-    left_layer = folium.TileLayer(
-        tiles=links[names.index(left_name)],
-        name=left_name,
-        attr="National Library of Scotland",
-        overlay=True,
-    )
-
-if right_name in basemaps:
-    right_layer = basemaps[right_name]
-else:
-    right_layer = folium.TileLayer(
-        tiles=links[names.index(right_name)],
-        name=right_name,
-        attr="National Library of Scotland",
-        overlay=True,
-    )
-
-if checkbox:
-    for index, name in enumerate(names):
-        if "OS 25 inch" in name:
-            m.add_tile_layer(
-                links[index], name, attribution="National Library of Scotland"
-            )
-
-m.split_map(left_layer, right_layer)
-m.to_streamlit(height=600)

pages/12_🌲_Land_Cover_Mapping.py

@@ -1,111 +0,0 @@
-import datetime
-import ee
-import streamlit as st
-import geemap.foliumap as geemap
-
-st.set_page_config(layout="wide")
-
-st.sidebar.info(
-    """
-    - Web App URL: <https://streamlit.gishub.org>
-    - GitHub repository: <https://github.com/giswqs/streamlit-geospatial>
-    """
-)
-
-st.sidebar.title("Contact")
-st.sidebar.info(
-    """
-    Qiusheng Wu at [wetlands.io](https://wetlands.io) | [GitHub](https://github.com/giswqs) | [Twitter](https://twitter.com/giswqs) | [YouTube](https://www.youtube.com/c/QiushengWu) | [LinkedIn](https://www.linkedin.com/in/qiushengwu)
-    """
-)
-
-st.title("Comparing Global Land Cover Maps")
-
-col1, col2 = st.columns([4, 1])
-
-Map = geemap.Map()
-Map.add_basemap("ESA WorldCover 2020 S2 FCC")
-Map.add_basemap("ESA WorldCover 2020 S2 TCC")
-Map.add_basemap("HYBRID")
-
-esa = ee.ImageCollection("ESA/WorldCover/v100").first()
-esa_vis = {"bands": ["Map"]}
-
-
-esri = ee.ImageCollection(
-    "projects/sat-io/open-datasets/landcover/ESRI_Global-LULC_10m"
-).mosaic()
-esri_vis = {
-    "min": 1,
-    "max": 10,
-    "palette": [
-        "#1A5BAB",
-        "#358221",
-        "#A7D282",
-        "#87D19E",
-        "#FFDB5C",
-        "#EECFA8",
-        "#ED022A",
-        "#EDE9E4",
-        "#F2FAFF",
-        "#C8C8C8",
-    ],
-}
-
-
-markdown = """
-    - [Dynamic World Land Cover](https://developers.google.com/earth-engine/datasets/catalog/GOOGLE_DYNAMICWORLD_V1?hl=en)
-    - [ESA Global Land Cover](https://developers.google.com/earth-engine/datasets/catalog/ESA_WorldCover_v100)
-    - [ESRI Global Land Cover](https://samapriya.github.io/awesome-gee-community-datasets/projects/esrilc2020)
-
-"""
-
-with col2:
-
-    longitude = st.number_input("Longitude", -180.0, 180.0, -89.3998)
-    latitude = st.number_input("Latitude", -90.0, 90.0, 43.0886)
-    zoom = st.number_input("Zoom", 0, 20, 11)
-
-    Map.setCenter(longitude, latitude, zoom)
-
-    start = st.date_input("Start Date for Dynamic World", datetime.date(2020, 1, 1))
-    end = st.date_input("End Date for Dynamic World", datetime.date(2021, 1, 1))
-
-    start_date = start.strftime("%Y-%m-%d")
-    end_date = end.strftime("%Y-%m-%d")
-
-    region = ee.Geometry.BBox(-179, -89, 179, 89)
-    dw = geemap.dynamic_world(region, start_date, end_date, return_type="hillshade")
-
-    layers = {
-        "Dynamic World": geemap.ee_tile_layer(dw, {}, "Dynamic World Land Cover"),
-        "ESA Land Cover": geemap.ee_tile_layer(esa, esa_vis, "ESA Land Cover"),
-        "ESRI Land Cover": geemap.ee_tile_layer(esri, esri_vis, "ESRI Land Cover"),
-    }
-
-    options = list(layers.keys())
-    left = st.selectbox("Select a left layer", options, index=1)
-    right = st.selectbox("Select a right layer", options, index=0)
-
-    left_layer = layers[left]
-    right_layer = layers[right]
-
-    Map.split_map(left_layer, right_layer)
-
-    legend = st.selectbox("Select a legend", options, index=options.index(right))
-    if legend == "Dynamic World":
-        Map.add_legend(
-            title="Dynamic World Land Cover",
-            builtin_legend="Dynamic_World",
-        )
-    elif legend == "ESA Land Cover":
-        Map.add_legend(title="ESA Land Cover", builtin_legend="ESA_WorldCover")
-    elif legend == "ESRI Land Cover":
-        Map.add_legend(title="ESRI Land Cover", builtin_legend="ESRI_LandCover")
-
-    with st.expander("Data sources"):
-        st.markdown(markdown)
-
-
-with col1:
-    Map.to_streamlit(height=750)

pages/13_🏘️_Global_Building_Footprints.py

@@ -1,111 +0,0 @@
-import ee
-import geemap.foliumap as geemap
-import geopandas as gpd
-import streamlit as st
-
-st.set_page_config(layout="wide")
-
-
-@st.cache(persist=True)
-def ee_authenticate(token_name="EARTHENGINE_TOKEN"):
-    geemap.ee_initialize(token_name=token_name)
-
-
-st.sidebar.info(
-    """
-    - Web App URL: <https://streamlit.gishub.org>
-    - GitHub repository: <https://github.com/giswqs/streamlit-geospatial>
-    """
-)
-
-st.sidebar.title("Contact")
-st.sidebar.info(
-    """
-    Qiusheng Wu at [wetlands.io](https://wetlands.io) | [GitHub](https://github.com/giswqs) | [Twitter](https://twitter.com/giswqs) | [YouTube](https://www.youtube.com/c/QiushengWu) | [LinkedIn](https://www.linkedin.com/in/qiushengwu)
-    """
-)
-
-st.title("Global Building Footprints")
-
-col1, col2 = st.columns([8, 2])
-
-
-@st.cache(allow_output_mutation=True)
-def read_data(url):
-    return gpd.read_file(url)
-
-
-countries = 'https://github.com/giswqs/geemap/raw/master/examples/data/countries.geojson'
-states = 'https://github.com/giswqs/geemap/raw/master/examples/data/us_states.json'
-
-countries_gdf = read_data(countries)
-states_gdf = read_data(states)
-
-country_names = countries_gdf['NAME'].values.tolist()
-country_names.remove('United States of America')
-country_names.append('USA')
-country_names.sort()
-country_names = [name.replace('.', '').replace(' ', '_')
-                 for name in country_names]
-
-state_names = states_gdf['name'].values.tolist()
-
-basemaps = list(geemap.basemaps)
-
-Map = geemap.Map()
-
-with col2:
-
-    basemap = st.selectbox("Select a basemap", basemaps,
-                           index=basemaps.index('HYBRID'))
-    Map.add_basemap(basemap)
-
-    country = st.selectbox('Select a country', country_names,
-                           index=country_names.index('USA'))
-
-    if country == 'USA':
-        state = st.selectbox('Select a state', state_names,
-                             index=state_names.index('Florida'))
-        layer_name = state
-
-        try:
-            fc = ee.FeatureCollection(
-                f'projects/sat-io/open-datasets/MSBuildings/US/{state}')
-        except:
-            st.error('No data available for the selected state.')
-
-    else:
-        try:
-            fc = ee.FeatureCollection(
-                f'projects/sat-io/open-datasets/MSBuildings/{country}')
-        except:
-            st.error('No data available for the selected country.')
-
-        layer_name = country
-
-    color = st.color_picker('Select a color', '#FF5500')
-
-    style = {'fillColor': '00000000', 'color': color}
-
-    split = st.checkbox("Split-panel map")
-
-    if split:
-        left = geemap.ee_tile_layer(fc.style(**style), {}, 'Left')
-        right = left
-        Map.split_map(left, right)
-    else:
-        Map.addLayer(fc.style(**style), {}, layer_name)
-
-    Map.centerObject(fc.first(), zoom=16)
-
-    with st.expander("Data Sources"):
-        st.info(
-            """
-            [Microsoft Building Footprints](https://gee-community-catalog.org/projects/msbuildings/)
-            """
-        )
-
-
-with col1:
-
-    Map.to_streamlit(height=1000)

pages/{5_📍_Marker_Cluster.py → 1_📍_Marker_Cluster.py}

@@ -5,15 +5,15 @@ st.set_page_config(layout="wide")
 
 st.sidebar.info(
     """
-    - Web App URL: <https://streamlit.gishub.org>
-    - GitHub repository: <https://github.com/giswqs/streamlit-geospatial>
+    - Web App URL: <https://huggingface.co/spaces/yunusserhat/Crime-Map>
+    - HuggingFace repository: <https://huggingface.co/spaces/yunusserhat/Crime-Map/tree/main>
     """
 )
 
 st.sidebar.title("Contact")
 st.sidebar.info(
     """
-    Qiusheng Wu at [wetlands.io](https://wetlands.io) | [GitHub](https://github.com/giswqs) | [Twitter](https://twitter.com/giswqs) | [YouTube](https://www.youtube.com/c/QiushengWu) | [LinkedIn](https://www.linkedin.com/in/qiushengwu)
+    Yunus Serhat Bıçakçı at [yunusserhat.com](https://yunusserhat.com) | [GitHub](https://github.com/yunusserhat) | [Twitter](https://twitter.com/yunusserhat) | [LinkedIn](https://www.linkedin.com/in/yunusserhat)
     """
 )
 

