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| # -*- coding: utf-8 -*- | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, | |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License. | |
| import leafmap.foliumap as leafmap | |
| import streamlit as st | |
| import altair as alt | |
| import ibis | |
| from ibis import _ | |
| import ibis.selectors as s | |
| st.set_page_config(layout="wide", page_title="Protected Areas Explorer", page_icon=":globe:") | |
| #pad_pmtiles = "https://data.source.coop/cboettig/pad-us-3/pad-stats.pmtiles" | |
| #parquet = "https://data.source.coop/cboettig/pad-us-3/pad-stats.parquet" | |
| #pad_pmtiles = "https://huggingface.co/spaces/boettiger-lab/pad-us/resolve/main/pad-stats.pmtiles" | |
| #parquet = "https://huggingface.co/spaces/boettiger-lab/pad-us/resolve/main/pad-stats.parquet" | |
| pad_pmtiles = "https://huggingface.co/datasets/boettiger-lab/pad-us-3/resolve/main/pad-stats.pmtiles" | |
| parquet = "https://huggingface.co/datasets/boettiger-lab/pad-us-3/resolve/main/pad-stats.parquet" | |
| # some default color variables, consider user palette via st.color_picker() | |
| private_color = "#DE881E" # orange #"#850101" # red | |
| tribal_color = "#BF40BF" # purple | |
| mixed_color = "#005a00" # green | |
| public_color = "#3388ff" # blue | |
| # default color breaks, consider tool via st.slider() | |
| low = 2 | |
| high = 3 | |
| alpha = .5 | |
| style_choice = "Manager Type" | |
| us_lower_48_area_m2 = 7.8e+12 | |
| ## Helper functions | |
| #@st.cache_resource | |
| def ibis_connection(parquet): | |
| return ibis.read_parquet(parquet) | |
| pad_data = ibis_connection(parquet) | |
| #@st.cache_data() | |
| def summary_table(column, colors): | |
| df = (pad_data | |
| .rename(area = "area_square_meters") | |
| .group_by(_[column]) | |
| .aggregate(hectares_protected = (_.area.sum() / 10000).round(), | |
| percent_protected = 100 * _.area.sum() / us_lower_48_area_m2, | |
| mean_richness = (_.richness * _.area).sum() / _.area.sum(), | |
| mean_rsr = (_.rsr * _.area).sum() / _.area.sum(), | |
| carbon_lost = (_.deforest_carbon * _.area).sum() / _.area.sum(), | |
| crop_expansion = (_.crop_expansion * _.area).sum() / _.area.sum(), | |
| human_impact = (_.human_impact * _.area).sum() / _.area.sum(), | |
| ) | |
| .mutate(percent_protected = _.percent_protected.round(1)) | |
| .inner_join(colors, column) | |
| ) | |
| df = df.to_pandas() | |
| df[column] = df[column].astype(str) | |
| return df | |
| def bar_chart(df, x, y): | |
| chart = alt.Chart(df).mark_bar().encode( | |
| x=x, | |
| y=y, | |
| color=alt.Color('color').scale(None) | |
| ).properties(width="container", height=300) | |
| return chart | |
| def area_plot(df, column): | |
| base = alt.Chart(df).encode( | |
| alt.Theta("percent_protected:Q").stack(True), | |
| ) | |
| pie = ( base | |
| .mark_arc(innerRadius= 40, outerRadius=70) | |
| .encode(alt.Color("color:N").scale(None).legend(None), | |
| tooltip=['percent_protected', 'hectares_protected', column]) | |
| ) | |
| text = ( base | |
| .mark_text(radius=60, size=12, color="white") | |
| .encode(text = column + ":N") | |
| ) | |
| plot = pie # pie + text | |
| return plot.properties(width=180, height=180) | |
| def pad_style(paint, alpha): | |
