WIP

app.py

@@ -35,21 +35,6 @@ st.set_page_config(layout="wide", page_title="Protected Areas Explorer", page_ic
 '''
 # US Protected Area Database Explorer
 
-The map below shows all continental US protected areas overlaid on [NatureServe's Map of Biodiversity Importance](https://www.natureserve.org/map-biodiversity-importance)
-which shows species richness for some 2,216 imperiled species in (990 m grid cells).
-Use the later tool in the top right to toggle layers on and off for visibility.
-Zoom into the map for more detailed rendering -- e.g. try exploring the many tiny public mixed used lands inside Los Angeles.
-Mouse over any polygon to see details about name, ownership, mean species richness, and mean rarity-weighted-richness.
-
-By default, areas are divided into the following categories: 
-- Publicly managed lands in Gap 1 & 2 (e.g. National Parks) ("public use", blue)
-- Publicly managed lands  in Gap 3 & 4 (most national forests, BLM lands, etc)
-- Privately managed lands
-- Tribally managed lands
-
-Alternative color rules can be applied, for instance, to distinguish between easements (rented) and fee (owned) protected areas. Below the interactive map, 
-charts summarize the total protected area and mean richness and mean RSR within each group.  
-
 '''
 # -
 
@@ -124,7 +109,7 @@ gap = {
             ['1', "#26633d"],
             ['2', "#879647"],
             ['3', "#BBBBBB"],
-            ['4', "#00000000"]
+            ['4', "#FFFFFF"]
         ]
         }
 
@@ -140,7 +125,7 @@ IUCN = {
                        ["V", "#9932CC"],
                        ["VI", "#9400D3"],
                        ["Other Conservation Area", "#DDA0DD"],
-                       ["Unassigned", "#00000000"]
+                       ["Unassigned", "#FFFFFF"]
             ]
             }
 
@@ -199,18 +184,34 @@ with st.sidebar:
     if st.toggle("Shaded Relief Topo"):
         m.add_basemap("Esri.WorldShadedRelief")
 
+    
+    "## Protected Areas"
 
-    boundaries = st.radio("Boundaries:",
-                          ["None",
-                           "State Boundaries",
-                           "County Boundaries",
-                           "Congressional District",  
-                           "custom"]
-    )
+    if st.toggle("PAD US-3", True):
+        alpha = st.slider("transparency", 0.0, 1.1, 0.5)
 
-    "## Raster layers"
-    
-    if st.toggle("Species Richness"):
+        with st.expander("custom style"):
+                custom = st.text_area(
+                label = "Define a custom mapbox fill-color rule",
+                value = custom_style, 
+                height = 100)
+
+        style_options = {
+                         "GAP Status Code": gap,
+                         "IUCN Status Code": IUCN,
+                         "Manager Type": manager,
+                         "Fee/Easement": easement,
+                         "Mean Richness": richness,
+                         "Mean RSR": rsr,
+                         "custom": eval(custom)}
+
+        style_choice = st.radio("Color protected Areas by", style_options)
+        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)
+
+
+    "## Data layers"
+    if st.toggle("Species Richness", True):
         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",
@@ -243,25 +244,18 @@ with st.sidebar:
         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)
 
-    "## Protected Areas"
     
-    style_dict = {"Manager Type": manager,
-              "Fee/Easement": easement,
-              "GAP Status Code": gap,
-              "IUCN Status Code": IUCN,
-              "Mean Richness": richness,
-              "Mean RSR": rsr,
-              "custom": eval(custom_style)}
-    
-    if st.toggle("PAD US-3", True):
-        alpha = st.slider("transparency", 0.0, 1.1, 0.5)
-        style_choice = st.radio("Color protected Areas by", style_dict)
+#    "## Boundaries"
+#    boundaries = st.radio("Boundaries:",
+#                          ["None",
+#                           "State Boundaries",
+#                           "County Boundaries",
+#                           "Congressional District",  
+#                           "custom"]
+#    )
 
-        style=pad_style(style_dict[style_choice], alpha)
-        m.add_pmtiles(pad_pmtiles, name="Protected Areas (PAD-US-3)", style=style, overlay=True, show=True, zoom_to_layer=False)
-   
    
