Spaces:
Sleeping
Sleeping
here we go
Browse files
app.py
CHANGED
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import leafmap.foliumap as leafmap
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import streamlit as st
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st.set_page_config(layout="wide", page_title="Protected Areas Explorer", page_icon=":globe:")
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richness = {
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"fill-color": [
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# ["min", ["number", ["get", "richness"]]],
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"rgb(252, 226, 220)",
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#["max", ["get", "richness"]],
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"rgb(102, 16, 66)"
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],
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"fill-opacity": 0.9
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}
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r = {
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"fill-color": [
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"rgb",
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thresholds = {
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"fill-color":
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['case',
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['<', ['get', 'richness'], low],
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red,
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['>=', ['get', 'richness'], high],
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green,
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blue # default
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],
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"fill-opacity": 0.5
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}
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bucket = {
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"fill-color":
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['case',
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['==', ['get', 'bucket'], 'public'],
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blue,
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['==', ['get', 'bucket'], 'private'],
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red,
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['==', ['get', 'bucket'], 'tribal'],
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purple,
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green # default (bucket == mixed)
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],
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"fill-opacity": 0.5
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}
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# -
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"source": "pad",
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"source-layer": "pad-mobi",
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"type": "fill",
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"paint":
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}]}
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m = leafmap.Map(center=[35, -100],
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#m.add_basemap("CartoDB.DarkMatter")
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# +
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# -
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t.group_by(_.bucket).aggregate(mean = (_.rsr * _.area).mean() / _.area.sum()).to_pandas()
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# +
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import leafmap.foliumap as leafmap
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import streamlit as st
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import altair as alt
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import ibis
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from ibis import _
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import ibis.selectors as s
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st.set_page_config(layout="wide", page_title="Protected Areas Explorer", page_icon=":globe:")
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'''
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# US Protected Area Database Explorer
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The map below shows all continental US protected areas overlaid on [NatureServe's Map of Biodiversity Importance](https://www.natureserve.org/map-biodiversity-importance)
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which shows species richness for some 2,216 imperiled species in (990 m grid cells).
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Use the later tool in the top right to toggle layers on and off for visibility.
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Zoom into the map for more detailed rendering -- e.g. try exploring the many tiny public mixed used lands inside Los Angeles.
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Mouse over any polygon to see details about name, ownership, mean species richness, and mean rarity-weighted-richness.
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By default, areas are divided into the following categories:
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- Publicly managed lands in Gap 1 & 2 (e.g. National Parks) ("public use", blue)
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- Publicly managed lands in Gap 3 & 4 (most national forests, BLM lands, etc)
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- Privately managed lands
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- Tribally managed lands
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Alternative color rules can be applied, for instance, to distinguish between easements (rented) and fee (owned) protected areas. Below the interactive map,
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charts summarize the total protected area and mean richness and mean RSR within each group.
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'''
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# -
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private_color = "#850101" # red
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tribal_color = "#BF40BF" # purple
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mixed_color = "#005a00" # green
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public_color = "#3388ff" # blue
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# +
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with st.sidebar:
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"## Map controls"
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style_choice = st.radio(
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"Color areas by",
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["management type",
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"Fee/Easement",
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"species richness (thresholds)",
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"species richness (continuous)",
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"custom"]
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)
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"### Management Types Color selector"
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public_color = st.color_picker('Color for Public Protected (Gap 1 & 2) lands', public_color)
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mixed_color = st.color_picker('Color for Public Mixed Use lands', mixed_color)
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tribal_color = st.color_picker('Color for Tribal managed lands', tribal_color)
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private_color = st.color_picker('Color for privately managed land', private_color)
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"### Threshold selector"
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low = st.slider("Red when richness is less than", 0, 30, 2)
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high = st.slider("Green for richness larger than", 0, 30, 3)
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"missing data in grey. in-between values in blue"
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"### Custom styles"
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custom = st.text_area("Define a custom mapbox fill-color rule",
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value = '''{
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"fill-color":
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['case',
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['==', ['get', 'bucket'], 'public'],
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public_color,
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['==', ['get', 'bucket'], 'private'],
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private_color,
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['==', ['get', 'bucket'], 'tribal'],
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tribal_color,
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mixed_color # default (bucket == mixed)
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],
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"fill-opacity": 0.5
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}
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''',
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height = 300
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)
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# +
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bucket = {
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"fill-color":
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['case',
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['==', ['get', 'bucket'], 'public'],
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public_color,
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['==', ['get', 'bucket'], 'private'],
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private_color,
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['==', ['get', 'bucket'], 'tribal'],
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tribal_color,
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mixed_color # default (bucket == mixed)
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],
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"fill-opacity": 0.5
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}
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easement = {
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"fill-color":
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['case',