| return { | |
| "version": 8, | |
| "sources": { | |
| "pad": { | |
| "type": "vector", | |
| "url": "pmtiles://" + pad_pmtiles, | |
| "attribution": "US PAD v3"}}, | |
| "layers": [{ | |
| "id": "public", | |
| "source": "pad", | |
| "source-layer": "pad-stats", | |
| "type": "fill", | |
| "paint": { | |
| "fill-color": paint, | |
| "fill-opacity": alpha | |
| } | |
| }]} | |
| ''' | |
| # US Protected Area Database Explorer | |
| ''' | |
| m = leafmap.Map(center=[35, -100], zoom=4, layers_control=True) | |
| custom_style = ''' | |
| "blue" | |
| ''' | |
| sample_q = '''( | |
| ibis.read_parquet(parquet). | |
| mutate(area = _.area_square_meters). | |
| group_by(_.gap_code). | |
| aggregate(percent_protected = 100 * _.area.sum() / us_lower_48_area_m2, | |
| mean_richness = (_.richness * _.area).sum() / _.area.sum(), | |
| mean_rsr = (_.rsr * _.area).sum() / _.area.sum() | |
| ). | |
| mutate(percent_protected = _.percent_protected.round()) | |
| ) | |
| ''' | |
| ## Protected Area polygon color codes | |
| manager = { | |
| 'property': 'manager_type', | |
| 'type': 'categorical', | |
| 'stops': [ | |
| ['Federal', "darkblue"], | |
| ['State', public_color], | |
| ['Local Government', "lightblue"], | |
| ['Regional Agency Special District', "darkgreen"], | |
| ['Unknown', "grey"], | |
| ['Joint', "green"], | |
| ['American Indian Lands', tribal_color], | |
| ['Private', "darkred"], | |
| ['Non-Governmental Organization', "orange"] | |
| ] | |
| } | |
| easement = { | |
| 'property': 'category', | |
| 'type': 'categorical', | |
| 'stops': [ | |
| ['Fee', public_color], | |
| ['Easement', private_color], | |
| ['Proclamation', tribal_color] | |
| ] | |
| } | |
| access = { | |
| 'property': 'public_access', | |
| 'type': 'categorical', | |
| 'stops': [ | |
| ['Open Access', public_color], | |
| ['Closed', private_color], | |
| ['Unknown', "grey"], | |
| ['Restricted Access', tribal_color] | |
| ] | |
| } | |
| gap = { | |
| 'property': 'gap_code', | |
| 'type': 'categorical', | |
| 'stops': [ | |
| ["1", "#26633d"], | |
| ["2", "#879647"], | |
| ["3", "#BBBBBB"], | |
| ["4", "#F8F8F8"] | |
| ] | |
| } | |
| iucn = { | |
| 'property': 'iucn_category', | |
| 'type': 'categorical', | |
| 'stops': [ | |
| ["Ia: Strict nature reserves", "#4B0082"], | |
| ["Ib: Wilderness areas", "#663399"], | |
| ["II: National park", "#7B68EE"], | |
| ["III: Natural monument or feature", "#9370DB"], | |
| ["IV: Habitat / species management", "#8A2BE2"], | |
| ["V: Protected landscape / seascape", "#9932CC"], | |
| ["VI: Protected area with sustainable use of natural resources", "#9400D3"], | |
| ["Other Conservation Area", "#DDA0DD"], | |
| ["Unassigned", "#F8F8F8"], | |
| ] | |
| } | |
| style_options = { | |
| "GAP Status Code": gap, | |
| "IUCN Status Code": iucn, | |
| "Manager Type": manager, | |
| "Fee/Easement": easement, | |
| "Public Access": access, | |
| # "Mean Richness": richness, | |
| # "Mean RSR": rsr, | |
| # "custom": eval(custom) | |
| } | |
| code_ex=''' | |
| m.add_cog_layer("https://data.source.coop/vizzuality/lg-land-carbon-data/natcrop_expansion_100m_cog.tif", | |
| palette="oranges", name="Cropland Expansion", transparent_bg=True, opacity = 0.7, zoom_to_layer=False) | |
| ''' | |
