You can launch this notebook in the US GHG Center JupyterHub by clicking the link below.
/stac endpoint. The collection processed in this notebook is the OCO-2 GEOS Column CO₂ Concentrations data product./collections/{collection_id}/items/{item_id}/tilejson.json endpoint.folium.plugins.DualMap, visualize two tiles (side-by-side), allowing time point comparison.In July 2014, NASA successfully launched the first dedicated Earth remote sensing satellite to study atmospheric carbon dioxide (CO₂) from space. The Orbiting Carbon Observatory-2 (OCO-2) is an exploratory science mission designed to collect space-based global measurements of atmospheric CO₂ with the precision, resolution, and coverage needed to characterize sources and sinks (fluxes) on regional scales (≥1000 km). This dataset provides global gridded, daily column-averaged carbon dioxide (XCO₂) concentrations from January 1, 2015 - February 28, 2022. The data are derived from OCO-2 observations that were input to the Goddard Earth Observing System (GEOS) Constituent Data Assimilation System (CoDAS), a modeling and data assimilation system maintained by NASA’s Global Modeling and Assimilation Office (GMAO). Concentrations are measured in moles of carbon dioxide per mole of dry air (mol CO₂/mol dry) at a spatial resolution of 0.5° x 0.625°. Data assimilation synthesizes simulations and observations, adjusting modeled atmospheric constituents like CO₂ to reflect observed values. With the support of NASA’s Carbon Monitoring System (CMS) Program and the OCO Science Team, this dataset was produced as part of the OCO-2 mission which provides the highest quality space-based XCO₂ retrievals to date.
For more information regarding this dataset, please visit the OCO-2 GEOS Column CO₂ Concentrations data overview page.
Required libraries are pre-installed on the GHG Center Hub. If you need to run this notebook elsewhere, please install them with this line in a code cell:
%pip install requests folium rasterstats pystac_client pandas matplotlib –quiet
# Import the following libraries
import requests
import folium
import folium.plugins
from folium import Map, TileLayer
from pystac_client import Client
import branca
import pandas as pd
import matplotlib.pyplot as plt/Users/rrimal/Library/Python/3.9/lib/python/site-packages/urllib3/__init__.py:35: NotOpenSSLWarning: urllib3 v2 only supports OpenSSL 1.1.1+, currently the 'ssl' module is compiled with 'LibreSSL 2.8.3'. See: https://github.com/urllib3/urllib3/issues/3020
warnings.warn(First, we are going to import the required libraries. Once imported, they allow better executing a query in the GHG Center Spatio Temporal Asset Catalog (STAC) Application Programming Interface (API) where the granules for this collection are stored.
# Provide STAC and RASTER API endpoints
STAC_API_URL = "https://earth.gov/ghgcenter/api/stac"
RASTER_API_URL = "https://earth.gov/ghgcenter/api/raster"
# Please use the collection name similar to the one used in STAC collection.
# Name of the collection for OCO-2 GEOS Column CO₂ Concentrations.
collection_name = "oco2geos-co2-daygrid-v10r"# Fetching the collection from STAC collections using appropriate endpoint.
collection = requests.get(f"{STAC_API_URL}/collections/{collection_name}").json()
collection{'id': 'oco2geos-co2-daygrid-v10r',
'type': 'Collection',
'links': [{'rel': 'items',
'type': 'application/geo+json',
'href': 'https://earth.gov/ghgcenter/api/stac/collections/oco2geos-co2-daygrid-v10r/items'},
{'rel': 'parent',
'type': 'application/json',
'href': 'https://earth.gov/ghgcenter/api/stac/'},
{'rel': 'root',
'type': 'application/json',
'href': 'https://earth.gov/ghgcenter/api/stac/'},
{'rel': 'self',
'type': 'application/json',
'href': 'https://earth.gov/ghgcenter/api/stac/collections/oco2geos-co2-daygrid-v10r'}],
'title': 'OCO-2 GEOS Column CO₂ Concentrations v10r',
'extent': {'spatial': {'bbox': [[-180.0, -90.0, 180.0, 90.0]]},
'temporal': {'interval': [['2015-01-01T00:00:00+00:00',
'2022-02-28T00:00:00+00:00']]}},
'license': 'CC0-1.0',
'renders': {'xco2': {'assets': ['xco2'],
'nodata': 0,
'rescale': [[412, 422]],
'colormap_name': 'magma'},
'dashboard': {'assets': ['xco2'],
'nodata': 0,
'rescale': [[412, 422]],
'colormap_name': 'magma'}},
'summaries': {'datetime': ['2015-01-01T00:00:00Z', '2022-02-28T00:00:00Z']},
