wip - app with new data, need to fix pmtiles

app/app.py

@@ -40,10 +40,8 @@ ca = con.table("mydata")
 
 for key in [
     'richness', 'rsr', 'irrecoverable_carbon', 'manageable_carbon',
-    'percent_fire_10yr', 'percent_rxburn_10yr', 'percent_disadvantaged',
-    'svi', 'svi_socioeconomic_status', 'svi_household_char',
-    'svi_racial_ethnic_minority', 'svi_housing_transit',
-    'deforest_carbon', 'human_impact'
+    'fire', 'rxburn', 'disadvantaged_communities',
+    'svi'
 ]:
     if key not in st.session_state:
         st.session_state[key] = False
@@ -85,7 +83,7 @@ st.markdown(
         }
         .block-container {
             padding-top: 0.5rem;
-            padding-bottom: 0rem;
+            padding-bottom: 2rem;
             padding-left: 5rem;
             padding-right: 5rem;
         }
@@ -108,6 +106,7 @@ st.markdown(
     unsafe_allow_html=True,
 )
 
+
 st.markdown(
     """
     <style>
@@ -229,10 +228,8 @@ def summary_table_sql(ca, column, colors, ids): # get df for charts + df_tab for
 
 chatbot_toggles = {key: False for key in [
     'richness', 'rsr', 'irrecoverable_carbon', 'manageable_carbon',
-    'percent_fire_10yr', 'percent_rxburn_10yr', 'percent_disadvantaged',
-    'svi', 'svi_socioeconomic_status', 'svi_household_char',
-    'svi_racial_ethnic_minority', 'svi_housing_transit',
-    'deforest_carbon', 'human_impact'
+    'fire', 'rxburn', 'disadvantaged_communities',
+    'svi'
 ]}
 
 
@@ -303,7 +300,6 @@ with st.container():
             st.stop()
 
 
-
 #### Data layers 
 with st.sidebar:  
     st.markdown('<p class = "medium-font-sidebar"> Data Layers:</p>', help = "Select data layers to visualize on the map. Summary charts will update based on the displayed layers.", unsafe_allow_html= True)
@@ -335,7 +331,7 @@ with st.sidebar:
     # Justice40 Section 
     with st.expander("🌱 Climate & Economic Justice"):
         a_justice = st.slider("transparency", 0.0, 1.0, 0.07, key = "social justice")
-        show_justice40 = st.toggle("Disadvantaged Communities (Justice40)", key = "percent_disadvantaged", value=chatbot_toggles['percent_disadvantaged'])
+        show_justice40 = st.toggle("Disadvantaged Communities (Justice40)", key = "disadvantaged_communities", value=chatbot_toggles['disadvantaged_communities'])
    
         if show_justice40:
             m.add_pmtiles(url_justice40, style=justice40_style, name="Justice40", opacity=a_justice, tooltip=False, fit_bounds = False)
@@ -344,58 +340,30 @@ with st.sidebar:
     with st.expander("🏡 Social Vulnerability"):
         a_svi = st.slider("transparency", 0.0, 1.0, 0.1, key = "SVI")
         show_sv = st.toggle("Social Vulnerability Index (SVI)", key = "svi", value=chatbot_toggles['svi'])
-        show_sv_socio = st.toggle("Socioeconomic Status", key = "svi_socioeconomic_status", value=chatbot_toggles['svi_socioeconomic_status'])
-        show_sv_household = st.toggle("Household Characteristics", key = "svi_household_char", value=chatbot_toggles['svi_household_char'])
-        show_sv_minority = st.toggle("Racial & Ethnic Minority Status", key = "svi_racial_ethnic_minority", value=chatbot_toggles['svi_racial_ethnic_minority'])
-        show_sv_housing = st.toggle("Housing Type & Transportation", key = "svi_housing_transit", value=chatbot_toggles['svi_housing_transit'])
-        
+
         if show_sv:
             m.add_pmtiles(url_svi, style = get_sv_style("RPL_THEMES"), opacity=a_svi, tooltip=False, fit_bounds = False)
         