| justice40 = "https://data.source.coop/cboettig/justice40/disadvantaged-communities.pmtiles" | |
| justice40_fill = { | |
| 'property': 'Disadvan', | |
| 'type': 'categorical', | |
| 'stops': [ | |
| [0, "rgba(255, 255, 255, 0)"], | |
| [1, "rgba(0, 0, 139, 1)"]]} | |
| justice40_style = { | |
| "version": 8, | |
| "sources": { | |
| "source1": { | |
| "type": "vector", | |
| "url": "pmtiles://" + justice40, | |
| "attribution": "Justice40"} | |
| }, | |
| "layers": [{ | |
| "id": "layer1", | |
| "source": "source1", | |
| "source-layer": "DisadvantagedCommunitiesCEJST", | |
| "type": "fill", | |
| "paint": {"fill-color": justice40_fill, "fill-opacity": 0.6}}] | |
| } | |
| # + | |
| ## Map controls sidebar | |
| with st.sidebar: | |
| if st.toggle("Protected Areas", True): | |
| style_choice = st.radio("Color by:", style_options) | |
| alpha = st.slider("transparency", 0.0, 1.0, 0.5) | |
| style = pad_style(style_options[style_choice], alpha) | |
| m.add_pmtiles(pad_pmtiles, name="Protected Areas (PAD-US-3)", style=style, overlay=True, show=True, zoom_to_layer=False) | |
| ## Add legend based on selected style? | |
| # m.add_legend(legend_dict=legend_dict) | |
| with st.expander("🦜 Biodiversity"): | |
| if st.toggle("Species Richness", False): | |
| m.add_tile_layer(url="https://data.source.coop/cboettig/mobi/tiles/red/species-richness-all/{z}/{x}/{y}.png", | |
| name="MOBI Species Richness", | |
| attribution="NatureServe", | |
| opacity=0.9 | |
| ) | |
| if st.toggle("Range-Size Rarity"): | |
| m.add_tile_layer(url="https://data.source.coop/cboettig/mobi/tiles/green/range-size-rarity-all/{z}/{x}/{y}.png", | |
| name="MOBI Range-Size Rarity", | |
| attribution="NatureServe", | |
| opacity=0.9 | |
| ) | |
| #m.add_cog_layer("https://data.source.coop/cboettig/mobi/range-size-rarity-all/RSR_All.tif", | |
| # palette="greens", name="Range-Size Rarity", transparent_bg=True, opacity = 0.9, zoom_to_layer=False) | |
| with st.expander("⛅ Carbon & Climate"): | |
| if st.toggle("Carbon Lost (2002-2022)"): | |
| m.add_cog_layer("https://data.source.coop/vizzuality/lg-land-carbon-data/deforest_carbon_100m_cog.tif", | |
| palette="reds", name="Carbon Lost (2002-2022)", transparent_bg=True, opacity = 0.8, zoom_to_layer=False) | |
| if st.toggle("Irrecoverable Carbon"): | |
| m.add_cog_layer("https://data.source.coop/cboettig/carbon/cogs/irrecoverable_c_total_2018.tif", | |
| palette="purples", name="Irrecoverable Carbon", transparent_bg=True, opacity = 0.8, zoom_to_layer=False) | |
| if st.toggle("Manageable Carbon"): | |
| m.add_cog_layer("https://data.source.coop/cboettig/carbon/cogs/manageable_c_total_2018.tif", | |
| palette="greens", name="Manageable Carbon", transparent_bg=True, opacity = 0.8, zoom_to_layer=False) | |
| with st.expander("🚜 Human Impacts"): | |
| if st.toggle("Human Impact"): | |
| hi="https://data.source.coop/vizzuality/hfp-100/hfp_2021_100m_v1-2_cog.tif" | |
| m.add_cog_layer(hi, palette="purples", name="Human Impact", transparent_bg=True, opacity = 0.8, zoom_to_layer=False) | |
| if st.toggle("cropland expansion"): | |
| m.add_cog_layer("https://data.source.coop/vizzuality/lg-land-carbon-data/natcrop_expansion_100m_cog.tif", | |
| palette="greens", name="cropland expansion", transparent_bg=True, opacity = 0.8, zoom_to_layer=False) | |