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['==', ['get', ''], 'Fee'],
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public_color,
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['==', ['get', 'FeatClass'], 'Easement'],
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private_color,
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['==', ['get', 'FeatClass'], 'Proclamation'],
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tribal_color,
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mixed_color # default (bucket == mixed)
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],
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"fill-opacity": 0.5
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}
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thresholds = {
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"fill-color":
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['case',
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['<', ['get', 'richness'], low],
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private_color,
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['>=', ['get', 'richness'], high],
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mixed_color,
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public_color # default
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],
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"fill-opacity": 0.5
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}
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richness = {
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"fill-color": [
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# ["min", ["number", ["get", "richness"]]],
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"rgb(252, 226, 220)",
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#["max", ["get", "richness"]],
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6,
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"rgb(102, 16, 66)"
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],
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"fill-opacity": 0.9
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}
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rsr = {
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"fill-color": [
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"interpolate",
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["linear"],
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["get", "rsr"],
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0,
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# ["min", ["number", ["get", "richness"]]],
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"rgb(252, 226, 220)",
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#["max", ["get", "richness"]],
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6,
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"rgb(102, 16, 66)"
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],
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"fill-opacity": 0.9
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}
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# +
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if style_choice == "management type":
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paint_fill = bucket
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if style_choice == "Fee/Easement":
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paint_fill = easement
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if style_choice == "species richness (thresholds)":
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paint_fill = thresholds
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if style_choice == "species richness (continuous)":
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paint_fill = richness
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if style_choice == "custom":
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paint_fill = custom
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r = {
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"fill-color": [
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"rgb",
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# +
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# -
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"source": "pad",
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"source-layer": "pad-mobi",
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"type": "fill",
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"paint": paint_fill
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}]}
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m = leafmap.Map(center=[35, -100],
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zoom=4,
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layers_control=True,
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draw_control=False,
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measure_control=False,
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fullscreen_control=True)
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#m.add_basemap("CartoDB.DarkMatter")
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m.add_basemap("Esri.WorldShadedRelief")
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m.add_tile_layer(
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url="https://minio.carlboettiger.info/shared-data/mobi-tiles/red/{z}/{x}/{y}.png",
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name="MOBI",
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attribution="NatureServe",
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opacity=0.9
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)
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m.add_pmtiles(url, name="Protected Areas (PAD-US-3)", style=style, overlay=True, show=True, zoom_to_layer=False)
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m.to_streamlit(height=900)
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# -
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# +
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#parquet = "https://data.source.coop/cboettig/pad-us-3/pad-mobi.parquet"
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parquet = "https://minio.carlboettiger.info/public-biodiversity/pad-us-3/pad-mobi.parquet"
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t = ibis.read_parquet(parquet)
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# +
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us_lower_48_area_m2 = 7.8e+12
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@st.cache_data()
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def summary_table():
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x = ibis.memtable({"bucket": ["public", "tribal", "mixed", "private"],
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"color": [public_color, tribal_color, mixed_color, private_color]})
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df = (t.
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group_by(_.bucket).
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aggregate(percent_protected = 100 * _.area.sum() / us_lower_48_area_m2,
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mean_richness = (_.richness * _.area).sum() / _.area.sum(),
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mean_rsr = (_.rsr * _.area).sum() / _.area.sum()
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).
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mutate(percent_protected = _.percent_protected.round())
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).inner_join(x, "bucket")
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return df.to_pandas()
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df = summary_table()
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# st.table(richness_table)
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# +
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#summary_table.to_pandas()
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# +
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base = alt.Chart(df).encode(
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alt.Theta("percent_protected:Q").stack(True),
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alt.Color("color:N").scale(None).legend(None)
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)
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area_chart = (
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base.mark_arc(innerRadius=50, outerRadius=120) +
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base.mark_text(radius=170, size=20).encode(text="bucket") +
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base.mark_text(radius=135, size=20).encode(text="percent_protected:N")
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)
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# area_chart
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# +
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richness_chart = alt.Chart(df).mark_bar().encode(
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x='bucket',
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y='mean_richness',
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color=alt.Color('color').scale(None)
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)
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#richness_chart
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# +
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rsr_chart = alt.Chart(df).mark_bar().encode(
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x='bucket',
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y='mean_rsr',
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color=alt.Color('color').scale(None)
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)
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# -
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"## Summary Statistics"
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# +
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col1, col2, col3 = st.columns(3)
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with col1:
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st.altair_chart(area_chart, use_container_width=True)
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"Percent of Continental US Area in each group"
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# -
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with col2:
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st.altair_chart(richness_chart, use_container_width=True)
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with col3:
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338 |
+
st.altair_chart(rsr_chart, use_container_width=True)
|
339 |
+
|
340 |
|
|