-        if show_sv_socio:
-            m.add_pmtiles(url_svi, style = get_sv_style("RPL_THEME1"), opacity=a_svi, tooltip=False, fit_bounds = False)
-        
-        if show_sv_household:
-            m.add_pmtiles(url_svi, style = get_sv_style("RPL_THEME2"), opacity=a_svi, tooltip=False, fit_bounds = False)
-        
-        if show_sv_minority:
-            m.add_pmtiles(url_svi, style = get_sv_style("RPL_THEME3"), opacity=a_svi, tooltip=False, fit_bounds = False)
-        
-        if show_sv_housing:
-            m.add_pmtiles(url_svi, style = get_sv_style("RPL_THEME4"), opacity=a_svi, tooltip=False, fit_bounds = False)
-
     # Fire Section
     with st.expander("🔥 Fire"):
-        a_fire = st.slider("transparency", 0.0, 1.0, 0.15, key = "fire")
-        show_fire_10 = st.toggle("Fires (2013-2022)", key = "percent_fire_10yr", value=chatbot_toggles['percent_fire_10yr'])
+        a_fire = st.slider("transparency", 0.0, 1.0, 0.15, key = "calfire")
+        show_fire_10 = st.toggle("Fires (2013-2023)", key = "fire", value=chatbot_toggles['fire'])
 
-        show_rx_10 = st.toggle("Prescribed Burns (2013-2022)", key = "percent_rxburn_10yr", value=chatbot_toggles['percent_rxburn_10yr'])
+        show_rx_10 = st.toggle("Prescribed Burns (2013-2023)", key = "rxburn", value=chatbot_toggles['rxburn'])
 
 
         if show_fire_10:
-            m.add_pmtiles(url_calfire, style=fire_style("layer2"), name="CALFIRE Fire Polygons (2013-2022)", opacity=a_fire, tooltip=False, fit_bounds = True)
+            m.add_pmtiles(url_calfire, style=fire_style("layer2"), name="CALFIRE Fire Polygons (2013-2023)", opacity=a_fire, tooltip=False, fit_bounds = True)
 
         if show_rx_10:
-            m.add_pmtiles(url_rxburn, style=rx_style("layer2"), name="CAL FIRE Prescribed Burns (2013-2022)", opacity=a_fire, tooltip=False, fit_bounds = True)
+            m.add_pmtiles(url_rxburn, style=rx_style("layer2"), name="CAL FIRE Prescribed Burns (2013-2023)", opacity=a_fire, tooltip=False, fit_bounds = True)
                     
 
-    # HI Section 
-    with st.expander("🚜 Human Impacts"):
-        a_hi = st.slider("transparency", 0.0, 1.0, 0.1, key = "hi")
-        show_carbon_lost = st.toggle("Deforested Carbon", key = "deforest_carbon", value=chatbot_toggles['deforest_carbon'])
-        show_human_impact = st.toggle("Human Footprint", key = "human_impact", value=chatbot_toggles['human_impact'])
-        
-        if show_carbon_lost:
-            m.add_tile_layer(url_loss_carbon, name="Deforested Carbon (2002-2022)", opacity = a_hi)
-        
-        if show_human_impact:
-            m.add_cog_layer(url_hi, name="Human Footprint (2017-2021)", opacity = a_hi, fit_bounds=False)
-
     st.divider()
     st.markdown('<p class = "medium-font-sidebar"> Filters:</p>', help = "Apply filters to adjust what data is shown on the map.", unsafe_allow_html= True)
     for label in style_options: # get selected filters (based on the buttons selected)
         with st.expander(label):  
-            if label == "GAP Status Code": # gap code 1 and 2 are on by default
+            if label == "GAP Code": # gap code 1 and 2 are on by default
                 opts = getButtons(style_options, label, default_gap)
             else: # other buttons are not on by default.
                 opts = getButtons(style_options, label) 
@@ -408,13 +376,14 @@ with st.sidebar:
         else: 
             filter_cols = []
             filter_vals = []
-
+            
     st.divider()
     st.markdown("""
     <p class="medium-font-sidebar">
     <svg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' class='bi bi-github ' style='height:1em;width:1em;fill:currentColor;vertical-align:-0.125em;margin-right:4px;'  aria-hidden='true' role='img'><path d='M8 0C3.58 0 0 3.58 0 8c0 3.54 2.29 6.53 5.47 7.59.4.07.55-.17.55-.38 0-.19-.01-.82-.01-1.49-2.01.37-2.53-.49-2.69-.94-.09-.23-.48-.94-.82-1.13-.28-.15-.68-.52-.01-.53.63-.01 1.08.58 1.23.82.72 1.21 1.87.87 2.33.66.07-.52.28-.87.51-1.07-1.78-.2-3.64-.89-3.64-3.95 0-.87.31-1.59.82-2.15-.08-.2-.36-1.02.08-2.12 0 0 .67-.21 2.2.82.64-.18 1.32-.27 2-.27.68 0 1.36.09 2 .27 1.53-1.04 2.2-.82 2.2-.82.44 1.1.16 1.92.08 2.12.51.56.82 1.27.82 2.15 0 3.07-1.87 3.75-3.65 3.95.29.25.54.73.54 1.48 0 1.07-.01 1.93-.01 2.2 0 .21.15.46.55.38A8.012 8.012 0 0 0 16 8c0-4.42-3.58-8-8-8z'></path></svg>Source Code: </p> <a href='https://github.com/boettiger-lab/ca-30x30' target='_blank'>https://github.com/boettiger-lab/ca-30x30</a>
     """, unsafe_allow_html=True)# adding github logo 
 