| if st.toggle("Biodiversity Intactness Loss"): | |
| m.add_cog_layer("https://data.source.coop/vizzuality/lg-land-carbon-data/natcrop_bii_100m_cog.tif", | |
| palette="reds", name="biodiversity intactness loss", transparent_bg=True, opacity = 0.8, zoom_to_layer=False) | |
| if st.toggle("Forest Integrity Loss"): | |
| m.add_cog_layer("https://data.source.coop/vizzuality/lg-land-carbon-data/natcrop_fii_100m_cog.tif", | |
| palette="reds", name="forest integrity loss", transparent_bg=True, opacity = 0.8, zoom_to_layer=False) | |
| with st.expander("⚖ Equity and Justice"): | |
| if st.toggle("Climate & Economic Justice"): | |
| m.add_pmtiles(justice40, name="Climate & Economic Justice", style = justice40_style, overlay=True, show=True, zoom_to_layer=False) | |
| with st.expander("🔥 Wildfire"): | |
| # Fire Polygons, USGS | |
| if st.toggle("Fire boundaries"): | |
| usgs = "https://data.source.coop/cboettig/fire/usgs-mtbs.pmtiles" | |
| fire_style = { | |
| "version": 8, | |
| "sources": { | |
| "source1": { | |
| "type": "vector", | |
| "url": "pmtiles://" + usgs, | |
| "attribution": "USGS"}}, | |
| "layers": [{ | |
| "id": "usgs", | |
| "source": "source1", | |
| "source-layer": "mtbs_perims_DD", | |
| "type": "fill", | |
| "paint": {"fill-color": "#FFA500", "fill-opacity": 0.4}}]} | |
| m.add_pmtiles(usgs, name="Fire", style=fire_style, overlay=True, show=True, zoom_to_layer=False) | |
| with st.expander("💻 Custom code"): | |
| if st.toggle("Custom map layers"): | |
| code = st.text_area(label = "leafmap code:", | |
| value = code_ex, | |
| height = 100) | |
| eval(compile(code, "<string>", "exec")) | |
| # "## Boundaries" | |
| # boundaries = st.radio("Boundaries:", | |
| # ["None", | |
| # "State Boundaries", | |
| # "County Boundaries", | |
| # "Congressional District", | |
| # "custom"] | |
| # ) | |
| with st.expander("🗺 Basemaps"): | |
| # radio selector would make more sense | |
| if st.toggle("Topography"): | |
| m.add_basemap("Esri.WorldShadedRelief") | |
| if st.toggle("Satellite"): | |
| m.add_basemap("Esri.WorldImagery") | |
| # Map radio buttons to corresponding column: | |
| select_column = { | |
| "GAP Status Code": "gap_code", | |
| "IUCN Status Code": "iucn_category", | |
| "Manager Type": "manager_type", | |
| "Fee/Easement": "category", | |
| "Public Access": "public_access", | |
| "Mean Richness": "gap_code", | |
| "Mean RSR": "gap_code", | |
| "custom": "gap_code"} | |
| column = select_column[style_choice] | |
| # Map radio buttons to corresponding color-scheme: | |
| select_colors = { | |
| "GAP Status Code": gap["stops"], | |
| "IUCN Status Code": iucn["stops"], | |
| "Manager Type": manager["stops"], | |
| "Fee/Easement": easement["stops"], | |
| "Public Access": access["stops"], | |
| "Mean Richness": gap["stops"], | |
| "Mean RSR": gap["stops"], | |
| "custom": gap["stops"]} | |
| colors = (ibis | |
| .memtable(select_colors[style_choice], columns = [column, "color"]) | |
| .to_pandas() | |
| ) | |
| main = st.container() | |
| with main: | |
| map_col, stats_col = st.columns([2,1]) | |
| with map_col: | |
| m.to_streamlit(height=700) | |
| df = summary_table(column, colors) | |
| total_percent = df.percent_protected.sum() | |