pages/1_📷_Timelapse.py

@@ -1,1527 +0,0 @@
-import ee
-import os
-import warnings
-import datetime
-import fiona
-import geopandas as gpd
-import folium
-import streamlit as st
-import geemap.colormaps as cm
-import geemap.foliumap as geemap
-from datetime import date
-from shapely.geometry import Polygon
-
-st.set_page_config(layout="wide")
-warnings.filterwarnings("ignore")
-
-
-@st.cache(allow_output_mutation=True)
-def ee_authenticate(token_name="EARTHENGINE_TOKEN"):
-    geemap.ee_initialize(token_name=token_name)
-
-
-st.sidebar.info(
-    """
-    - Web App URL: <https://streamlit.gishub.org>
-    - GitHub repository: <https://github.com/giswqs/streamlit-geospatial>
-    """
-)
-
-st.sidebar.title("Contact")
-st.sidebar.info(
-    """
-    Qiusheng Wu at [wetlands.io](https://wetlands.io) | [GitHub](https://github.com/giswqs) | [Twitter](https://twitter.com/giswqs) | [YouTube](https://www.youtube.com/c/QiushengWu) | [LinkedIn](https://www.linkedin.com/in/qiushengwu)
-    """
-)
-
-goes_rois = {
-    "Creek Fire, CA (2020-09-05)": {
-        "region": Polygon(
-            [
-                [-121.003418, 36.848857],
-                [-121.003418, 39.049052],
-                [-117.905273, 39.049052],
-                [-117.905273, 36.848857],
-                [-121.003418, 36.848857],
-            ]
-        ),
-        "start_time": "2020-09-05T15:00:00",
-        "end_time": "2020-09-06T02:00:00",
-    },
-    "Bomb Cyclone (2021-10-24)": {
-        "region": Polygon(
-            [
-                [-159.5954, 60.4088],
-                [-159.5954, 24.5178],
-                [-114.2438, 24.5178],
-                [-114.2438, 60.4088],
-            ]
-        ),
-        "start_time": "2021-10-24T14:00:00",
-        "end_time": "2021-10-25T01:00:00",
-    },
-    "Hunga Tonga Volcanic Eruption (2022-01-15)": {
-        "region": Polygon(
-            [
-                [-192.480469, -32.546813],
-                [-192.480469, -8.754795],
-                [-157.587891, -8.754795],
-                [-157.587891, -32.546813],
-                [-192.480469, -32.546813],
-            ]
-        ),
-        "start_time": "2022-01-15T03:00:00",
-        "end_time": "2022-01-15T07:00:00",
-    },
-    "Hunga Tonga Volcanic Eruption Closer Look (2022-01-15)": {
-        "region": Polygon(
-            [
-                [-178.901367, -22.958393],
-                [-178.901367, -17.85329],
-                [-171.452637, -17.85329],
-                [-171.452637, -22.958393],
-                [-178.901367, -22.958393],
-            ]
-        ),
-        "start_time": "2022-01-15T03:00:00",
-        "end_time": "2022-01-15T07:00:00",
-    },
-}
-
-
-landsat_rois = {
-    "Aral Sea": Polygon(
-        [
-            [57.667236, 43.834527],
-            [57.667236, 45.996962],
-            [61.12793, 45.996962],
-            [61.12793, 43.834527],
-            [57.667236, 43.834527],
-        ]
-    ),
-    "Dubai": Polygon(
-        [
-            [54.541626, 24.763044],
-            [54.541626, 25.427152],
-            [55.632019, 25.427152],
-            [55.632019, 24.763044],
-            [54.541626, 24.763044],
-        ]
-    ),
-    "Hong Kong International Airport": Polygon(
-        [
-            [113.825226, 22.198849],
-            [113.825226, 22.349758],
-            [114.085121, 22.349758],
-            [114.085121, 22.198849],
-            [113.825226, 22.198849],
-        ]
-    ),
-    "Las Vegas, NV": Polygon(
-        [
-            [-115.554199, 35.804449],
-            [-115.554199, 36.558188],
-            [-113.903503, 36.558188],
-            [-113.903503, 35.804449],
-            [-115.554199, 35.804449],
-        ]
-    ),
-    "Pucallpa, Peru": Polygon(
-        [
-            [-74.672699, -8.600032],
-            [-74.672699, -8.254983],
-            [-74.279938, -8.254983],
-            [-74.279938, -8.600032],
-        ]
-    ),
-    "Sierra Gorda, Chile": Polygon(
-        [
-            [-69.315491, -22.837104],
-            [-69.315491, -22.751488],
-            [-69.190006, -22.751488],
-            [-69.190006, -22.837104],
-            [-69.315491, -22.837104],
-        ]
-    ),
-}
-
-modis_rois = {
-    "World": Polygon(
-        [
-            [-171.210938, -57.136239],
-            [-171.210938, 79.997168],
-            [177.539063, 79.997168],
-            [177.539063, -57.136239],
-            [-171.210938, -57.136239],
-        ]
-    ),
-    "Africa": Polygon(
-        [
-            [-18.6983, 38.1446],
-            [-18.6983, -36.1630],
-            [52.2293, -36.1630],
-            [52.2293, 38.1446],
-        ]
-    ),
-    "USA": Polygon(
-        [
-            [-127.177734, 23.725012],
-            [-127.177734, 50.792047],
-            [-66.269531, 50.792047],
-            [-66.269531, 23.725012],
-            [-127.177734, 23.725012],
-        ]
-    ),
-}
-
-ocean_rois = {
-    "Gulf of Mexico": Polygon(
-        [
-            [-101.206055, 15.496032],
-            [-101.206055, 32.361403],
-            [-75.673828, 32.361403],
-            [-75.673828, 15.496032],
-            [-101.206055, 15.496032],
-        ]
-    ),
-    "North Atlantic Ocean": Polygon(
-        [
-            [-85.341797, 24.046464],
-            [-85.341797, 45.02695],
-            [-55.810547, 45.02695],
-            [-55.810547, 24.046464],
-            [-85.341797, 24.046464],
-        ]
-    ),
-    "World": Polygon(
-        [
-            [-171.210938, -57.136239],
-            [-171.210938, 79.997168],
-            [177.539063, 79.997168],
-            [177.539063, -57.136239],
-            [-171.210938, -57.136239],
-        ]
-    ),
-}
-
-
-@st.cache(allow_output_mutation=True)
-def uploaded_file_to_gdf(data):
-    import tempfile
-    import os
-    import uuid
-
-    _, file_extension = os.path.splitext(data.name)
-    file_id = str(uuid.uuid4())
-    file_path = os.path.join(tempfile.gettempdir(), f"{file_id}{file_extension}")
-
-    with open(file_path, "wb") as file:
-        file.write(data.getbuffer())
-
-    if file_path.lower().endswith(".kml"):
-        fiona.drvsupport.supported_drivers["KML"] = "rw"
-        gdf = gpd.read_file(file_path, driver="KML")
-    else:
-        gdf = gpd.read_file(file_path)
-
-    return gdf
-
-
-def app():
-
-    today = date.today()
-
-    st.title("Create Satellite Timelapse")
-
-    st.markdown(
-        """
-        An interactive web app for creating [Landsat](https://developers.google.com/earth-engine/datasets/catalog/landsat)/[GOES](https://jstnbraaten.medium.com/goes-in-earth-engine-53fbc8783c16) timelapse for any location around the globe. 
-        The app was built using [streamlit](https://streamlit.io), [geemap](https://geemap.org), and [Google Earth Engine](https://earthengine.google.com). For more info, check out my streamlit [blog post](https://blog.streamlit.io/creating-satellite-timelapse-with-streamlit-and-earth-engine). 
-    """
-    )
-
-    row1_col1, row1_col2 = st.columns([2, 1])
-
-    if st.session_state.get("zoom_level") is None:
-        st.session_state["zoom_level"] = 4
-
-    st.session_state["ee_asset_id"] = None
-    st.session_state["bands"] = None
-    st.session_state["palette"] = None
-    st.session_state["vis_params"] = None
-
-    with row1_col1:
-        ee_authenticate(token_name="EARTHENGINE_TOKEN")
-        m = geemap.Map(
-            basemap="HYBRID",
-            plugin_Draw=True,
-            Draw_export=True,
-            locate_control=True,
-            plugin_LatLngPopup=False,
-        )
-        m.add_basemap("ROADMAP")
-
-    with row1_col2:
-
-        keyword = st.text_input("Search for a location:", "")
-        if keyword:
-            locations = geemap.geocode(keyword)
-            if locations is not None and len(locations) > 0:
-                str_locations = [str(g)[1:-1] for g in locations]
-                location = st.selectbox("Select a location:", str_locations)
-                loc_index = str_locations.index(location)
-                selected_loc = locations[loc_index]
-                lat, lng = selected_loc.lat, selected_loc.lng
-                folium.Marker(location=[lat, lng], popup=location).add_to(m)
-                m.set_center(lng, lat, 12)
-                st.session_state["zoom_level"] = 12
-
-        collection = st.selectbox(
-            "Select a satellite image collection: ",
-            [
-                "Any Earth Engine ImageCollection",
-                "Landsat TM-ETM-OLI Surface Reflectance",
-                "Sentinel-2 MSI Surface Reflectance",
-                "Geostationary Operational Environmental Satellites (GOES)",
-                "MODIS Vegetation Indices (NDVI/EVI) 16-Day Global 1km",
-                "MODIS Gap filled Land Surface Temperature Daily",
-                "MODIS Ocean Color SMI",
-                "USDA National Agriculture Imagery Program (NAIP)",
-            ],
-            index=1,
-        )
-
-        if collection in [
-            "Landsat TM-ETM-OLI Surface Reflectance",
-            "Sentinel-2 MSI Surface Reflectance",
-        ]:
-            roi_options = ["Uploaded GeoJSON"] + list(landsat_rois.keys())
-
-        elif collection == "Geostationary Operational Environmental Satellites (GOES)":
-            roi_options = ["Uploaded GeoJSON"] + list(goes_rois.keys())
-
-        elif collection in [
-            "MODIS Vegetation Indices (NDVI/EVI) 16-Day Global 1km",
-            "MODIS Gap filled Land Surface Temperature Daily",
-        ]:
-            roi_options = ["Uploaded GeoJSON"] + list(modis_rois.keys())
-        elif collection == "MODIS Ocean Color SMI":
-            roi_options = ["Uploaded GeoJSON"] + list(ocean_rois.keys())
-        else:
-            roi_options = ["Uploaded GeoJSON"]
-
-        if collection == "Any Earth Engine ImageCollection":
-            keyword = st.text_input("Enter a keyword to search (e.g., MODIS):", "")
-            if keyword:
-
-                assets = geemap.search_ee_data(keyword)
-                ee_assets = []
-                for asset in assets:
-                    if asset["ee_id_snippet"].startswith("ee.ImageCollection"):
-                        ee_assets.append(asset)
-
-                asset_titles = [x["title"] for x in ee_assets]
-                dataset = st.selectbox("Select a dataset:", asset_titles)
-                if len(ee_assets) > 0:
-                    st.session_state["ee_assets"] = ee_assets
-                    st.session_state["asset_titles"] = asset_titles
-                    index = asset_titles.index(dataset)
-                    ee_id = ee_assets[index]["id"]
-                else:
-                    ee_id = ""
-
-                if dataset is not None:
-                    with st.expander("Show dataset details", False):
-                        index = asset_titles.index(dataset)
-                        html = geemap.ee_data_html(st.session_state["ee_assets"][index])
-                        st.markdown(html, True)
-            # elif collection == "MODIS Gap filled Land Surface Temperature Daily":
-            #     ee_id = ""
-            else:
-                ee_id = ""
-
-            asset_id = st.text_input("Enter an ee.ImageCollection asset ID:", ee_id)
-
-            if asset_id:
-                with st.expander("Customize band combination and color palette", True):
-                    try:
-                        col = ee.ImageCollection.load(asset_id)
-                        st.session_state["ee_asset_id"] = asset_id
-                    except:
-                        st.error("Invalid Earth Engine asset ID.")
-                        st.session_state["ee_asset_id"] = None
-                        return
-
-                    img_bands = col.first().bandNames().getInfo()
-                    if len(img_bands) >= 3:
-                        default_bands = img_bands[:3][::-1]
-                    else:
-                        default_bands = img_bands[:]
-                    bands = st.multiselect(
-                        "Select one or three bands (RGB):", img_bands, default_bands
-                    )
-                    st.session_state["bands"] = bands
-
-                    if len(bands) == 1:
-                        palette_options = st.selectbox(
-                            "Color palette",
-                            cm.list_colormaps(),
-                            index=2,
-                        )
-                        palette_values = cm.get_palette(palette_options, 15)
-                        palette = st.text_area(
-                            "Enter a custom palette:",
-                            palette_values,
-                        )
-                        st.write(
-                            cm.plot_colormap(cmap=palette_options, return_fig=True)
-                        )
-                        st.session_state["palette"] = eval(palette)
-
-                    if bands:
-                        vis_params = st.text_area(
-                            "Enter visualization parameters",
-                            "{'bands': ["
-                            + ", ".join([f"'{band}'" for band in bands])
-                            + "]}",
-                        )
-                    else:
-                        vis_params = st.text_area(
-                            "Enter visualization parameters",
-                            "{}",
-                        )
-                    try:
-                        st.session_state["vis_params"] = eval(vis_params)
-                        st.session_state["vis_params"]["palette"] = st.session_state[
-                            "palette"
-                        ]
-                    except Exception as e:
-                        st.session_state["vis_params"] = None
-                        st.error(
-                            f"Invalid visualization parameters. It must be a dictionary."
-                        )
-
-        elif collection == "MODIS Gap filled Land Surface Temperature Daily":
-            with st.expander("Show dataset details", False):
-                st.markdown(
-                    """
-                See the [Awesome GEE Community Datasets](https://samapriya.github.io/awesome-gee-community-datasets/projects/daily_lst/).
-                """
-                )
-
-            MODIS_options = ["Daytime (1:30 pm)", "Nighttime (1:30 am)"]
-            MODIS_option = st.selectbox("Select a MODIS dataset:", MODIS_options)
-            if MODIS_option == "Daytime (1:30 pm)":
-                st.session_state[
-                    "ee_asset_id"
-                ] = "projects/sat-io/open-datasets/gap-filled-lst/gf_day_1km"
-            else:
-                st.session_state[
-                    "ee_asset_id"
-                ] = "projects/sat-io/open-datasets/gap-filled-lst/gf_night_1km"
-
-            palette_options = st.selectbox(
-                "Color palette",
-                cm.list_colormaps(),
-                index=90,
-            )
-            palette_values = cm.get_palette(palette_options, 15)
-            palette = st.text_area(
-                "Enter a custom palette:",
-                palette_values,
-            )
-            st.write(cm.plot_colormap(cmap=palette_options, return_fig=True))
-            st.session_state["palette"] = eval(palette)
-        elif collection == "MODIS Ocean Color SMI":
-            with st.expander("Show dataset details", False):
-                st.markdown(
-                    """
-                See the [Earth Engine Data Catalog](https://developers.google.com/earth-engine/datasets/catalog/NASA_OCEANDATA_MODIS-Aqua_L3SMI).
-                """
-                )
-
-            MODIS_options = ["Aqua", "Terra"]
-            MODIS_option = st.selectbox("Select a satellite:", MODIS_options)
-            st.session_state["ee_asset_id"] = MODIS_option
-            # if MODIS_option == "Daytime (1:30 pm)":
-            #     st.session_state[
-            #         "ee_asset_id"
-            #     ] = "projects/sat-io/open-datasets/gap-filled-lst/gf_day_1km"
-            # else:
-            #     st.session_state[
-            #         "ee_asset_id"
-            #     ] = "projects/sat-io/open-datasets/gap-filled-lst/gf_night_1km"
-
-            band_dict = {
-                "Chlorophyll a concentration": "chlor_a",
-                "Normalized fluorescence line height": "nflh",
-                "Particulate organic carbon": "poc",
-                "Sea surface temperature": "sst",
-                "Remote sensing reflectance at band 412nm": "Rrs_412",
-                "Remote sensing reflectance at band 443nm": "Rrs_443",
-                "Remote sensing reflectance at band 469nm": "Rrs_469",
-                "Remote sensing reflectance at band 488nm": "Rrs_488",