+    
 # Display CA 30x30 Data
 if 'out' not in locals():
     style = get_pmtiles_style(style_options[color_choice], alpha, filter_cols, filter_vals)
@@ -428,7 +397,9 @@ column = select_column[color_choice]
 
 select_colors = {
     "Year": year["stops"],
-    "GAP Status Code": gap["stops"],
+    "GAP Code": gap["stops"],
+    "Status": status["stops"],
+    "Ecoregion": ecoregion["stops"],
     "Manager Type": manager["stops"],
     "Easement": easement["stops"],
     "Access Type": access["stops"],
@@ -440,6 +411,7 @@ colors = (
     .to_pandas()
 )
 
+
 # get summary tables used for charts + printed table 
 # df - charts; df_tab - printed table (omits colors) 
 if 'out' not in locals():
@@ -455,16 +427,10 @@ richness_chart = bar_chart(df, column, 'mean_richness', "Species Richness")
 rsr_chart = bar_chart(df, column, 'mean_rsr', "Range-Size Rarity")
 irr_carbon_chart = bar_chart(df, column, 'mean_irrecoverable_carbon', "Irrecoverable Carbon")
 man_carbon_chart = bar_chart(df, column, 'mean_manageable_carbon', "Manageable Carbon")
-fire_10_chart = bar_chart(df, column, 'mean_percent_fire_10yr', "Fires (2013-2022)")
-rx_10_chart = bar_chart(df, column, 'mean_percent_rxburn_10yr',"Prescribed Burns (2013-2022)")
-justice40_chart = bar_chart(df, column, 'mean_percent_disadvantaged', "Disadvantaged Communities (Justice40)")
-svi_chart = bar_chart(df, column, 'mean_svi', "Social Vulnerability Index")
-svi_socio_chart = bar_chart(df, column, 'mean_svi_socioeconomic_status', "SVI - Socioeconomic Status")
-svi_house_chart = bar_chart(df, column, 'mean_svi_household_char', "SVI - Household Characteristics")
-svi_minority_chart = bar_chart(df, column, 'mean_svi_racial_ethnic_minority', "SVI - Racial and Ethnic Minority")
-svi_transit_chart = bar_chart(df, column, 'mean_svi_housing_transit', "SVI - Housing Type and Transit")
-carbon_loss_chart = bar_chart(df, column, 'mean_carbon_lost', "Deforested Carbon (2002-2022)")
-hi_chart = bar_chart(df, column, 'mean_human_impact', "Human Footprint (2017-2021)")
+fire_10_chart = bar_chart(df, column, 'mean_fire', "Fires (2013-2023)")
+rx_10_chart = bar_chart(df, column, 'mean_rxburn',"Prescribed Burns (2013-2023)")
+justice40_chart = bar_chart(df, column, 'mean_disadvantaged_communities', "Disadvantaged Communities (Justice40) ")
+svi_chart = bar_chart(df, column, 'mean_svi', "Social Vulnerability Index (2023)")
 
 
 main = st.container()
@@ -486,63 +452,30 @@ with main:
             st.altair_chart(area_plot(df, column), use_container_width=True)
                 
             if show_richness:
-                # "Species Richness"
                 st.altair_chart(richness_chart, use_container_width=True)
 
             if show_rsr:
-                # "Range-Size Rarity"
                 st.altair_chart(rsr_chart, use_container_width=True)
 
             if show_irrecoverable_carbon:
-                # "Irrecoverable Carbon"
                 st.altair_chart(irr_carbon_chart, use_container_width=True)
 
             if show_manageable_carbon:
-                # "Manageable Carbon"
                 st.altair_chart(man_carbon_chart, use_container_width=True)
 
             if show_fire_10:
-                # "Fires (2013-2022)"
                 st.altair_chart(fire_10_chart, use_container_width=True)
                 
             if show_rx_10:
-                # "Prescribed Burns (2013-2022)"
                 st.altair_chart(rx_10_chart, use_container_width=True)
 
             if show_justice40:
-                # "Disadvantaged Communities (Justice40)"
                 st.altair_chart(justice40_chart, use_container_width=True)
                 
             if show_sv:
-                # "Social Vulnerability Index"
                 st.altair_chart(svi_chart, use_container_width=True)
                 
