app.py

# -*- 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 rioxarray
import geopandas as gpd
import streamlit as st
import altair as alt
import ibis
from ibis import _
import ibis.selectors as s
from streamlit_folium import st_folium
import json

def extract_geom(gdf, cog):
    x = (rioxarray.
         open_rasterio('/vsicurl/'+cog, masked=True).
         rio.clip(gdf.geometry.values, gdf.crs, from_disk=True)
    )
    return x

def read_polygon(polygon):
    geojson_str = json.dumps(polygon)
    gdf = gpd.read_file(geojson_str, driver='GeoJSON')
    gdf.set_crs('epsg:4326')
    return gdf

def area_hectares(gdf):
    area = gdf.to_crs("EPSG:9822").area / 10000.
    return area


# +
st.set_page_config(layout="wide", page_title="Leafmap Explorer", page_icon="⚡")

st.title("Demo Carbon Calculator")

DESCRIPTION='''
Pan and zoom to the desired location on the map. Then, use the map tools to draw a polygon (pentagon tool), bounding box (square tool) or other shape anywhere on the map.
(use esc key to exit drawing mode).  Map will display the tons of carbon lost between 2002 - 2022 below.
Data comes from Vizzuality repo on [source.coop](https://beta.source.coop/repositories/vizzuality/lg-land-carbon-data/description/).
'''

code_ex = ""

deforest = "https://data.source.coop/vizzuality/lg-land-carbon-data/deforest_carbon_100m_cog.tif"
# measured in Mg / Hct (tons)
irrecoverable = "https://data.source.coop/cboettig/carbon/cogs/irrecoverable_c_total_2018.tif"
vulnerable = "https://data.source.coop/cboettig/carbon/cogs/vulnerable_c_total_2018.tif"
manageable = "https://data.source.coop/cboettig/carbon/cogs/manageable_c_total_2018.tif"

#rsr = "https://data.source.coop/cboettig/mobi/range-size-rarity-all/RSR_All.tif"
#richness = "https://data.source.coop/cboettig/mobi/species-richness-all/SpeciesRichness_All.tif"

# Use signed data layers
#rsr = "https://data.source.coop/cboettig/mobi/range-size-rarity-all/RSR_All.tif"
#richness = "https://data.source.coop/cboettig/mobi/species-richness-all/SpeciesRichness_All.tif"



m = leafmap.Map(center=[35, -100], zoom=3)

## Map controls sidebar
with st.sidebar:
    st.markdown(DESCRIPTION)

    cog_layers = {
            "Carbon Lost, 2002-2022": deforest,
            "Vulnerable Carbon (2018)": vulnerable,
            "Manageable Carbon (2018)": manageable,
            "Irrecoverable Carbon (2018)": irrecoverable
            }

    selection = st.radio("Data", cog_layers)
    cog = cog_layers[selection]
    m.add_cog_layer(cog, palette="reds", name=selection,
                    transparent_bg=True, opacity = 0.8, 
                    zoom_to_layer=False)

    "### python code for map layer:"
    "adjust options or add additional layers using leafmap"
    code = st.text_area(
        label = "code:",
        value = code_ex, 
        height = 400)

# run whatever python code is in the python box, just for fun
eval(compile(code, "<string>", "exec"))
st_data = m.to_streamlit(height=400, bidirectional=True)

units="Tonnes"

polygon = st_data["last_active_drawing"]
# Here we actually compute the total carbon in the requested polygon
if polygon is not None:
    gdf = read_polygon(polygon)
    x = extract_geom(gdf, cog).fillna(0)    
    count = x.count()
    area = round(float(area_hectares(gdf)))
    carbon_total = round(float(x.mean()) * area) # no, mean does not include zeros
    col1, col2, col3 = st.columns(3)
    col1.metric(label=f"{selection}", value=f"{carbon_total:,}  {units}")
    col2.metric(label=f"Area", value=f"{area:,} Hectares")
    col3.metric(label=f"pixels", value=f"{count:,}")


# pixel sums instead of means
#    value = round(float(x.sum()))
#    if(selection in ["Vulnerable Carbon (2018)",
#                     "Manageable Carbon (2018)",
#                     "Irrecoverable Carbon (2018)"]):
#        value = value * 9 # 300m pixels, each pixel is 9 hectres


st.divider()

"## Explore further"

with st.expander("code examples"):
    st.write('''
    Try adding additional options to the map. Some suggested examples are shown below. 
    (Of course any self-respecting streamlit app would make these into toggle buttons,
    but this is a demo and it's fun & flexible to be able to execute arbitrary code).

    To explore further, simply modify the Streamlit app.py file from the Files menu up top!
    '''
    )

    st.code('''
    # irrecoverable carbon (Conservation International):
    carbon = "https://data.source.coop/cboettig/carbon/cogs/irrecoverable_c_total_2018.tif"
    m.add_cog_layer(carbon, palette="reds", name="irrecoverable carbon",
                    transparent_bg=True, opacity = 0.8, zoom_to_layer=False)

    # Human Impacts, Vizzuality
    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)

    # Fire Polygons, USGS
    usgs = "https://data.source.coop/cboettig/fire/usgs-mtbs.pmtiles"
    combined_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": 0.2}}]}

    m.add_pmtiles(usgs, name="Fire", style=combined_style, overlay=True, show=True, zoom_to_layer=False)
    ''')       


st.divider()

'''
Note: this is just a proof-of-principle demonstration of these tools, and these calculations have not been validated. 

## Credits

### Data sources

- 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
- 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 USGS, reprocessed to PMTiles on https://beta.source.coop/cboettig/fire/, License: Public Domain.

### Software stack
 
- Streamlit (python) app hosted on free-tier HuggingFace spaces ([source code](https://huggingface.co/spaces/boettiger-lab/leafmap/blob/main/app.py)).
- Cloud-optimized geotifs hosted on [Source.Coop](https://source.coop)
- Mapping with Leafmap, calculations with rasterio

'''