| richness_chart = bar_chart(df, column, 'mean_richness') | |
| rsr_chart = bar_chart(df, column, 'mean_rsr') | |
| carbon_lost = bar_chart(df, column, 'carbon_lost') | |
| crop_expansion = bar_chart(df, column, 'crop_expansion') | |
| human_impact = bar_chart(df, column, 'human_impact') | |
| with stats_col: | |
| with st.container(): | |
| col1, col2, col3 = st.columns(3) | |
| with col1: | |
| f"{total_percent}% Continental US Covered" | |
| st.altair_chart(area_plot(df, column), use_container_width=False) | |
| with col2: | |
| "Species Richness" | |
| st.altair_chart(richness_chart, use_container_width=True) | |
| with col3: | |
| "Range-Size Rarity" | |
| st.altair_chart(rsr_chart, use_container_width=True) | |
| with st.container(): | |
| col1b, col2b, col3b = st.columns(3) | |
| with col1b: | |
| "Carbon Lost ('02-'22)" | |
| st.altair_chart(carbon_lost, use_container_width=True) | |
| with col2b: | |
| "Crop expansion" | |
| st.altair_chart(crop_expansion, use_container_width=True) | |
| with col3b: | |
| "Human Impact" | |
| st.altair_chart(human_impact, use_container_width=True) | |
| st.divider() | |
| footer = st.container() | |
| with footer: | |
| ''' | |
| ## Custom queries | |
| Input custom python code below to interactively explore the data. | |
| ''' | |
| col2_1, col2_2 = st.columns(2) | |
| with col2_1: | |
| query = st.text_area( | |
| label = "Python code:", | |
| value = sample_q, | |
| height = 300) | |
| with col2_2: | |
| "Output table:" | |
| df = eval(query) | |
| st.write(df.to_pandas()) | |
| st.divider() | |
| ''' | |
| ## Credits | |
| Author: Carl Boettiger, UC Berkeley | |
| License: BSD-2-clause | |
| ### Data sources | |
| - US Protected Areas Database v3 by USGS. Data: https://beta.source.coop/cboettig/us-pad-3. Citation: https://doi.org/10.5066/P9Q9LQ4B, License: Public Domain | |
| - Imperiled Species Richness and Range-Size-Rarity from NatureServe (2022). Data: https://beta.source.coop/repositories/cboettig/mobi. License CC-BY-NC-ND | |
| - Carbon-loss and farming impact by Vizzuality, on https://beta.source.coop/repositories/vizzuality/lg-land-carbon-data. Citation: https://doi.org/10.1101/2023.11.01.565036, License: CC-BY | |
| - Human Footprint by Vizzuality, on https://beta.source.coop/repositories/vizzuality/hfp-100. Citation: https://doi.org/10.3389/frsen.2023.1130896, License: Public Domain | |
| - Fire polygons by USGS, reprocessed to PMTiles on https://beta.source.coop/cboettig/fire/. License: Public Domain | |
| - Irrecoverable Carbon from Conservation International, reprocessed to COG on https://beta.source.coop/cboettig/carbon, citation: https://doi.org/10.1038/s41893-021-00803-6, License: CC-BY-NC | |
| - Climate and Economic Justice Screening Tool, US Council on Environmental Quality, Justice40, data: https://beta.source.coop/repositories/cboettig/justice40/description/, License: Public Domain | |
| ### Software | |
| Proudly built with a free and Open Source software stack: Streamlit (reactive application), HuggingFace (application hosting), Source.Coop (data hosting), | |
| using cloud-native data serializations in COG, PMTiles, and GeoParquet. Coded in pure python using leafmap and duckdb. Map styling with [MapLibre](https://maplibre.org/). | |
| ''' | |