-            if show_sv_socio:
-                # "SVI - Socioeconomic Status"
-                st.altair_chart(svi_socio_chart, use_container_width=True)
-            
-            if show_sv_household:
-                # "SVI - Household Characteristics"
-                st.altair_chart(svi_house_chart, use_container_width=True)
-            
-            if show_sv_minority:
-                # "SVI - Racial and Ethnic Minority"
-                st.altair_chart(svi_minority_chart, use_container_width=True)
-            
-            if show_sv_housing:
-                # "SVI - Housing Type and Transit"
-                st.altair_chart(svi_transit_chart, use_container_width=True)
-            
-            if show_carbon_lost:
-                # "Deforested Carbon (2002-2022)"
-                st.altair_chart(carbon_loss_chart, use_container_width=True)
-
-            if show_human_impact:
-                # "Human Footprint (2017-2021)"
-                st.altair_chart(hi_chart, use_container_width=True)
-
-
-
+ 
 
 
 st.caption("***The label 'established' is inferred from the California Protected Areas Database, which may introduce artifacts. For details on our methodology, please refer to our code: https://github.com/boettiger-lab/ca-30x30.") 

app/footer.md

@@ -11,12 +11,8 @@ Data: https://huggingface.co/datasets/boettiger-lab/ca-30x30
 
 - 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
 
-- Fire polygons by CAL FIRE (2022), reprocessed to PMTiles on https://beta.source.coop/cboettig/fire/. License: Public Domain
+- Fire polygons by CAL FIRE (2023), reprocessed to PMTiles on https://beta.source.coop/cboettig/fire/. License: Public Domain
 
-- Climate and Economic Justice Screening Tool, US Council on Environmental Quality, Justice40. Description: https://screeningtool.geoplatform.gov/en/methodology#3/33.47/-97.5. Data: https://beta.source.coop/repositories/cboettig/justice40/description/, License: Public Domain
+- Climate and Economic Justice Screening Tool, US Council on Environmental Quality, Justice40. Data: https://beta.source.coop/repositories/cboettig/justice40/description/, License: Public Domain
 
-- CDC 2020 Social Vulnerability Index by US Census Tract. Description: https://www.atsdr.cdc.gov/place-health/php/svi/index.html. Data: https://source.coop/repositories/cboettig/social-vulnerability/description. 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
+- CDC 2022 Social Vulnerability Index by US Census Tract. Description: https://www.atsdr.cdc.gov/place-health/php/svi/index.html. Data: https://source.coop/repositories/cboettig/social-vulnerability/description. License: Public Domain

app/system_prompt.txt

@@ -36,12 +36,12 @@ example_assistant: {{"sql_query":
 ## Example: 
 example_user: "Which gap code has been impacted the most by fire?"
 example_assistant: {{"sql_query":  
-    SELECT "reGAP", SUM("percent_fire_10yr") AS temp
+    SELECT "reGAP", SUM("fire") AS temp
     FROM mydata
     GROUP BY "reGAP"
     ORDER BY temp ASC
     LIMIT 1;
-"explanation":"I used the `percent_fire_10yr` column, which shows the percentage of each area burned over the past 10 years (2013–2022), summing it for each GAP code to find the one with the highest total fire impact."
+"explanation":"I used the `fire` column, which shows the percentage of each area burned over the past 10 years (2013–2022), summing it for each GAP code to find the one with the highest total fire impact."
 }}
 
 ## Example: 
@@ -70,13 +70,13 @@ example_assistant: {{"sql_query":
 ## Example: 
 example_user: "Show me the 50 most biodiverse areas found in disadvantaged communities."
 example_assistant: {{"sql_query":   
-    SELECT "id", "geom", "name", "acres", "richness", "percent_disadvantaged" FROM mydata 
-    WHERE "percent_disadvantaged" > 0
+    SELECT "id", "geom", "name", "acres", "richness", "disadvantaged_communities" FROM mydata 
+    WHERE "disadvantaged_communities" > 0
     ORDER BY "richness" DESC
     LIMIT 50;
-"explanation": "I used the `richness` column to measure biodiversity and the `percent_disadvantaged` column to identify areas located in disadvantaged communities. The `percent_disadvantaged` value is derived from the Justice40 initiative, which identifies communities burdened by systemic inequities and vulnerabilities across multiple domains, including climate resilience, energy access, health disparities, housing affordability, pollution exposure, transportation infrastructure, water quality, and workforce opportunities.
+"explanation": "I used the `richness` column to measure biodiversity and the `disadvantaged_communities` column to identify areas located in disadvantaged communities. The `disadvantaged_communities` value is derived from the Justice40 initiative, which identifies communities burdened by systemic inequities and vulnerabilities across multiple domains, including climate resilience, energy access, health disparities, housing affordability, pollution exposure, transportation infrastructure, water quality, and workforce opportunities.
 