-                "Remote sensing reflectance at band 531nm": "Rrs_531",
-                "Remote sensing reflectance at band 547nm": "Rrs_547",
-                "Remote sensing reflectance at band 555nm": "Rrs_555",
-                "Remote sensing reflectance at band 645nm": "Rrs_645",
-                "Remote sensing reflectance at band 667nm": "Rrs_667",
-                "Remote sensing reflectance at band 678nm": "Rrs_678",
-            }
-
-            band_options = list(band_dict.keys())
-            band = st.selectbox(
-                "Select a band",
-                band_options,
-                band_options.index("Sea surface temperature"),
-            )
-            st.session_state["band"] = band_dict[band]
-
-            colors = cm.list_colormaps()
-            palette_options = st.selectbox(
-                "Color palette",
-                colors,
-                index=colors.index("coolwarm"),
-            )
-            palette_values = cm.get_palette(palette_options, 15)
-            palette = st.text_area(
-                "Enter a custom palette:",
-                palette_values,
-            )
-            st.write(cm.plot_colormap(cmap=palette_options, return_fig=True))
-            st.session_state["palette"] = eval(palette)
-
-        sample_roi = st.selectbox(
-            "Select a sample ROI or upload a GeoJSON file:",
-            roi_options,
-            index=0,
-        )
-
-        add_outline = st.checkbox(
-            "Overlay an administrative boundary on timelapse", False
-        )
-
-        if add_outline:
-
-            with st.expander("Customize administrative boundary", True):
-
-                overlay_options = {
-                    "User-defined": None,
-                    "Continents": "continents",
-                    "Countries": "countries",
-                    "US States": "us_states",
-                    "China": "china",
-                }
-
-                overlay = st.selectbox(
-                    "Select an administrative boundary:",
-                    list(overlay_options.keys()),
-                    index=2,
-                )
-
-                overlay_data = overlay_options[overlay]
-
-                if overlay_data is None:
-                    overlay_data = st.text_input(
-                        "Enter an HTTP URL to a GeoJSON file or an ee.FeatureCollection asset id:",
-                        "https://raw.githubusercontent.com/giswqs/geemap/master/examples/data/countries.geojson",
-                    )
-
-                overlay_color = st.color_picker(
-                    "Select a color for the administrative boundary:", "#000000"
-                )
-                overlay_width = st.slider(
-                    "Select a line width for the administrative boundary:", 1, 20, 1
-                )
-                overlay_opacity = st.slider(
-                    "Select an opacity for the administrative boundary:",
-                    0.0,
-                    1.0,
-                    1.0,
-                    0.05,
-                )
-        else:
-            overlay_data = None
-            overlay_color = "black"
-            overlay_width = 1
-            overlay_opacity = 1
-
-    with row1_col1:
-
-        with st.expander(
-            "Steps: Draw a rectangle on the map -> Export it as a GeoJSON -> Upload it back to the app -> Click the Submit button. Expand this tab to see a demo 👉"
-        ):
-            video_empty = st.empty()
-
-        data = st.file_uploader(
-            "Upload a GeoJSON file to use as an ROI. Customize timelapse parameters and then click the Submit button 😇👇",
-            type=["geojson", "kml", "zip"],
-        )
-
-        crs = "epsg:4326"
-        if sample_roi == "Uploaded GeoJSON":
-            if data is None:
-                # st.info(
-                #     "Steps to create a timelapse: Draw a rectangle on the map -> Export it as a GeoJSON -> Upload it back to the app -> Click Submit button"
-                # )
-                if collection in [
-                    "Geostationary Operational Environmental Satellites (GOES)",
-                    "USDA National Agriculture Imagery Program (NAIP)",
-                ] and (not keyword):
-                    m.set_center(-100, 40, 3)
-                # else:
-                #     m.set_center(4.20, 18.63, zoom=2)
-        else:
-            if collection in [
-                "Landsat TM-ETM-OLI Surface Reflectance",
-                "Sentinel-2 MSI Surface Reflectance",
-            ]:
-                gdf = gpd.GeoDataFrame(
-                    index=[0], crs=crs, geometry=[landsat_rois[sample_roi]]
-                )
-            elif (
-                collection
-                == "Geostationary Operational Environmental Satellites (GOES)"
-            ):
-                gdf = gpd.GeoDataFrame(
-                    index=[0], crs=crs, geometry=[goes_rois[sample_roi]["region"]]
-                )
-            elif collection == "MODIS Vegetation Indices (NDVI/EVI) 16-Day Global 1km":
-                gdf = gpd.GeoDataFrame(
-                    index=[0], crs=crs, geometry=[modis_rois[sample_roi]]
-                )
-
-        if sample_roi != "Uploaded GeoJSON":
-
-            if collection in [
-                "Landsat TM-ETM-OLI Surface Reflectance",
-                "Sentinel-2 MSI Surface Reflectance",
-            ]:
-                gdf = gpd.GeoDataFrame(
-                    index=[0], crs=crs, geometry=[landsat_rois[sample_roi]]
-                )
-            elif (
-                collection
-                == "Geostationary Operational Environmental Satellites (GOES)"
-            ):
-                gdf = gpd.GeoDataFrame(
-                    index=[0], crs=crs, geometry=[goes_rois[sample_roi]["region"]]
-                )
-            elif collection in [
-                "MODIS Vegetation Indices (NDVI/EVI) 16-Day Global 1km",
-                "MODIS Gap filled Land Surface Temperature Daily",
-            ]:
-                gdf = gpd.GeoDataFrame(
-                    index=[0], crs=crs, geometry=[modis_rois[sample_roi]]
-                )
-            elif collection == "MODIS Ocean Color SMI":
-                gdf = gpd.GeoDataFrame(
-                    index=[0], crs=crs, geometry=[ocean_rois[sample_roi]]
-                )
-            try:
-                st.session_state["roi"] = geemap.gdf_to_ee(gdf, geodesic=False)
-            except Exception as e:
-                st.error(e)
-                st.error("Please draw another ROI and try again.")
-                return
-            m.add_gdf(gdf, "ROI")
-
-        elif data:
-            gdf = uploaded_file_to_gdf(data)
-            try:
-                st.session_state["roi"] = geemap.gdf_to_ee(gdf, geodesic=False)
-                m.add_gdf(gdf, "ROI")
-            except Exception as e:
-                st.error(e)
-                st.error("Please draw another ROI and try again.")
-                return
-
-        m.to_streamlit(height=600)
-
-    with row1_col2:
-
-        if collection in [
-            "Landsat TM-ETM-OLI Surface Reflectance",
-            "Sentinel-2 MSI Surface Reflectance",
-        ]:
-
-            if collection == "Landsat TM-ETM-OLI Surface Reflectance":
-                sensor_start_year = 1984
-                timelapse_title = "Landsat Timelapse"
-                timelapse_speed = 5
-            elif collection == "Sentinel-2 MSI Surface Reflectance":
-                sensor_start_year = 2015
-                timelapse_title = "Sentinel-2 Timelapse"
-                timelapse_speed = 5
-            video_empty.video("https://youtu.be/VVRK_-dEjR4")
-
-            with st.form("submit_landsat_form"):
-
-                roi = None
-                if st.session_state.get("roi") is not None:
-                    roi = st.session_state.get("roi")
-                out_gif = geemap.temp_file_path(".gif")
-
-                title = st.text_input(
-                    "Enter a title to show on the timelapse: ", timelapse_title
-                )
-                RGB = st.selectbox(
-                    "Select an RGB band combination:",
-                    [
-                        "Red/Green/Blue",
-                        "NIR/Red/Green",
-                        "SWIR2/SWIR1/NIR",
-                        "NIR/SWIR1/Red",
-                        "SWIR2/NIR/Red",
-                        "SWIR2/SWIR1/Red",
-                        "SWIR1/NIR/Blue",
-                        "NIR/SWIR1/Blue",
-                        "SWIR2/NIR/Green",
-                        "SWIR1/NIR/Red",
-                        "SWIR2/NIR/SWIR1",
-                        "SWIR1/NIR/SWIR2",
-                    ],
-                    index=9,
-                )
-
-                frequency = st.selectbox(
-                    "Select a temporal frequency:",
-                    ["year", "quarter", "month"],
-                    index=0,
-                )
-
-                with st.expander("Customize timelapse"):
-
-                    speed = st.slider("Frames per second:", 1, 30, timelapse_speed)
-                    dimensions = st.slider(
-                        "Maximum dimensions (Width*Height) in pixels", 768, 2000, 768
-                    )
-                    progress_bar_color = st.color_picker(
-                        "Progress bar color:", "#0000ff"
-                    )
-                    years = st.slider(
-                        "Start and end year:",
-                        sensor_start_year,
-                        today.year,
-                        (sensor_start_year, today.year),
-                    )
-                    months = st.slider("Start and end month:", 1, 12, (1, 12))
-                    font_size = st.slider("Font size:", 10, 50, 30)
-                    font_color = st.color_picker("Font color:", "#ffffff")
-                    apply_fmask = st.checkbox(
-                        "Apply fmask (remove clouds, shadows, snow)", True
-                    )
-                    font_type = st.selectbox(
-                        "Select the font type for the title:",
-                        ["arial.ttf", "alibaba.otf"],
-                        index=0,
-                    )
-                    fading = st.slider(
-                        "Fading duration (seconds) for each frame:", 0.0, 3.0, 0.0
-                    )
-                    mp4 = st.checkbox("Save timelapse as MP4", True)
-
-                empty_text = st.empty()
-                empty_image = st.empty()
-                empty_fire_image = st.empty()
-                empty_video = st.container()
-                submitted = st.form_submit_button("Submit")
-                if submitted:
-
-                    if sample_roi == "Uploaded GeoJSON" and data is None:
-                        empty_text.warning(
-                            "Steps to create a timelapse: Draw a rectangle on the map -> Export it as a GeoJSON -> Upload it back to the app -> Click the Submit button. Alternatively, you can select a sample ROI from the dropdown list."
-                        )
-                    else:
-
-                        empty_text.text("Computing... Please wait...")
-
-                        start_year = years[0]
-                        end_year = years[1]
-                        start_date = str(months[0]).zfill(2) + "-01"
-                        end_date = str(months[1]).zfill(2) + "-30"
-                        bands = RGB.split("/")
-
-                        try:
-                            if collection == "Landsat TM-ETM-OLI Surface Reflectance":
-                                out_gif = geemap.landsat_timelapse(
-                                    roi=roi,
-                                    out_gif=out_gif,
-                                    start_year=start_year,
-                                    end_year=end_year,
-                                    start_date=start_date,
-                                    end_date=end_date,
-                                    bands=bands,
-                                    apply_fmask=apply_fmask,
-                                    frames_per_second=speed,
-                                    # dimensions=dimensions,
-                                    dimensions=768,
-                                    overlay_data=overlay_data,
-                                    overlay_color=overlay_color,
-                                    overlay_width=overlay_width,
-                                    overlay_opacity=overlay_opacity,
-                                    frequency=frequency,
-                                    date_format=None,
-                                    title=title,
-                                    title_xy=("2%", "90%"),
-                                    add_text=True,
-                                    text_xy=("2%", "2%"),
-                                    text_sequence=None,
-                                    font_type=font_type,
-                                    font_size=font_size,
-                                    font_color=font_color,
-                                    add_progress_bar=True,
-                                    progress_bar_color=progress_bar_color,
-                                    progress_bar_height=5,
-                                    loop=0,
-                                    mp4=mp4,
-                                    fading=fading,
-                                )
-                            elif collection == "Sentinel-2 MSI Surface Reflectance":
-                                out_gif = geemap.sentinel2_timelapse(
-                                    roi=roi,
-                                    out_gif=out_gif,
-                                    start_year=start_year,
-                                    end_year=end_year,
-                                    start_date=start_date,
-                                    end_date=end_date,
-                                    bands=bands,
-                                    apply_fmask=apply_fmask,
-                                    frames_per_second=speed,
-                                    dimensions=768,
-                                    # dimensions=dimensions,
-                                    overlay_data=overlay_data,
-                                    overlay_color=overlay_color,
-                                    overlay_width=overlay_width,
-                                    overlay_opacity=overlay_opacity,
-                                    frequency=frequency,
-                                    date_format=None,
-                                    title=title,
-                                    title_xy=("2%", "90%"),
-                                    add_text=True,
-                                    text_xy=("2%", "2%"),
-                                    text_sequence=None,
-                                    font_type=font_type,
-                                    font_size=font_size,
-                                    font_color=font_color,
-                                    add_progress_bar=True,
-                                    progress_bar_color=progress_bar_color,
-                                    progress_bar_height=5,
-                                    loop=0,
-                                    mp4=mp4,
-                                    fading=fading,
-                                )
-                        except:
-                            empty_text.error(
-                                "An error occurred while computing the timelapse. Your probably requested too much data. Try reducing the ROI or timespan."
-                            )
-                            st.stop()
-
-                        if out_gif is not None and os.path.exists(out_gif):
-
-                            empty_text.text(
-                                "Right click the GIF to save it to your computer👇"
-                            )
-                            empty_image.image(out_gif)
-
-                            out_mp4 = out_gif.replace(".gif", ".mp4")
-                            if mp4 and os.path.exists(out_mp4):
-                                with empty_video:
-                                    st.text(
-                                        "Right click the MP4 to save it to your computer👇"
-                                    )
-                                    st.video(out_gif.replace(".gif", ".mp4"))
-
-                        else:
-                            empty_text.error(
-                                "Something went wrong. You probably requested too much data. Try reducing the ROI or timespan."
-                            )
-
-        elif collection == "Geostationary Operational Environmental Satellites (GOES)":