-    
+    "## Additional elements"
     # Fire Polygons, USGS
     if st.toggle("Fire boundaries"):
         usgs = "https://data.source.coop/cboettig/fire/usgs-mtbs.pmtiles"
@@ -281,7 +275,6 @@ with st.sidebar:
         m.add_pmtiles(usgs, name="Fire", style=combined_style, overlay=True, show=True, zoom_to_layer=False)
 
 
-
 # -
 
 
@@ -298,7 +291,7 @@ with st.sidebar:
 
 # m.add_legend(legend_dict=legend_dict)
 
-m.to_streamlit(height=900)
+m.to_streamlit(height=700)
 # -
 
 st.divider()
@@ -419,44 +412,26 @@ with col2_2:
     df = eval(query)
     st.write(df.to_pandas())
 
-# -
-
-'''
-## Technical errata
-
-
-**Protected Areas** data are derived from the 
-
-> U.S. Geological Survey (USGS) Gap Analysis Project (GAP), 2022, Protected Areas Database of the United States (PAD-US) 3.0: U.S. Geological Survey data release, https://doi.org/10.5066/P9Q9LQ4B.
-
-Data is subset to the continental US (matching availability in MOBI data), and restricted to feature classes of "Fee" and "Easements",
-except for tribal boundaries which are taken from the "Proclamations."  See [ProtectedLands.net](https://www.protectedlands.net/pad-us-data-structure-attributes/)
-for a more detailed discussion of the data structure and classification involved in PAD.
 
-USGS PAD-v3 is distributed as an ESRI Geodatabase.  After subsetting the data and labelling according to the additional classification listed above based
-on manager type indicated in the data, core attributes are serialized into [PMTiles](https://docs.protomaps.com/pmtiles/) and [Geoparquet](https://geoparquet.org/)
-formats hosted on [source.coop](https://beta.source.coop/repositories/cboettig/pad-us-3/description/).  PMTiles allows for rapid rendering of vector objects
-at the appropriate zoom level in an interactive map from remote servers.  Geoparquet provides a high-performance serialization that can be efficiently queried directly from
-remote https addresses without download using software such as [duckdb](https://duckdb.org), widely available in python, R, and other languages.
+# +
 
-See our public Source.Coop repository [pad-us-3](https://beta.source.coop/repositories/cboettig/pad-us-3/description/) for more information on data processing
-and for direct access to the processed data layers.
+'''
+## Credits
 
-**Biodiversity Importance** data are derived from:
+Author: Carl Boettiger, UC Berkeley
+License: BSD-2-clause
 
-> The Map of Biodiversity Importance, (2022), NatureServe. 
+### Data sources
 
-The 2018 version of this data product can be found on Microsoft Planetary Computer, but the 2022 release is currently distributed through their [ESRI GeoHub](https://geohub-natureserve.opendata.arcgis.com/search?q=mobi).  
-The original data is provided in the geotiff format (ESRI  LayerFiles) at 990 meter resolution, and includes assets subset by various taxonomic groups for three indicators: for 2,216 imperiled species (species with global conservation status of G1, G2 or listed as threatened or endagered under the United States Ednagered Species Act).
-The indicators include species richness (the number of imperiled species occurring in a given pixel),
-range-size rarity (RSR, the sum of the inverse of the range sizes of each species occurring in a given pixel),
-and protection-weighted RSR (RSR times the perecent of the range that is unprotected in GAP 1 & Gap 2).  
-See [geohub description](https://geohub-natureserve.opendata.arcgis.com/content/e5a6de94cc7b4d5b9204e2cc5d8b6e4e/about) for more details.
-Only data from all species for the species richness and RSR metrics is processed here (at the time of writing). 
+- US Protected Areas Database v3 by USGS, data hosted on https://beta.source.coop/cboettig/us-pad-3. Citation: https://doi.org/10.5066/P9Q9LQ4B, License: Public Domain
+- Carbon-loss 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
 
-Our public Source.Coop repository [mobi](https://beta.source.coop/repositories/cboettig/mobi/) provides access
-to the geotiffs for species richness and RSR. 
-The repository also includes static tiles from zooms 1-10 that can be used as a static tile server in interactive maps.
-Technical details on processing are described in the repository.
+### 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/).
 '''
+