-The results are sorted in descending order by biodiversity richness (highest biodiversity first), and only areas with a `percent_disadvantaged` value greater than 0 (indicating some portion of the area overlaps with a disadvantaged community) are included."
+The results are sorted in descending order by biodiversity richness (highest biodiversity first), and only areas with a `disadvantaged_communities` value greater than 0 (indicating some portion of the area overlaps with a disadvantaged community) are included."
 }}
 
 
@@ -90,7 +90,7 @@ sql_query:
     SELECT "id", "geom", "name", "acres","richness", "reGAP"
     FROM mydata
     WHERE "reGAP" = 3
-        AND "percent_fire_10yr" >= 0.5
+        AND "fire" >= 0.5
         and "manager_type" = "Federal"
         AND "richness" > (SELECT temp FROM temp_tab);
 
@@ -105,12 +105,11 @@ sql_query:
 
 # Detailed Explanation of the Columns in the California Dataset 
 - "established": The time range which the land was acquired, either "2024" or "pre-2024". 
-- "reGAP": The GAP status code; corresponds to the level of protection the area has. There are 4 gap codes and are defined as the following. 
-    Status 1: Permanently protected to maintain a natural state, allowing natural disturbances or mimicking them through management.
-    Status 2: Permanently protected but may allow some uses or management practices that degrade natural communities or suppress natural disturbances.
-    Status 3: Permanently protected from major land cover conversion but allows some extractive uses (e.g., logging, mining) and protects federally listed species.
-    Status 4: No protection mandates; land may be converted to unnatural habitat types or its management intent is unknown.
-
+- "reGAP": The GAP code; corresponds to the level of protection the area has. There are 4 gap codes and are defined as the following. 
+    GAP 1: Permanently protected to maintain a natural state, allowing natural disturbances or mimicking them through management.
+    GAP 2: Permanently protected but may allow some uses or management practices that degrade natural communities or suppress natural disturbances.
+    GAP 3: Permanently protected from major land cover conversion but allows some extractive uses (e.g., logging, mining) and protects federally listed species.
+    GAP 4: No protection mandates; land may be converted to unnatural habitat types or its management intent is unknown.
 - "name": The name of a protected area. The user may use a shortened name and/or not capitalize it. For example, "redwoods" may refer to "Redwood National Park", or "klamath" refers to "Klamath National Forest". Another example, "san diego wildlife refuge" could refer to multiple areas, so you would use "WHERE LOWER("name") LIKE '%san diego%' AND LOWER("name") LIKE '%wildlife%' AND LOWER("name") LIKE '%refuge%';" in your SQL query, to ensure that it is case-insensitive and matches any record that includes our phrases, because we don't want to overlook a match.  If the name isn't capitalized, you MUST ensure the search is case-insensitive by converting "name" to lowercase. 
 The names of the largest parks are {names}.
 - "access_type": Level of access to the land: "Unknown Access","Restricted Access","No Public Access" and "Open Access". 
@@ -122,17 +121,13 @@ The names of the largest parks are {names}.
 - "type": Physical type of area, either "Land" or "Water". 
 - "richness": Species richness; higher values indicate better biodiversity.
 - "rsr": Range-size rarity; higher values indicate better rarity metrics.
-- "svi": Social Vulnerability Index based on 4 themes: socioeconomic status, household characteristics, racial & ethnic minority status, and housing & transportation. Higher values indicate greater vulnerability.
-    - Themes:
-        - "svi_socioeconomic_status": Poverty, unemployment, housing cost burden, education, and health insurance.
-        - "svi_household_char": Age, disability, single-parent households, and language proficiency.
-        - "svi_racial_ethnic_minority": Race and ethnicity variables.
-        - "svi_housing_transit": Housing type, crowding, vehicles, and group quarters.
-- "percent_disadvantaged": Justice40-defined disadvantaged communities overburdened by climate, energy, health, housing, pollution, transportation, water, and workforce factors. Higher values indicate more disadvantage. Range is between 0 and 1. 
-- "deforest_carbon": Carbon emissions due to deforestation.
-- "human_impact": A score representing the human footprint: cumulative anthropogenic impacts such as land cover change, population density, and infrastructure. 
-- "percent_fire_10yr": The percentage of the area burned by fires from (2013-2022). Range is between 0 and 1. 
-- "percent_rxburn_10yr": The percentage of the area affected by prescribed burns from (2013-2022). Range is between 0 and 1. 
+- "svi": Social Vulnerability Index based on 4 themes: 1) socioeconomic status (e.g. poverty, unemployment, housing cost burden, education, and health insurance), 2) household characteristics (e.g. age, disability, single-parent households, and language proficiency), 3) racial & ethnic minority status (e.g. race and ethnicity variables), and 4) housing & transportation (housing type, crowding, vehicles, and group quarters.). Higher values indicate greater vulnerability.
+- "disadvantaged_communities": Justice40-defined disadvantaged communities overburdened by climate, energy, health, housing, pollution, transportation, water, and workforce factors. Higher values indicate more disadvantage. Range is between 0 and 1. 
+- "fire": The percentage of the area burned by fires from (2013-2022). Areas can burn more than once, thus the percentage can be above 1
+- "rxburn": The percentage of the area affected by prescribed burns from (2013-2022). Areas can be burned more than once. 
+- "status": The conservation status. GAP 1 and 2 count towards 30x30, thus are "30x30-conserved", GAP 3 and 4 land are grouped into "other-conserved", and areas outside of GAP are designed "non-conserved". 
+- "ecoregion": Ecoregions are areas with similar ecosystems and environmental resources. The ecoregions in California are: 'Sierra Nevada Foothills','Southern Cascades','Southeastern Great Basin','Southern CA Mountains and Valleys','Sonoran Desert', 'Northwestern Basin','Colorado Desert','Central Valley Coast Ranges', 'Great Valley (South)', 'Sierra Nevada','Northern CA Coast Ranges', 'Northern CA Interior Coast Ranges','Mojave Desert', 'Mono', 'Southern CA Coast', 'Modoc Plateau', 'Klamath Mountains','Northern CA Coast','Great Valley (North)', 'Central CA Coast', and 'None'. 
+
 