-
-            video_empty.video("https://youtu.be/16fA2QORG4A")
-
-            with st.form("submit_goes_form"):
-
-                roi = None
-                if st.session_state.get("roi") is not None:
-                    roi = st.session_state.get("roi")
-                out_gif = geemap.temp_file_path(".gif")
-
-                satellite = st.selectbox("Select a satellite:", ["GOES-17", "GOES-16"])
-                earliest_date = datetime.date(2017, 7, 10)
-                latest_date = datetime.date.today()
-
-                if sample_roi == "Uploaded GeoJSON":
-                    roi_start_date = today - datetime.timedelta(days=2)
-                    roi_end_date = today - datetime.timedelta(days=1)
-                    roi_start_time = datetime.time(14, 00)
-                    roi_end_time = datetime.time(1, 00)
-                else:
-                    roi_start = goes_rois[sample_roi]["start_time"]
-                    roi_end = goes_rois[sample_roi]["end_time"]
-                    roi_start_date = datetime.datetime.strptime(
-                        roi_start[:10], "%Y-%m-%d"
-                    )
-                    roi_end_date = datetime.datetime.strptime(roi_end[:10], "%Y-%m-%d")
-                    roi_start_time = datetime.time(
-                        int(roi_start[11:13]), int(roi_start[14:16])
-                    )
-                    roi_end_time = datetime.time(
-                        int(roi_end[11:13]), int(roi_end[14:16])
-                    )
-
-                start_date = st.date_input("Select the start date:", roi_start_date)
-                end_date = st.date_input("Select the end date:", roi_end_date)
-
-                with st.expander("Customize timelapse"):
-
-                    add_fire = st.checkbox("Add Fire/Hotspot Characterization", False)
-
-                    scan_type = st.selectbox(
-                        "Select a scan type:", ["Full Disk", "CONUS", "Mesoscale"]
-                    )
-
-                    start_time = st.time_input(
-                        "Select the start time of the start date:", roi_start_time
-                    )
-
-                    end_time = st.time_input(
-                        "Select the end time of the end date:", roi_end_time
-                    )
-
-                    start = (
-                        start_date.strftime("%Y-%m-%d")
-                        + "T"
-                        + start_time.strftime("%H:%M:%S")
-                    )
-                    end = (
-                        end_date.strftime("%Y-%m-%d")
-                        + "T"
-                        + end_time.strftime("%H:%M:%S")
-                    )
-
-                    speed = st.slider("Frames per second:", 1, 30, 5)
-                    add_progress_bar = st.checkbox("Add a progress bar", True)
-                    progress_bar_color = st.color_picker(
-                        "Progress bar color:", "#0000ff"
-                    )
-                    font_size = st.slider("Font size:", 10, 50, 20)
-                    font_color = st.color_picker("Font color:", "#ffffff")
-                    fading = st.slider(
-                        "Fading duration (seconds) for each frame:", 0.0, 3.0, 0.0
-                    )
-                    mp4 = st.checkbox("Save timelapse as MP4", True)
-
-                empty_text = st.empty()
-                empty_image = st.empty()
-                empty_video = st.container()
-                empty_fire_text = st.empty()
-                empty_fire_image = st.empty()
-
-                submitted = st.form_submit_button("Submit")
-                if submitted:
-                    if sample_roi == "Uploaded GeoJSON" and data is None:
-                        empty_text.warning(
-                            "Steps to create a timelapse: Draw a rectangle on the map -> Export it as a GeoJSON -> Upload it back to the app -> Click the Submit button. Alternatively, you can select a sample ROI from the dropdown list."
-                        )
-                    else:
-                        empty_text.text("Computing... Please wait...")
-
-                        geemap.goes_timelapse(
-                            roi,
-                            out_gif,
-                            start_date=start,
-                            end_date=end,
-                            data=satellite,
-                            scan=scan_type.replace(" ", "_").lower(),
-                            dimensions=768,
-                            framesPerSecond=speed,
-                            date_format="YYYY-MM-dd HH:mm",
-                            xy=("3%", "3%"),
-                            text_sequence=None,
-                            font_type="arial.ttf",
-                            font_size=font_size,
-                            font_color=font_color,
-                            add_progress_bar=add_progress_bar,
-                            progress_bar_color=progress_bar_color,
-                            progress_bar_height=5,
-                            loop=0,
-                            overlay_data=overlay_data,
-                            overlay_color=overlay_color,
-                            overlay_width=overlay_width,
-                            overlay_opacity=overlay_opacity,
-                            mp4=mp4,
-                            fading=fading,
-                        )
-
-                        if out_gif is not None and os.path.exists(out_gif):
-                            empty_text.text(
-                                "Right click the GIF to save it to your computer👇"
-                            )
-                            empty_image.image(out_gif)
-
-                            out_mp4 = out_gif.replace(".gif", ".mp4")
-                            if mp4 and os.path.exists(out_mp4):
-                                with empty_video:
-                                    st.text(
-                                        "Right click the MP4 to save it to your computer👇"
-                                    )
-                                    st.video(out_gif.replace(".gif", ".mp4"))
-
-                            if add_fire:
-                                out_fire_gif = geemap.temp_file_path(".gif")
-                                empty_fire_text.text(
-                                    "Delineating Fire Hotspot... Please wait..."
-                                )
-                                geemap.goes_fire_timelapse(
-                                    out_fire_gif,
-                                    start_date=start,
-                                    end_date=end,
-                                    data=satellite,
-                                    scan=scan_type.replace(" ", "_").lower(),
-                                    region=roi,
-                                    dimensions=768,
-                                    framesPerSecond=speed,
-                                    date_format="YYYY-MM-dd HH:mm",
-                                    xy=("3%", "3%"),
-                                    text_sequence=None,
-                                    font_type="arial.ttf",
-                                    font_size=font_size,
-                                    font_color=font_color,
-                                    add_progress_bar=add_progress_bar,
-                                    progress_bar_color=progress_bar_color,
-                                    progress_bar_height=5,
-                                    loop=0,
-                                )
-                                if os.path.exists(out_fire_gif):
-                                    empty_fire_image.image(out_fire_gif)
-                        else:
-                            empty_text.text(
-                                "Something went wrong, either the ROI is too big or there are no data available for the specified date range. Please try a smaller ROI or different date range."
-                            )
-
-        elif collection == "MODIS Vegetation Indices (NDVI/EVI) 16-Day Global 1km":
-
-            video_empty.video("https://youtu.be/16fA2QORG4A")
-
-            satellite = st.selectbox("Select a satellite:", ["Terra", "Aqua"])
-            band = st.selectbox("Select a band:", ["NDVI", "EVI"])
-
-            with st.form("submit_modis_form"):
-
-                roi = None
-                if st.session_state.get("roi") is not None:
-                    roi = st.session_state.get("roi")
-                out_gif = geemap.temp_file_path(".gif")
-
-                with st.expander("Customize timelapse"):
-
-                    start = st.date_input(
-                        "Select a start date:", datetime.date(2000, 2, 8)
-                    )
-                    end = st.date_input("Select an end date:", datetime.date.today())
-
-                    start_date = start.strftime("%Y-%m-%d")
-                    end_date = end.strftime("%Y-%m-%d")
-
-                    speed = st.slider("Frames per second:", 1, 30, 5)
-                    add_progress_bar = st.checkbox("Add a progress bar", True)
-                    progress_bar_color = st.color_picker(
-                        "Progress bar color:", "#0000ff"
-                    )
-                    font_size = st.slider("Font size:", 10, 50, 20)
-                    font_color = st.color_picker("Font color:", "#ffffff")
-
-                    font_type = st.selectbox(
-                        "Select the font type for the title:",
-                        ["arial.ttf", "alibaba.otf"],
-                        index=0,
-                    )
-                    fading = st.slider(
-                        "Fading duration (seconds) for each frame:", 0.0, 3.0, 0.0
-                    )
-                    mp4 = st.checkbox("Save timelapse as MP4", True)
-
-                empty_text = st.empty()
-                empty_image = st.empty()
-                empty_video = st.container()
-
-                submitted = st.form_submit_button("Submit")
-                if submitted:
-                    if sample_roi == "Uploaded GeoJSON" and data is None:
-                        empty_text.warning(
-                            "Steps to create a timelapse: Draw a rectangle on the map -> Export it as a GeoJSON -> Upload it back to the app -> Click the Submit button. Alternatively, you can select a sample ROI from the dropdown list."
-                        )
-                    else:
-
-                        empty_text.text("Computing... Please wait...")
-
-                        geemap.modis_ndvi_timelapse(
-                            roi,
-                            out_gif,
-                            satellite,
-                            band,
-                            start_date,
-                            end_date,
-                            768,
-                            speed,
-                            overlay_data=overlay_data,
-                            overlay_color=overlay_color,
-                            overlay_width=overlay_width,
-                            overlay_opacity=overlay_opacity,
-                            mp4=mp4,
-                            fading=fading,
-                        )
-
-                        geemap.reduce_gif_size(out_gif)
-
-                        empty_text.text(
-                            "Right click the GIF to save it to your computer👇"
-                        )
-                        empty_image.image(out_gif)
-
-                        out_mp4 = out_gif.replace(".gif", ".mp4")
-                        if mp4 and os.path.exists(out_mp4):
-                            with empty_video:
-                                st.text(
-                                    "Right click the MP4 to save it to your computer👇"
-                                )
-                                st.video(out_gif.replace(".gif", ".mp4"))
-
-        elif collection == "Any Earth Engine ImageCollection":
-
-            with st.form("submit_ts_form"):
-                with st.expander("Customize timelapse"):
-
-                    title = st.text_input(
-                        "Enter a title to show on the timelapse: ", "Timelapse"
-                    )
-                    start_date = st.date_input(
-                        "Select the start date:", datetime.date(2020, 1, 1)
-                    )
-                    end_date = st.date_input(
-                        "Select the end date:", datetime.date.today()
-                    )
-                    frequency = st.selectbox(
-                        "Select a temporal frequency:",
-                        ["year", "quarter", "month", "day", "hour", "minute", "second"],
-                        index=0,
-                    )
-                    reducer = st.selectbox(
-                        "Select a reducer for aggregating data:",
-                        ["median", "mean", "min", "max", "sum", "variance", "stdDev"],
-                        index=0,
-                    )
-                    data_format = st.selectbox(
-                        "Select a date format to show on the timelapse:",
-                        [
-                            "YYYY-MM-dd",
-                            "YYYY",
-                            "YYMM-MM",
-                            "YYYY-MM-dd HH:mm",
-                            "YYYY-MM-dd HH:mm:ss",
-                            "HH:mm",
-                            "HH:mm:ss",
-                            "w",
-                            "M",
-                            "d",
-                            "D",
-                        ],
-                        index=0,
-                    )
-
-                    speed = st.slider("Frames per second:", 1, 30, 5)
-                    add_progress_bar = st.checkbox("Add a progress bar", True)
-                    progress_bar_color = st.color_picker(
-                        "Progress bar color:", "#0000ff"
-                    )
-                    font_size = st.slider("Font size:", 10, 50, 30)
-                    font_color = st.color_picker("Font color:", "#ffffff")
-                    font_type = st.selectbox(
-                        "Select the font type for the title:",
-                        ["arial.ttf", "alibaba.otf"],
-                        index=0,
-                    )
-                    fading = st.slider(
-                        "Fading duration (seconds) for each frame:", 0.0, 3.0, 0.0
-                    )
-                    mp4 = st.checkbox("Save timelapse as MP4", True)
-
-                empty_text = st.empty()
-                empty_image = st.empty()
-                empty_video = st.container()
-                empty_fire_image = st.empty()
-
-                roi = None
-                if st.session_state.get("roi") is not None:
-                    roi = st.session_state.get("roi")
-                out_gif = geemap.temp_file_path(".gif")
-
-                submitted = st.form_submit_button("Submit")
-                if submitted:
-
-                    if sample_roi == "Uploaded GeoJSON" and data is None:
-                        empty_text.warning(
-                            "Steps to create a timelapse: Draw a rectangle on the map -> Export it as a GeoJSON -> Upload it back to the app -> Click the Submit button. Alternatively, you can select a sample ROI from the dropdown list."
-                        )
-                    else:
-
-                        empty_text.text("Computing... Please wait...")
-                        try:
-                            geemap.create_timelapse(
-                                st.session_state.get("ee_asset_id"),
-                                start_date=start_date.strftime("%Y-%m-%d"),
-                                end_date=end_date.strftime("%Y-%m-%d"),
-                                region=roi,
-                                frequency=frequency,
-                                reducer=reducer,
-                                date_format=data_format,
-                                out_gif=out_gif,
-                                bands=st.session_state.get("bands"),
-                                palette=st.session_state.get("palette"),
-                                vis_params=st.session_state.get("vis_params"),
-                                dimensions=768,
-                                frames_per_second=speed,
-                                crs="EPSG:3857",
-                                overlay_data=overlay_data,
-                                overlay_color=overlay_color,
-                                overlay_width=overlay_width,
-                                overlay_opacity=overlay_opacity,