 Only use the following tables:
 {table_info}.

app/utils.py

@@ -26,16 +26,10 @@ def get_summary(ca, combined_filter, column, colors=None): #summary stats, based
                        mean_rsr = (_.rsr * _.acres).sum() / _.acres.sum(),
                        mean_irrecoverable_carbon = (_.irrecoverable_carbon * _.acres).sum() / _.acres.sum(),
                        mean_manageable_carbon = (_.manageable_carbon * _.acres).sum() / _.acres.sum(),
-                       mean_percent_fire_10yr = (_.percent_fire_10yr *_.acres).sum()/_.acres.sum(),
-                       mean_percent_rxburn_10yr = (_.percent_rxburn_10yr *_.acres).sum()/_.acres.sum(),
-                       mean_percent_disadvantaged =  (_.percent_disadvantaged * _.acres).sum() / _.acres.sum(),
+                       mean_fire = (_.fire *_.acres).sum()/_.acres.sum(),
+                       mean_rxburn = (_.rxburn *_.acres).sum()/_.acres.sum(),
+                       mean_disadvantaged_communities =  (_.disadvantaged_communities * _.acres).sum() / _.acres.sum(),
                        mean_svi =  (_.svi * _.acres).sum() / _.acres.sum(),
-                       mean_svi_socioeconomic_status =  (_.svi_socioeconomic_status * _.acres).sum() / _.acres.sum(),
-                       mean_svi_household_char =  (_.svi_household_char * _.acres).sum() / _.acres.sum(),
-                       mean_svi_racial_ethnic_minority =  (_.svi_racial_ethnic_minority * _.acres).sum() / _.acres.sum(),
-                       mean_svi_housing_transit =  (_.svi_housing_transit * _.acres).sum() / _.acres.sum(),
-                       mean_carbon_lost = (_.deforest_carbon * _.acres).sum() / _.acres.sum(),
-                       mean_human_impact =  (_.human_impact * _.acres).sum() / _.acres.sum(),
                       )
             .mutate(percent_protected=_.percent_protected.round(1))
          )
@@ -58,6 +52,11 @@ def summary_table(ca, column, colors, filter_cols, filter_vals,colorby_vals): #
         filter_cols.append(column)
         filters.append(getattr(_, column).isin(colorby_vals[column])) 
     combined_filter = reduce(lambda x, y: x & y, filters) #combining all the filters into ibis filter expression 
+    print(column)
+    print(combined_filter)
+    if column == "status":
+        combined_filter = (combined_filter) | (_.status.isin(['30x30-conserved','other-conserved','non-conserved']))
+    print(combined_filter)
     df = get_summary(ca, combined_filter, [column], colors) # df used for charts 
     df_tab = get_summary(ca, combined_filter, filter_cols, colors = None) #df used for printed table
     return df, df_tab 
@@ -84,9 +83,12 @@ def area_plot(df, column): #percent protected pie chart
 def bar_chart(df, x, y, title): #display summary stats for color_by column 
 