-                                title=title,
-                                title_xy=("2%", "90%"),
-                                add_text=True,
-                                text_xy=("2%", "2%"),
-                                text_sequence=None,
-                                font_type=font_type,
-                                font_size=font_size,
-                                font_color=font_color,
-                                add_progress_bar=add_progress_bar,
-                                progress_bar_color=progress_bar_color,
-                                progress_bar_height=5,
-                                loop=0,
-                                mp4=mp4,
-                                fading=fading,
-                            )
-                        except:
-                            empty_text.error(
-                                "An error occurred while computing the timelapse. You probably requested too much data. Try reducing the ROI or timespan."
-                            )
-
-                        empty_text.text(
-                            "Right click the GIF to save it to your computer👇"
-                        )
-                        empty_image.image(out_gif)
-
-                        out_mp4 = out_gif.replace(".gif", ".mp4")
-                        if mp4 and os.path.exists(out_mp4):
-                            with empty_video:
-                                st.text(
-                                    "Right click the MP4 to save it to your computer👇"
-                                )
-                                st.video(out_gif.replace(".gif", ".mp4"))
-
-        elif collection in [
-            "MODIS Gap filled Land Surface Temperature Daily",
-            "MODIS Ocean Color SMI",
-        ]:
-
-            with st.form("submit_ts_form"):
-                with st.expander("Customize timelapse"):
-
-                    title = st.text_input(
-                        "Enter a title to show on the timelapse: ",
-                        "Surface Temperature",
-                    )
-                    start_date = st.date_input(
-                        "Select the start date:", datetime.date(2018, 1, 1)
-                    )
-                    end_date = st.date_input(
-                        "Select the end date:", datetime.date(2020, 12, 31)
-                    )
-                    frequency = st.selectbox(
-                        "Select a temporal frequency:",
-                        ["year", "quarter", "month", "week", "day"],
-                        index=2,
-                    )
-                    reducer = st.selectbox(
-                        "Select a reducer for aggregating data:",
-                        ["median", "mean", "min", "max", "sum", "variance", "stdDev"],
-                        index=0,
-                    )
-
-                    vis_params = st.text_area(
-                        "Enter visualization parameters",
-                        "",
-                        help="Enter a string in the format of a dictionary, such as '{'min': 23, 'max': 32}'",
-                    )
-
-                    speed = st.slider("Frames per second:", 1, 30, 5)
-                    add_progress_bar = st.checkbox("Add a progress bar", True)
-                    progress_bar_color = st.color_picker(
-                        "Progress bar color:", "#0000ff"
-                    )
-                    font_size = st.slider("Font size:", 10, 50, 30)
-                    font_color = st.color_picker("Font color:", "#ffffff")
-                    font_type = st.selectbox(
-                        "Select the font type for the title:",
-                        ["arial.ttf", "alibaba.otf"],
-                        index=0,
-                    )
-                    add_colorbar = st.checkbox("Add a colorbar", True)
-                    colorbar_label = st.text_input(
-                        "Enter the colorbar label:", "Surface Temperature (°C)"
-                    )
-                    fading = st.slider(
-                        "Fading duration (seconds) for each frame:", 0.0, 3.0, 0.0
-                    )
-                    mp4 = st.checkbox("Save timelapse as MP4", True)
-
-                empty_text = st.empty()
-                empty_image = st.empty()
-                empty_video = st.container()
-
-                roi = None
-                if st.session_state.get("roi") is not None:
-                    roi = st.session_state.get("roi")
-                out_gif = geemap.temp_file_path(".gif")
-
-                submitted = st.form_submit_button("Submit")
-                if submitted:
-
-                    if sample_roi == "Uploaded GeoJSON" and data is None:
-                        empty_text.warning(
-                            "Steps to create a timelapse: Draw a rectangle on the map -> Export it as a GeoJSON -> Upload it back to the app -> Click the Submit button. Alternatively, you can select a sample ROI from the dropdown list."
-                        )
-                    else:
-
-                        empty_text.text("Computing... Please wait...")
-                        try:
-                            if (
-                                collection
-                                == "MODIS Gap filled Land Surface Temperature Daily"
-                            ):
-                                out_gif = geemap.create_timelapse(
-                                    st.session_state.get("ee_asset_id"),
-                                    start_date=start_date.strftime("%Y-%m-%d"),
-                                    end_date=end_date.strftime("%Y-%m-%d"),
-                                    region=roi,
-                                    bands=None,
-                                    frequency=frequency,
-                                    reducer=reducer,
-                                    date_format=None,
-                                    out_gif=out_gif,
-                                    palette=st.session_state.get("palette"),
-                                    vis_params=None,
-                                    dimensions=768,
-                                    frames_per_second=speed,
-                                    crs="EPSG:3857",
-                                    overlay_data=overlay_data,
-                                    overlay_color=overlay_color,
-                                    overlay_width=overlay_width,
-                                    overlay_opacity=overlay_opacity,
-                                    title=title,
-                                    title_xy=("2%", "90%"),
-                                    add_text=True,
-                                    text_xy=("2%", "2%"),
-                                    text_sequence=None,
-                                    font_type=font_type,
-                                    font_size=font_size,
-                                    font_color=font_color,
-                                    add_progress_bar=add_progress_bar,
-                                    progress_bar_color=progress_bar_color,
-                                    progress_bar_height=5,
-                                    add_colorbar=add_colorbar,
-                                    colorbar_label=colorbar_label,
-                                    loop=0,
-                                    mp4=mp4,
-                                    fading=fading,
-                                )
-                            elif collection == "MODIS Ocean Color SMI":
-                                if vis_params.startswith("{") and vis_params.endswith(
-                                    "}"
-                                ):
-                                    vis_params = eval(vis_params)
-                                else:
-                                    vis_params = None
-                                out_gif = geemap.modis_ocean_color_timelapse(
-                                    st.session_state.get("ee_asset_id"),
-                                    start_date=start_date.strftime("%Y-%m-%d"),
-                                    end_date=end_date.strftime("%Y-%m-%d"),
-                                    region=roi,
-                                    bands=st.session_state["band"],
-                                    frequency=frequency,
-                                    reducer=reducer,
-                                    date_format=None,
-                                    out_gif=out_gif,
-                                    palette=st.session_state.get("palette"),
-                                    vis_params=vis_params,
-                                    dimensions=768,
-                                    frames_per_second=speed,
-                                    crs="EPSG:3857",
-                                    overlay_data=overlay_data,
-                                    overlay_color=overlay_color,
-                                    overlay_width=overlay_width,
-                                    overlay_opacity=overlay_opacity,
-                                    title=title,
-                                    title_xy=("2%", "90%"),
-                                    add_text=True,
-                                    text_xy=("2%", "2%"),
-                                    text_sequence=None,
-                                    font_type=font_type,
-                                    font_size=font_size,
-                                    font_color=font_color,
-                                    add_progress_bar=add_progress_bar,
-                                    progress_bar_color=progress_bar_color,
-                                    progress_bar_height=5,
-                                    add_colorbar=add_colorbar,
-                                    colorbar_label=colorbar_label,
-                                    loop=0,
-                                    mp4=mp4,
-                                    fading=fading,
-                                )
-                        except:
-                            empty_text.error(
-                                "Something went wrong. You probably requested too much data. Try reducing the ROI or timespan."
-                            )
-
-                        if out_gif is not None and os.path.exists(out_gif):
-
-                            geemap.reduce_gif_size(out_gif)
-
-                            empty_text.text(
-                                "Right click the GIF to save it to your computer👇"
-                            )
-                            empty_image.image(out_gif)
-
-                            out_mp4 = out_gif.replace(".gif", ".mp4")
-                            if mp4 and os.path.exists(out_mp4):
-                                with empty_video:
-                                    st.text(
-                                        "Right click the MP4 to save it to your computer👇"
-                                    )
-                                    st.video(out_gif.replace(".gif", ".mp4"))
-
-                        else:
-                            st.error(
-                                "Something went wrong. You probably requested too much data. Try reducing the ROI or timespan."
-                            )
-
-        elif collection == "USDA National Agriculture Imagery Program (NAIP)":
-
-            with st.form("submit_naip_form"):
-                with st.expander("Customize timelapse"):
-
-                    title = st.text_input(
-                        "Enter a title to show on the timelapse: ", "NAIP Timelapse"
-                    )
-
-                    years = st.slider(
-                        "Start and end year:",
-                        2003,
-                        today.year,
-                        (2003, today.year),
-                    )
-
-                    bands = st.selectbox(
-                        "Select a band combination:", ["N/R/G", "R/G/B"], index=0
-                    )
-
-                    speed = st.slider("Frames per second:", 1, 30, 3)
-                    add_progress_bar = st.checkbox("Add a progress bar", True)
-                    progress_bar_color = st.color_picker(
-                        "Progress bar color:", "#0000ff"
-                    )
-                    font_size = st.slider("Font size:", 10, 50, 30)
-                    font_color = st.color_picker("Font color:", "#ffffff")
-                    font_type = st.selectbox(
-                        "Select the font type for the title:",
-                        ["arial.ttf", "alibaba.otf"],
-                        index=0,
-                    )
-                    fading = st.slider(
-                        "Fading duration (seconds) for each frame:", 0.0, 3.0, 0.0
-                    )
-                    mp4 = st.checkbox("Save timelapse as MP4", True)
-
-                empty_text = st.empty()
-                empty_image = st.empty()
-                empty_video = st.container()
-                empty_fire_image = st.empty()
-
-                roi = None
-                if st.session_state.get("roi") is not None:
-                    roi = st.session_state.get("roi")
-                out_gif = geemap.temp_file_path(".gif")
-
-                submitted = st.form_submit_button("Submit")
-                if submitted:
-
-                    if sample_roi == "Uploaded GeoJSON" and data is None:
-                        empty_text.warning(
-                            "Steps to create a timelapse: Draw a rectangle on the map -> Export it as a GeoJSON -> Upload it back to the app -> Click the Submit button. Alternatively, you can select a sample ROI from the dropdown list."
-                        )
-                    else:
-
-                        empty_text.text("Computing... Please wait...")
-                        try:
-                            geemap.naip_timelapse(
-                                roi,
-                                years[0],
-                                years[1],
-                                out_gif,
-                                bands=bands.split("/"),
-                                palette=st.session_state.get("palette"),
-                                vis_params=None,
-                                dimensions=768,
-                                frames_per_second=speed,
-                                crs="EPSG:3857",
-                                overlay_data=overlay_data,
-                                overlay_color=overlay_color,
-                                overlay_width=overlay_width,
-                                overlay_opacity=overlay_opacity,
-                                title=title,
-                                title_xy=("2%", "90%"),
-                                add_text=True,
-                                text_xy=("2%", "2%"),
-                                text_sequence=None,
-                                font_type=font_type,
-                                font_size=font_size,
-                                font_color=font_color,
-                                add_progress_bar=add_progress_bar,
-                                progress_bar_color=progress_bar_color,
-                                progress_bar_height=5,
-                                loop=0,
-                                mp4=mp4,
-                                fading=fading,
-                            )
-                        except:
-                            empty_text.error(
-                                "Something went wrong. You either requested too much data or the ROI is outside the U.S."
-                            )
-
-                        if out_gif is not None and os.path.exists(out_gif):
-
-                            empty_text.text(
-                                "Right click the GIF to save it to your computer👇"
-                            )
-                            empty_image.image(out_gif)
-
-                            out_mp4 = out_gif.replace(".gif", ".mp4")
-                            if mp4 and os.path.exists(out_mp4):
-                                with empty_video:
-                                    st.text(
-                                        "Right click the MP4 to save it to your computer👇"
-                                    )
-                                    st.video(out_gif.replace(".gif", ".mp4"))
-
-                        else:
-                            st.error(
-                                "Something went wrong. You either requested too much data or the ROI is outside the U.S."
-                            )
-
-
-try:
-    app()
-except Exception as e:
-    pass

pages/2_🏠_U.S._Housing.py

@@ -1,482 +0,0 @@
-import datetime
-import os
-import pathlib
-import requests
-import zipfile
-import pandas as pd
-import pydeck as pdk
-import geopandas as gpd
-import streamlit as st
-import leafmap.colormaps as cm
-from leafmap.common import hex_to_rgb
-
-st.set_page_config(layout="wide")
-
-st.sidebar.info(
-    """
-    - Web App URL: <https://streamlit.gishub.org>
-    - GitHub repository: <https://github.com/giswqs/streamlit-geospatial>
-    """
-)
-
-st.sidebar.title("Contact")
-st.sidebar.info(
-    """
-    Qiusheng Wu at [wetlands.io](https://wetlands.io) | [GitHub](https://github.com/giswqs) | [Twitter](https://twitter.com/giswqs) | [YouTube](https://www.youtube.com/c/QiushengWu) | [LinkedIn](https://www.linkedin.com/in/qiushengwu)
-    """
-)
-
-STREAMLIT_STATIC_PATH = pathlib.Path(st.__path__[0]) / "static"
-# We create a downloads directory within the streamlit static asset directory
-# and we write output files to it
-DOWNLOADS_PATH = STREAMLIT_STATIC_PATH / "downloads"
-if not DOWNLOADS_PATH.is_dir():
-    DOWNLOADS_PATH.mkdir()
-
-# Data source: https://www.realtor.com/research/data/
-# link_prefix = "https://econdata.s3-us-west-2.amazonaws.com/Reports/"
-link_prefix = "https://raw.githubusercontent.com/giswqs/data/main/housing/"
-
-data_links = {
-    "weekly": {
-        "national": link_prefix + "Core/listing_weekly_core_aggregate_by_country.csv",
-        "metro": link_prefix + "Core/listing_weekly_core_aggregate_by_metro.csv",
-    },
-    "monthly_current": {
-        "national": link_prefix + "Core/RDC_Inventory_Core_Metrics_Country.csv",
-        "state": link_prefix + "Core/RDC_Inventory_Core_Metrics_State.csv",
-        "metro": link_prefix + "Core/RDC_Inventory_Core_Metrics_Metro.csv",
-        "county": link_prefix + "Core/RDC_Inventory_Core_Metrics_County.csv",
-        "zip": link_prefix + "Core/RDC_Inventory_Core_Metrics_Zip.csv",
-    },
-    "monthly_historical": {
-        "national": link_prefix + "Core/RDC_Inventory_Core_Metrics_Country_History.csv",
-        "state": link_prefix + "Core/RDC_Inventory_Core_Metrics_State_History.csv",
-        "metro": link_prefix + "Core/RDC_Inventory_Core_Metrics_Metro_History.csv",
-        "county": link_prefix + "Core/RDC_Inventory_Core_Metrics_County_History.csv",
-        "zip": link_prefix + "Core/RDC_Inventory_Core_Metrics_Zip_History.csv",
-    },
-    "hotness": {
-        "metro": link_prefix
-        + "Hotness/RDC_Inventory_Hotness_Metrics_Metro_History.csv",
-        "county": link_prefix
-        + "Hotness/RDC_Inventory_Hotness_Metrics_County_History.csv",
-        "zip": link_prefix + "Hotness/RDC_Inventory_Hotness_Metrics_Zip_History.csv",
-    },
-}
-
-
-def get_data_columns(df, category, frequency="monthly"):
-    if frequency == "monthly":
-        if category.lower() == "county":
-            del_cols = ["month_date_yyyymm", "county_fips", "county_name"]
-        elif category.lower() == "state":
-            del_cols = ["month_date_yyyymm", "state", "state_id"]
-        elif category.lower() == "national":
-            del_cols = ["month_date_yyyymm", "country"]
-        elif category.lower() == "metro":
-            del_cols = ["month_date_yyyymm", "cbsa_code", "cbsa_title", "HouseholdRank"]
-        elif category.lower() == "zip":
-            del_cols = ["month_date_yyyymm", "postal_code", "zip_name", "flag"]
-    elif frequency == "weekly":
-        if category.lower() == "national":
-            del_cols = ["week_end_date", "geo_country"]
-        elif category.lower() == "metro":
-            del_cols = ["week_end_date", "cbsa_code", "cbsa_title", "hh_rank"]
-
-    cols = df.columns.values.tolist()
-
-    for col in cols:
-        if col.strip() in del_cols:
-            cols.remove(col)
-    if category.lower() == "metro":
-        return cols[2:]
-    else:
-        return cols[1:]
-
-
-@st.cache(allow_output_mutation=True)
-def get_inventory_data(url):
-    df = pd.read_csv(url)
-    url = url.lower()
-    if "county" in url:
-        df["county_fips"] = df["county_fips"].map(str)
-        df["county_fips"] = df["county_fips"].str.zfill(5)
-    elif "state" in url:
-        df["STUSPS"] = df["state_id"].str.upper()
-    elif "metro" in url:
-        df["cbsa_code"] = df["cbsa_code"].map(str)
-    elif "zip" in url:
-        df["postal_code"] = df["postal_code"].map(str)
-        df["postal_code"] = df["postal_code"].str.zfill(5)
-
-    if "listing_weekly_core_aggregate_by_country" in url:
-        columns = get_data_columns(df, "national", "weekly")
-        for column in columns:
-            if column != "median_days_on_market_by_day_yy":
-                df[column] = df[column].str.rstrip("%").astype(float) / 100
-    if "listing_weekly_core_aggregate_by_metro" in url:
-        columns = get_data_columns(df, "metro", "weekly")
-        for column in columns:
-            if column != "median_days_on_market_by_day_yy":
-                df[column] = df[column].str.rstrip("%").astype(float) / 100
-        df["cbsa_code"] = df["cbsa_code"].str[:5]
-    return df
-
-
-def filter_weekly_inventory(df, week):
-    df = df[df["week_end_date"] == week]
-    return df
-
-
-def get_start_end_year(df):
-    start_year = int(str(df["month_date_yyyymm"].min())[:4])
-    end_year = int(str(df["month_date_yyyymm"].max())[:4])
-    return start_year, end_year
-
-
-def get_periods(df):
-    return [str(d) for d in list(set(df["month_date_yyyymm"].tolist()))]
-
-
-@st.cache(allow_output_mutation=True)
-def get_geom_data(category):
-
-    prefix = (
-        "https://raw.githubusercontent.com/giswqs/streamlit-geospatial/master/data/"
-    )
-    links = {
-        "national": prefix + "us_nation.geojson",
-        "state": prefix + "us_states.geojson",
-        "county": prefix + "us_counties.geojson",
-        "metro": prefix + "us_metro_areas.geojson",
-        "zip": "https://www2.census.gov/geo/tiger/GENZ2018/shp/cb_2018_us_zcta510_500k.zip",
-    }
-
-    if category.lower() == "zip":
-        r = requests.get(links[category])
-        out_zip = os.path.join(DOWNLOADS_PATH, "cb_2018_us_zcta510_500k.zip")
-        with open(out_zip, "wb") as code:
-            code.write(r.content)
-        zip_ref = zipfile.ZipFile(out_zip, "r")
-        zip_ref.extractall(DOWNLOADS_PATH)
-        gdf = gpd.read_file(out_zip.replace("zip", "shp"))
-    else:
-        gdf = gpd.read_file(links[category])
-    return gdf
-
-
-def join_attributes(gdf, df, category):
-
-    new_gdf = None
-    if category == "county":
-        new_gdf = gdf.merge(df, left_on="GEOID", right_on="county_fips", how="outer")
-    elif category == "state":
-        new_gdf = gdf.merge(df, left_on="STUSPS", right_on="STUSPS", how="outer")
-    elif category == "national":
-        if "geo_country" in df.columns.values.tolist():
-            df["country"] = None
-            df.loc[0, "country"] = "United States"
-        new_gdf = gdf.merge(df, left_on="NAME", right_on="country", how="outer")
-    elif category == "metro":
-        new_gdf = gdf.merge(df, left_on="CBSAFP", right_on="cbsa_code", how="outer")
-    elif category == "zip":
-        new_gdf = gdf.merge(df, left_on="GEOID10", right_on="postal_code", how="outer")
-    return new_gdf
-
-
-def select_non_null(gdf, col_name):
-    new_gdf = gdf[~gdf[col_name].isna()]
-    return new_gdf
-
-
-def select_null(gdf, col_name):
-    new_gdf = gdf[gdf[col_name].isna()]
-    return new_gdf
-
-
-def get_data_dict(name):
-    in_csv = os.path.join(os.getcwd(), "data/realtor_data_dict.csv")
-    df = pd.read_csv(in_csv)
-    label = list(df[df["Name"] == name]["Label"])[0]
-    desc = list(df[df["Name"] == name]["Description"])[0]
-    return label, desc
-
-
-def get_weeks(df):
-    seq = list(set(df[~df["week_end_date"].isnull()]["week_end_date"].tolist()))
-    weeks = [
-        datetime.date(int(d.split("/")[2]), int(d.split("/")[0]), int(d.split("/")[1]))
-        for d in seq
-    ]
-    weeks.sort()
-    return weeks
-
-
-def get_saturday(in_date):
-    idx = (in_date.weekday() + 1) % 7
-    sat = in_date + datetime.timedelta(6 - idx)
-    return sat
-
-
-def app():
-
-    st.title("U.S. Real Estate Data and Market Trends")
-    st.markdown(
-        """**Introduction:** This interactive dashboard is designed for visualizing U.S. real estate data and market trends at multiple levels (i.e., national,
-         state, county, and metro). The data sources include [Real Estate Data](https://www.realtor.com/research/data) from realtor.com and 
-         [Cartographic Boundary Files](https://www.census.gov/geographies/mapping-files/time-series/geo/carto-boundary-file.html) from U.S. Census Bureau.
-         Several open-source packages are used to process the data and generate the visualizations, e.g., [streamlit](https://streamlit.io),
-          [geopandas](https://geopandas.org), [leafmap](https://leafmap.org), and [pydeck](https://deckgl.readthedocs.io).
-    """
-    )
-
-    with st.expander("See a demo"):
-        st.image("https://i.imgur.com/Z3dk6Tr.gif")
-
-    row1_col1, row1_col2, row1_col3, row1_col4, row1_col5 = st.columns(
-        [0.6, 0.8, 0.6, 1.4, 2]
-    )
-    with row1_col1:
-        frequency = st.selectbox("Monthly/weekly data", ["Monthly", "Weekly"])
-    with row1_col2:
-        types = ["Current month data", "Historical data"]