     #axis label angles / chart size
-    if x == "manager_type": #labels are too long, making vertical 
+    if x in ["manager_type", 'ecoregion','status']: #labels are too long, making vertical 
         angle = 270
         height = 373
+        if x == 'ecoregion':
+            height = 430
+
     else: #other labels are horizontal
         angle = 0
         height = 310
@@ -106,7 +108,7 @@ def bar_chart(df, x, y, title): #display summary stats for color_by column
         access_label=f"replace(datum.{x}, ' Access', '')"  #omit access from access_type labels so it fits in frame
         ).encode(
         x=alt.X("access_label:N",
-                axis=alt.Axis(labelAngle=angle, title=x_title),
+                axis=alt.Axis(labelAngle=angle, title=x_title, labelLimit = 200),
                         sort=sort),  
         y=alt.Y(y, axis=alt.Axis()), 
         color=alt.Color('color').scale(None)
@@ -219,6 +221,9 @@ def get_pmtiles_style(paint, alpha, filter_cols, filter_vals):
     for col, val in zip(filter_cols, filter_vals):
         filters.append(["match", ["get", col], val, True, False])
     combined_filters = ["all"] + filters
+    if paint['property'] == "status": #show non-conserved and other-conserved areas 
+        conserved = ['match', ['get', 'status'], ['30x30-conserved', 'other-conserved', 'non-conserved'], True, False]
+        combined_filters = ['any']+ [combined_filters] + [conserved]
     style = {
         "version": 8,
         "sources": {
@@ -231,7 +236,7 @@ def get_pmtiles_style(paint, alpha, filter_cols, filter_vals):
             {
                 "id": "ca30x30",
                 "source": "ca",
-                "source-layer": "layer",
+                "source-layer": "ca_30x30_stats",
                 "type": "fill",
                 "filter": combined_filters,
                 "paint": {
@@ -257,7 +262,7 @@ def get_pmtiles_style_llm(paint, ids):
             {
                 "id": "ca30x30",
                 "source": "ca",
-                "source-layer": "layer",
+                "source-layer": "ca_30x30_stats",
                 "type": "fill",
                 "filter": combined_filters,
                 "paint": {

app/variables.py

@@ -1,6 +1,9 @@
 # urls for main layer 
-ca_pmtiles = "https://huggingface.co/datasets/boettiger-lab/ca-30x30/resolve/main/cpad-stats.pmtiles"
-ca_parquet = "https://huggingface.co/datasets/boettiger-lab/ca-30x30/resolve/main/cpad-stats.parquet"
+# ca_pmtiles = "https://huggingface.co/datasets/boettiger-lab/ca-30x30/resolve/main/cpad-stats.pmtiles"
+# ca_parquet = "https://huggingface.co/datasets/boettiger-lab/ca-30x30/resolve/main/cpad-stats.parquet"
+
+ca_pmtiles = "https://huggingface.co/datasets/boettiger-lab/ca-30x30/resolve/main/ca_30x30_stats.pmtiles"
+ca_parquet = "https://huggingface.co/datasets/boettiger-lab/ca-30x30/resolve/main/ca_30x30_stats.parquet"
 
 ca_area_acres = 1.014e8 #acres 
 style_choice = "GAP Status Code"
@@ -13,8 +16,6 @@ url_irr_carbon = "https://huggingface.co/datasets/boettiger-lab/ca-30x30/resolve
 url_man_carbon = "https://huggingface.co/datasets/boettiger-lab/ca-30x30/resolve/main/ca_manageable_c_2018_cog.tif"
 url_svi = "https://data.source.coop/cboettig/social-vulnerability/svi2020_us_county.pmtiles"
 url_justice40 = "https://data.source.coop/cboettig/justice40/disadvantaged-communities.pmtiles"
-url_loss_carbon = "https://huggingface.co/datasets/boettiger-lab/ca-30x30/resolve/main/deforest-carbon-ca/{z}/{x}/{y}.png"
-url_hi = "https://huggingface.co/datasets/boettiger-lab/ca-30x30/resolve/main/ca_human_impact_cog.tif"
 url_calfire = "https://huggingface.co/datasets/boettiger-lab/ca-30x30/resolve/main/cal_fire_2022.pmtiles"
 url_rxburn = "https://huggingface.co/datasets/boettiger-lab/ca-30x30/resolve/main/cal_rxburn_2022.pmtiles"
 
@@ -41,6 +42,7 @@ white =  "#FFFFFF"
 
 # gap codes 3 and 4 are off by default. 
 default_gap = {
+    0: False,
     3: False,
     4: False,
 }
@@ -60,7 +62,8 @@ manager = {
         ['Joint', joint_color],
         ['Tribal', tribal_color],
         ['Private', private_color],
-        ['HOA', hoa_color]
+        ['HOA', hoa_color],
+        # ['None',white]
     ]
 }
 