-        if frequency == "Weekly":
-            types.remove("Current month data")
-        cur_hist = st.selectbox(
-            "Current/historical data",
-            types,
-        )
-    with row1_col3:
-        if frequency == "Monthly":
-            scale = st.selectbox(
-                "Scale", ["National", "State", "Metro", "County"], index=3
-            )
-        else:
-            scale = st.selectbox("Scale", ["National", "Metro"], index=1)
-
-    gdf = get_geom_data(scale.lower())
-
-    if frequency == "Weekly":
-        inventory_df = get_inventory_data(data_links["weekly"][scale.lower()])
-        weeks = get_weeks(inventory_df)
-        with row1_col1:
-            selected_date = st.date_input("Select a date", value=weeks[-1])
-            saturday = get_saturday(selected_date)
-            selected_period = saturday.strftime("%-m/%-d/%Y")
-            if saturday not in weeks:
-                st.error(
-                    "The selected date is not available in the data. Please select a date between {} and {}".format(
-                        weeks[0], weeks[-1]
-                    )
-                )
-                selected_period = weeks[-1].strftime("%-m/%-d/%Y")
-        inventory_df = get_inventory_data(data_links["weekly"][scale.lower()])
-        inventory_df = filter_weekly_inventory(inventory_df, selected_period)
-
-    if frequency == "Monthly":
-        if cur_hist == "Current month data":
-            inventory_df = get_inventory_data(
-                data_links["monthly_current"][scale.lower()]
-            )
-            selected_period = get_periods(inventory_df)[0]
-        else:
-            with row1_col2:
-                inventory_df = get_inventory_data(
-                    data_links["monthly_historical"][scale.lower()]
-                )
-                start_year, end_year = get_start_end_year(inventory_df)
-                periods = get_periods(inventory_df)
-                with st.expander("Select year and month", True):
-                    selected_year = st.slider(
-                        "Year",
-                        start_year,
-                        end_year,
-                        value=start_year,
-                        step=1,
-                    )
-                    selected_month = st.slider(
-                        "Month",
-                        min_value=1,
-                        max_value=12,
-                        value=int(periods[0][-2:]),
-                        step=1,
-                    )
-                selected_period = str(selected_year) + str(selected_month).zfill(2)
-                if selected_period not in periods:
-                    st.error("Data not available for selected year and month")
-                    selected_period = periods[0]
-                inventory_df = inventory_df[
-                    inventory_df["month_date_yyyymm"] == int(selected_period)
-                ]
-
-    data_cols = get_data_columns(inventory_df, scale.lower(), frequency.lower())
-
-    with row1_col4:
-        selected_col = st.selectbox("Attribute", data_cols)
-    with row1_col5:
-        show_desc = st.checkbox("Show attribute description")
-        if show_desc:
-            try:
-                label, desc = get_data_dict(selected_col.strip())
-                markdown = f"""
-                **{label}**: {desc}
-                """
-                st.markdown(markdown)
-            except:
-                st.warning("No description available for selected attribute")
-
-    row2_col1, row2_col2, row2_col3, row2_col4, row2_col5, row2_col6 = st.columns(
-        [0.6, 0.68, 0.7, 0.7, 1.5, 0.8]
-    )
-
-    palettes = cm.list_colormaps()
-    with row2_col1:
-        palette = st.selectbox("Color palette", palettes, index=palettes.index("Blues"))
-    with row2_col2:
-        n_colors = st.slider("Number of colors", min_value=2, max_value=20, value=8)
-    with row2_col3:
-        show_nodata = st.checkbox("Show nodata areas", value=True)
-    with row2_col4:
-        show_3d = st.checkbox("Show 3D view", value=False)
-    with row2_col5:
-        if show_3d:
-            elev_scale = st.slider(
-                "Elevation scale", min_value=1, max_value=1000000, value=1, step=10
-            )
-            with row2_col6:
-                st.info("Press Ctrl and move the left mouse button.")
-        else:
-            elev_scale = 1
-
-    gdf = join_attributes(gdf, inventory_df, scale.lower())
-    gdf_null = select_null(gdf, selected_col)
-    gdf = select_non_null(gdf, selected_col)
-    gdf = gdf.sort_values(by=selected_col, ascending=True)
-
-    colors = cm.get_palette(palette, n_colors)
-    colors = [hex_to_rgb(c) for c in colors]
-
-    for i, ind in enumerate(gdf.index):
-        index = int(i / (len(gdf) / len(colors)))
-        if index >= len(colors):
-            index = len(colors) - 1
-        gdf.loc[ind, "R"] = colors[index][0]
-        gdf.loc[ind, "G"] = colors[index][1]
-        gdf.loc[ind, "B"] = colors[index][2]
-
-    initial_view_state = pdk.ViewState(
-        latitude=40,
-        longitude=-100,
-        zoom=3,
-        max_zoom=16,
-        pitch=0,
-        bearing=0,
-        height=900,
-        width=None,
-    )
-
-    min_value = gdf[selected_col].min()
-    max_value = gdf[selected_col].max()
-    color = "color"
-    # color_exp = f"[({selected_col}-{min_value})/({max_value}-{min_value})*255, 0, 0]"
-    color_exp = f"[R, G, B]"
-
-    geojson = pdk.Layer(
-        "GeoJsonLayer",
-        gdf,
-        pickable=True,
-        opacity=0.5,
-        stroked=True,
-        filled=True,
-        extruded=show_3d,
-        wireframe=True,
-        get_elevation=f"{selected_col}",
-        elevation_scale=elev_scale,
-        # get_fill_color="color",
-        get_fill_color=color_exp,
-        get_line_color=[0, 0, 0],
-        get_line_width=2,
-        line_width_min_pixels=1,
-    )
-
-    geojson_null = pdk.Layer(
-        "GeoJsonLayer",
-        gdf_null,
-        pickable=True,
-        opacity=0.2,
-        stroked=True,
-        filled=True,
-        extruded=False,
-        wireframe=True,
-        # get_elevation="properties.ALAND/100000",
-        # get_fill_color="color",
-        get_fill_color=[200, 200, 200],
-        get_line_color=[0, 0, 0],
-        get_line_width=2,
-        line_width_min_pixels=1,
-    )
-
-    # tooltip = {"text": "Name: {NAME}"}
-
-    # tooltip_value = f"<b>Value:</b> {median_listing_price}""
-    tooltip = {
-        "html": "<b>Name:</b> {NAME}<br><b>Value:</b> {"
-        + selected_col
-        + "}<br><b>Date:</b> "
-        + selected_period
-        + "",
-        "style": {"backgroundColor": "steelblue", "color": "white"},
-    }
-
-    layers = [geojson]
-    if show_nodata:
-        layers.append(geojson_null)
-
-    r = pdk.Deck(
-        layers=layers,
-        initial_view_state=initial_view_state,
-        map_style="light",
-        tooltip=tooltip,
-    )
-
-    row3_col1, row3_col2 = st.columns([6, 1])
-
-    with row3_col1:
-        st.pydeck_chart(r)
-    with row3_col2:
-        st.write(
-            cm.create_colormap(
-                palette,
-                label=selected_col.replace("_", " ").title(),
-                width=0.2,
-                height=3,
-                orientation="vertical",
-                vmin=min_value,
-                vmax=max_value,
-                font_size=10,
-            )
-        )
-    row4_col1, row4_col2, row4_col3 = st.columns([1, 2, 3])
-    with row4_col1:
-        show_data = st.checkbox("Show raw data")
-    with row4_col2:
-        show_cols = st.multiselect("Select columns", data_cols)
-    with row4_col3:
-        show_colormaps = st.checkbox("Preview all color palettes")
-        if show_colormaps:
-            st.write(cm.plot_colormaps(return_fig=True))
-    if show_data:
-        if scale == "National":
-            st.dataframe(gdf[["NAME", "GEOID"] + show_cols])
-        elif scale == "State":
-            st.dataframe(gdf[["NAME", "STUSPS"] + show_cols])
-        elif scale == "County":
-            st.dataframe(gdf[["NAME", "STATEFP", "COUNTYFP"] + show_cols])
-        elif scale == "Metro":
-            st.dataframe(gdf[["NAME", "CBSAFP"] + show_cols])
-        elif scale == "Zip":
-            st.dataframe(gdf[["GEOID10"] + show_cols])
-
-
-app()

pages/{4_🔥_Heatmap.py → 2_🔥_Heatmap.py}

@@ -5,15 +5,15 @@ st.set_page_config(layout="wide")
 
 st.sidebar.info(
     """
-    - Web App URL: <https://streamlit.gishub.org>
-    - GitHub repository: <https://github.com/giswqs/streamlit-geospatial>
+    - Web App URL: <https://huggingface.co/spaces/yunusserhat/Crime-Map>
+    - HuggingFace repository: <https://huggingface.co/spaces/yunusserhat/Crime-Map/tree/main>
     """
 )
 
 st.sidebar.title("Contact")
 st.sidebar.info(
     """
-    Qiusheng Wu at [wetlands.io](https://wetlands.io) | [GitHub](https://github.com/giswqs) | [Twitter](https://twitter.com/giswqs) | [YouTube](https://www.youtube.com/c/QiushengWu) | [LinkedIn](https://www.linkedin.com/in/qiushengwu)
+    Yunus Serhat Bıçakçı at [yunusserhat.com](https://yunusserhat.com) | [GitHub](https://github.com/yunusserhat) | [Twitter](https://twitter.com/yunusserhat) | [LinkedIn](https://www.linkedin.com/in/yunusserhat)
     """
 )
 