@@ -69,7 +72,8 @@ easement = {
     'type': 'categorical',
     'stops': [
         ['True', private_access_color],
-        ['False', public_access_color]
+        ['False', public_access_color],
+        # ['None', white]
     ]
 }
 
@@ -78,7 +82,8 @@ year = {
     'type': 'categorical',
     'stops': [
         ['pre-2024', year2023_color],
-        ['2024', year2024_color]
+        ['2024', year2024_color],
+        # ['None',white]
     ]
 }
 
@@ -89,12 +94,14 @@ access = {
         ['Open Access', public_access_color],
         ['No Public Access', private_access_color],
         ['Unknown Access', "#bbbbbb"],
-        ['Restricted Access', tribal_color]
+        ['Restricted Access', tribal_color],
+        # ['None', white]
+
     ]
 }
 
 gap = {
-    'property': 'reGAP',
+    'property': 'gap_code',
     'type': 'categorical',
     'stops': [
         [1, "#26633d"],
@@ -104,9 +111,80 @@ gap = {
     ]
 }
 
+status = {
+    'property': 'status',
+    'type': 'categorical',
+    'stops': [
+        ['30x30-conserved', "#26633d"],
+        ['other-conserved', "#879647"],
+        ['non-conserved', "#A9A9A9"]
+    ]
+}
+
+
+# ecoregion = {
+#     'property': 'ecoregion',
+#     'type': 'categorical',
+#     'stops': [
+#         ['Sierra Nevada Foothills', "#1f77b4"],
+#         ['Southern Cascades', "#ff7f0e"],
+#         ['Southeastern Great Basin', "#2ca02c"],
+#         ['Southern California Mountains and Valleys', "#d62728"],
+#         ['Sonoran Desert', "#9467bd"],
+#         ['Northwestern Basin', "#8c564b"],
+#         ['Colorado Desert', "#e377c2"],
+#         ['Central Valley Coast Ranges', "#7f7f7f"],
+#         ['Great Valley (South)', "#bcbd22"],
+#         ['Sierra Nevada', "#17becf"],
+#         ['Northern California Coast Ranges', "#aec7e8"],
+#         ['Northern California Interior Coast Ranges', "#ffbb78"],
+#         ['Mojave Desert', "#98df8a"],
+#         ['Mono', "#ff9896"],
+#         ['Southern California Coast', "#c5b0d5"],
+#         ['Modoc Plateau', "#c49c94"],
+#         ['Klamath Mountains', "#f7b6d2"],
+#         ['Northern California Coast', "#c7c7c7"],
+#         ['Great Valley (North)', "#dbdb8d"],
+#         ['Central California Coast', "#9edae5"],
+#         ['None', "#A9A9A9"]
+#     ]
+# }
+
+ecoregion = {
+    'property': 'ecoregion',
+    'type': 'categorical',
+    'stops': [
+        ['Sierra Nevada Foothills', "#1f77b4"],
+        ['Southern Cascades', "#ff7f0e"],
+        ['Southeastern Great Basin', "#2ca02c"],
+        ['Southern CA Mountains and Valleys', "#d62728"],
+        ['Sonoran Desert', "#9467bd"],
+        ['Northwestern Basin', "#8c564b"],
+        ['Colorado Desert', "#e377c2"],
+        ['Central Valley Coast Ranges', "#7f7f7f"],
+        ['Great Valley (South)', "#bcbd22"],
+        ['Sierra Nevada', "#17becf"],
+        ['Northern CA Coast Ranges', "#aec7e8"],
+        ['Northern CA Interior Coast Ranges', "#ffbb78"],
+        ['Mojave Desert', "#98df8a"],
+        ['Mono', "#ff9896"],
+        ['Southern CA Coast', "#c5b0d5"],
+        ['Modoc Plateau', "#c49c94"],
+        ['Klamath Mountains', "#f7b6d2"],
+        ['Northern CA Coast', "#c7c7c7"],
+        ['Great Valley (North)', "#dbdb8d"],
+        ['Central CA Coast', "#9edae5"],
+        ['None', "#A9A9A9"]
+    ]
+}
+
+
+
 style_options = {
     "Year": year,
-    "GAP Status Code": gap,
+    "GAP Code": gap,
+    "Status": status,
+    "Ecoregion": ecoregion,
     "Manager Type": manager,
     "Easement": easement,
     "Access Type": access,
@@ -146,9 +224,12 @@ justice40_style = {
 
 select_column = {
     "Year": "established",
-    "GAP Status Code": "reGAP",
+    "GAP Code": "gap_code",
+    "Status":  "status",
+    "Ecoregion":  "ecoregion",
     "Manager Type": "manager_type",
     "Easement": "easement",
-    "Access Type": "access_type",
+    "Access Type": "access_type"
+
 }