@@ -21,10 +21,10 @@ st.title("Heatmap")
 
 with st.expander("See source code"):
     with st.echo():
-        filepath = "https://raw.githubusercontent.com/giswqs/leafmap/master/examples/data/us_cities.csv"
-        m = leafmap.Map(center=[40, -100], zoom=4, tiles="stamentoner")
+        tweets = "https://raw.githubusercontent.com/giswqs/leafmap/master/examples/data/us_cities.csv"
+        m = leafmap.Map(center=[51.50, -0.1], zoom=10, tiles="stamentoner")
         m.add_heatmap(
-            filepath,
+            tweets,
             latitude="latitude",
             longitude="longitude",
             value="pop_max",

pages/3_🪟_Split_Map.py

@@ -1,30 +0,0 @@
-import streamlit as st
-import leafmap.foliumap as leafmap
-
-st.set_page_config(layout="wide")
-
-st.sidebar.info(
-    """
-    - Web App URL: <https://streamlit.gishub.org>
-    - GitHub repository: <https://github.com/giswqs/streamlit-geospatial>
-    """
-)
-
-st.sidebar.title("Contact")
-st.sidebar.info(
-    """
-    Qiusheng Wu at [wetlands.io](https://wetlands.io) | [GitHub](https://github.com/giswqs) | [Twitter](https://twitter.com/giswqs) | [YouTube](https://www.youtube.com/c/QiushengWu) | [LinkedIn](https://www.linkedin.com/in/qiushengwu)
-    """
-)
-
-st.title("Split-panel Map")
-
-with st.expander("See source code"):
-    with st.echo():
-        m = leafmap.Map()
-        m.split_map(
-            left_layer='ESA WorldCover 2020 S2 FCC', right_layer='ESA WorldCover 2020'
-        )
-        m.add_legend(title='ESA Land Cover', builtin_legend='ESA_WorldCover')
-
-m.to_streamlit(height=700)

pages/6_🗺️_Basemaps.py

@@ -1,63 +0,0 @@
-import streamlit as st
-import leafmap.foliumap as leafmap
-
-st.set_page_config(layout="wide")
-
-st.sidebar.info(
-    """
-    - Web App URL: <https://streamlit.gishub.org>
-    - GitHub repository: <https://github.com/giswqs/streamlit-geospatial>
-    """
-)
-
-st.sidebar.title("Contact")
-st.sidebar.info(
-    """
-    Qiusheng Wu at [wetlands.io](https://wetlands.io) | [GitHub](https://github.com/giswqs) | [Twitter](https://twitter.com/giswqs) | [YouTube](https://www.youtube.com/c/QiushengWu) | [LinkedIn](https://www.linkedin.com/in/qiushengwu)
-    """
-)
-
-
-def app():
-    st.title("Search Basemaps")
-    st.markdown(
-        """
-    This app is a demonstration of searching and loading basemaps from [xyzservices](https://github.com/geopandas/xyzservices) and [Quick Map Services (QMS)](https://github.com/nextgis/quickmapservices). Selecting from 1000+ basemaps with a few clicks.  
-    """
-    )
-
-    with st.expander("See demo"):
-        st.image("https://i.imgur.com/0SkUhZh.gif")
-
-    row1_col1, row1_col2 = st.columns([3, 1])
-    width = 800
-    height = 600
-    tiles = None
-
-    with row1_col2:
-
-        checkbox = st.checkbox("Search Quick Map Services (QMS)")
-        keyword = st.text_input("Enter a keyword to search and press Enter:")
-        empty = st.empty()
-
-        if keyword:
-            options = leafmap.search_xyz_services(keyword=keyword)
-            if checkbox:
-                qms = leafmap.search_qms(keyword=keyword)
-                if qms is not None:
-                    options = options + qms
-
-            tiles = empty.multiselect(
-                "Select XYZ tiles to add to the map:", options)
-
-        with row1_col1:
-            m = leafmap.Map()
-
-            if tiles is not None:
-                for tile in tiles:
-                    m.add_xyz_service(tile)
-
-            m.to_streamlit(height=height)
-
-
-app()

pages/7_📦_Web_Map_Service.py

@@ -1,87 +0,0 @@
-import ast
-import streamlit as st
-import leafmap.foliumap as leafmap
-
-st.set_page_config(layout="wide")
-
-st.sidebar.info(
-    """
-    - Web App URL: <https://streamlit.gishub.org>
-    - GitHub repository: <https://github.com/giswqs/streamlit-geospatial>
-    """
-)
-
-st.sidebar.title("Contact")
-st.sidebar.info(
-    """
-    Qiusheng Wu at [wetlands.io](https://wetlands.io) | [GitHub](https://github.com/giswqs) | [Twitter](https://twitter.com/giswqs) | [YouTube](https://www.youtube.com/c/QiushengWu) | [LinkedIn](https://www.linkedin.com/in/qiushengwu)
-    """
-)
-
-
-@st.cache(allow_output_mutation=True)
-def get_layers(url):
-    options = leafmap.get_wms_layers(url)
-    return options
-
-
-def app():
-    st.title("Web Map Service (WMS)")
-    st.markdown(
-        """
-    This app is a demonstration of loading Web Map Service (WMS) layers. Simply enter the URL of the WMS service 
-    in the text box below and press Enter to retrieve the layers. Go to https://apps.nationalmap.gov/services to find 
-    some WMS URLs if needed.
-    """
-    )
-
-    row1_col1, row1_col2 = st.columns([3, 1.3])
-    width = 800
-    height = 600
-    layers = None
-
-    with row1_col2:
-
-        esa_landcover = "https://services.terrascope.be/wms/v2"
-        url = st.text_input(
-            "Enter a WMS URL:", value="https://services.terrascope.be/wms/v2"
-        )
-        empty = st.empty()
-
-        if url:
-            options = get_layers(url)
-
-            default = None
-            if url == esa_landcover:
-                default = "WORLDCOVER_2020_MAP"
-            layers = empty.multiselect(
-                "Select WMS layers to add to the map:", options, default=default
-            )
-            add_legend = st.checkbox("Add a legend to the map", value=True)
-            if default == "WORLDCOVER_2020_MAP":
-                legend = str(leafmap.builtin_legends["ESA_WorldCover"])
-            else:
-                legend = ""
-            if add_legend:
-                legend_text = st.text_area(
-                    "Enter a legend as a dictionary {label: color}",
-                    value=legend,
-                    height=200,
-                )
-
-        with row1_col1:
-            m = leafmap.Map(center=(36.3, 0), zoom=2)
-
-            if layers is not None:
-                for layer in layers:
-                    m.add_wms_layer(
-                        url, layers=layer, name=layer, attribution=" ", transparent=True
-                    )
-            if add_legend and legend_text:
-                legend_dict = ast.literal_eval(legend_text)
-                m.add_legend(legend_dict=legend_dict)
-
-            m.to_streamlit(height=height)
-
-
-app()

pages/8_🏜️_Raster_Data_Visualization.py

@@ -1,106 +0,0 @@
-import os
-import leafmap.foliumap as leafmap
-import leafmap.colormaps as cm
-import streamlit as st
-
-st.set_page_config(layout="wide")
-
-st.sidebar.info(
-    """
-    - Web App URL: <https://streamlit.gishub.org>
-    - GitHub repository: <https://github.com/giswqs/streamlit-geospatial>
-    """
-)
-
-st.sidebar.title("Contact")
-st.sidebar.info(
-    """
-    Qiusheng Wu at [wetlands.io](https://wetlands.io) | [GitHub](https://github.com/giswqs) | [Twitter](https://twitter.com/giswqs) | [YouTube](https://www.youtube.com/c/QiushengWu) | [LinkedIn](https://www.linkedin.com/in/qiushengwu)
-    """
-)
-
-
-@st.cache(allow_output_mutation=True)
-def load_cog_list():
-    print(os.getcwd())
-    in_txt = os.path.join(os.getcwd(), "data/cog_files.txt")
-    with open(in_txt) as f:
-        return [line.strip() for line in f.readlines()[1:]]
-
-
-@st.cache(allow_output_mutation=True)
-def get_palettes():
-    return list(cm.palettes.keys())
-    # palettes = dir(palettable.matplotlib)[:-16]
-    # return ["matplotlib." + p for p in palettes]
-
-
-st.title("Visualize Raster Datasets")
-st.markdown(
-    """
-An interactive web app for visualizing local raster datasets and Cloud Optimized GeoTIFF ([COG](https://www.cogeo.org)). The app was built using [streamlit](https://streamlit.io), [leafmap](https://leafmap.org), and [Titiler](https://developmentseed.org/titiler/).
-
-
-"""
-)
-
-row1_col1, row1_col2 = st.columns([2, 1])
-
-with row1_col1:
-    cog_list = load_cog_list()
-    cog = st.selectbox("Select a sample Cloud Opitmized GeoTIFF (COG)", cog_list)
-
-with row1_col2:
-    empty = st.empty()
-
-    url = empty.text_input(
-        "Enter a HTTP URL to a Cloud Optimized GeoTIFF (COG)",
-        cog,
-    )
-
-    if url:
-        try:
-            options = leafmap.cog_bands(url)
-        except Exception as e:
-            st.error(e)
-        if len(options) > 3:
-            default = options[:3]
-        else:
-            default = options[0]
-        bands = st.multiselect("Select bands to display", options, default=options)
-
-        if len(bands) == 1 or len(bands) == 3:
-            pass
-        else:
-            st.error("Please select one or three bands")
-
-    add_params = st.checkbox("Add visualization parameters")
-    if add_params:
-        vis_params = st.text_area("Enter visualization parameters", "{}")
-    else:
-        vis_params = {}
-
-    if len(vis_params) > 0:
-        try:
-            vis_params = eval(vis_params)
-        except Exception as e:
-            st.error(
-                f"Invalid visualization parameters. It should be a dictionary. Error: {e}"
-            )
-            vis_params = {}
-
-    submit = st.button("Submit")
-
-m = leafmap.Map(latlon_control=False)
-
-if submit:
-    if url:
-        try:
-            m.add_cog_layer(url, bands=bands, **vis_params)
-        except Exception as e:
-            with row1_col2:
-                st.error(e)
-                st.error("Work in progress. Try it again later.")
-
-with row1_col1:
-    m.to_streamlit()

pages/9_🔲_Vector_Data_Visualization.py

@@ -1,117 +0,0 @@
-import os
-import fiona
-import geopandas as gpd
-import streamlit as st
-
-st.set_page_config(layout="wide")
-
-st.sidebar.info(
-    """
-    - Web App URL: <https://streamlit.gishub.org>
-    - GitHub repository: <https://github.com/giswqs/streamlit-geospatial>
-    """
-)
-
-st.sidebar.title("Contact")
-st.sidebar.info(
-    """
-    Qiusheng Wu at [wetlands.io](https://wetlands.io) | [GitHub](https://github.com/giswqs) | [Twitter](https://twitter.com/giswqs) | [YouTube](https://www.youtube.com/c/QiushengWu) | [LinkedIn](https://www.linkedin.com/in/qiushengwu)
-    """
-)
-
-
-def save_uploaded_file(file_content, file_name):
-    """
-    Save the uploaded file to a temporary directory
-    """
-    import tempfile
-    import os
-    import uuid
-
-    _, file_extension = os.path.splitext(file_name)
-    file_id = str(uuid.uuid4())
-    file_path = os.path.join(tempfile.gettempdir(), f"{file_id}{file_extension}")
-
-    with open(file_path, "wb") as file:
-        file.write(file_content.getbuffer())
-
-    return file_path
-
-
-def app():
-
-    st.title("Upload Vector Data")
-
-    row1_col1, row1_col2 = st.columns([2, 1])
-    width = 950
-    height = 600
-
-    with row1_col2:
-
-        backend = st.selectbox(
-            "Select a plotting backend", ["folium", "kepler.gl", "pydeck"], index=2
-        )
-
-        if backend == "folium":
-            import leafmap.foliumap as leafmap
-        elif backend == "kepler.gl":
-            import leafmap.kepler as leafmap
-        elif backend == "pydeck":
-            import leafmap.deck as leafmap
-
-        url = st.text_input(
-            "Enter a URL to a vector dataset",
-            "https://github.com/giswqs/streamlit-geospatial/raw/master/data/us_states.geojson",
-        )
-
-        data = st.file_uploader(
-            "Upload a vector dataset", type=["geojson", "kml", "zip", "tab"]
-        )
-
-        container = st.container()
-
-        if data or url:
-            if data:
-                file_path = save_uploaded_file(data, data.name)
-                layer_name = os.path.splitext(data.name)[0]
-            elif url:
-                file_path = url
-                layer_name = url.split("/")[-1].split(".")[0]
-
-            with row1_col1:
-                if file_path.lower().endswith(".kml"):
-                    fiona.drvsupport.supported_drivers["KML"] = "rw"
-                    gdf = gpd.read_file(file_path, driver="KML")
-                else:
-                    gdf = gpd.read_file(file_path)
-                lon, lat = leafmap.gdf_centroid(gdf)
-                if backend == "pydeck":
-
-                    column_names = gdf.columns.values.tolist()
-                    random_column = None
-                    with container:
-                        random_color = st.checkbox("Apply random colors", True)
-                        if random_color:
-                            random_column = st.selectbox(
-                                "Select a column to apply random colors", column_names
-                            )
-
-                    m = leafmap.Map(center=(lat, lon))
-                    m.add_gdf(gdf, random_color_column=random_column)
-                    st.pydeck_chart(m)
-
-                else:
-                    m = leafmap.Map(center=(lat, lon), draw_export=True)
-                    m.add_gdf(gdf, layer_name=layer_name)
-                    # m.add_vector(file_path, layer_name=layer_name)
-                    if backend == "folium":
-                        m.zoom_to_gdf(gdf)
-                    m.to_streamlit(width=width, height=height)
-
-        else:
-            with row1_col1:
-                m = leafmap.Map()
-                st.pydeck_chart(m)
-
-
-app()