'description': 'This dataset provides global gridded, daily column-averaged carbon dioxide (XCO₂) concentrations from January 1, 2015 - February 28, 2022. The data are derived from Orbiting Carbon Observatory-2 (OCO-2) satellite observations that were input to the Goddard Earth Observing System (GEOS) Constituent Data Assimilation System (CoDAS), a modeling and data assimilation system maintained by NASA’s Global Modeling and Assimilation Office (GMAO). Concentrations are measured in moles of carbon dioxide per mole of dry air (mol CO₂/mol dry) at a spatial resolution of 0.5° x 0.625°. Data assimilation synthesizes simulations and observations, adjusting modeled atmospheric constituents like CO₂ to reflect observed values. With the support of NASA’s Carbon Monitoring System (CMS) Program and the OCO Science Team, this dataset was produced as part of the OCO-2 mission which provides the highest quality space-based XCO₂ retrievals to date. The source data can be found at https://doi.org/10.5067/Y9M4NM9MPCGH',
'item_assets': {'xco2': {'type': 'image/tiff; application=geotiff; profile=cloud-optimized',
'roles': ['data', 'layer'],
'title': 'Average Dry-Air Column CO₂ (XCO₂)',
'description': 'Daily dry air column-averaged mole fractions of carbon dioxide created from data assimilations of OCO-2 satellite retrievals.'},
'xco2prec': {'type': 'image/tiff; application=geotiff; profile=cloud-optimized',
'roles': ['data', 'layer'],
'title': 'Average Dry-Air Column CO₂ Precision (XCO₂PREC)',
'description': 'Random errors for daily dry air column-averaged mole fractions of carbon dioxide calculated using a posteriori diagnostics.'}},
'stac_version': '1.0.0',
'stac_extensions': ['https://stac-extensions.github.io/render/v1.0.0/schema.json',
'https://stac-extensions.github.io/item-assets/v1.0.0/schema.json'],
'dashboard:is_periodic': True,
'dashboard:time_density': 'day'}Examining the contents of our collection under the temporal variable, we see that the data is available from January 2015 to February 2022. By looking at the dashboard:time density, we can see that these observations are collected daily.
def get_item_count(collection_id):
count = 0
items_url = f"{STAC_API_URL}/collections/{collection_id}/items"
while True:
response = requests.get(items_url)
if not response.ok:
print("error getting items")
exit()
stac = response.json()
count += int(stac["context"].get("returned", 0))
next = [link for link in stac["links"] if link["rel"] == "next"]
if not next:
break
items_url = next[0]["href"]
return count# Check total number of items available
number_of_items = get_item_count(collection_name)
items = requests.get(f"{STAC_API_URL}/collections/{collection_name}/items?limit={number_of_items}").json()["features"]
print(f"Found {len(items)} items")Found 2615 items# Examining the first item in the collection
items[0]{'id': 'oco2geos-co2-daygrid-v10r-20220228',
'bbox': [-180.3125, -90.25, 179.6875, 90.25],
'type': 'Feature',
'links': [{'rel': 'collection',
'type': 'application/json',
'href': 'https://earth.gov/ghgcenter/api/stac/collections/oco2geos-co2-daygrid-v10r'},
{'rel': 'parent',
'type': 'application/json',
'href': 'https://earth.gov/ghgcenter/api/stac/collections/oco2geos-co2-daygrid-v10r'},
{'rel': 'root',
'type': 'application/json',
'href': 'https://earth.gov/ghgcenter/api/stac/'},
{'rel': 'self',
'type': 'application/geo+json',
'href': 'https://earth.gov/ghgcenter/api/stac/collections/oco2geos-co2-daygrid-v10r/items/oco2geos-co2-daygrid-v10r-20220228'},
{'title': 'Map of Item',
'href': 'https://earth.gov/ghgcenter/api/raster/collections/oco2geos-co2-daygrid-v10r/items/oco2geos-co2-daygrid-v10r-20220228/map?assets=xco2&nodata=0&rescale=412%2C422&colormap_name=magma',
'rel': 'preview',
'type': 'text/html'}],
'assets': {'xco2': {'href': 's3://ghgc-data-store/oco2geos-co2-daygrid-v10r/oco2_GEOS_XCO2_L3CO2_day_B10206Ar_20220228.tif',
'type': 'image/tiff; application=geotiff',
'roles': ['data', 'layer'],
'title': 'Average Dry-Air Column CO₂ (XCO₂)',
'proj:bbox': [-180.3125, -90.25, 179.6875, 90.25],
'proj:epsg': 4326.0,
'proj:shape': [361.0, 576.0],
'description': 'Daily dry air column-averaged mole fractions of carbon dioxide created from data assimilations of OCO-2 satellite retrievals.',
'raster:bands': [{'scale': 1.0,
'offset': 0.0,
'sampling': 'area',
'data_type': 'float64',
'histogram': {'max': 423.60419320175424,
'min': 411.7429234611336,
'count': 11.0,
'buckets': [37851.0,
30550.0,
19173.0,
11220.0,
15304.0,
31151.0,
45205.0,
15819.0,
1524.0,
139.0]},
'statistics': {'mean': 416.40504944204235,
'stddev': 2.967704894550985,
'maximum': 423.60419320175424,
'minimum': 411.7429234611336,
'valid_percent': 0.00048091720529393656}}],
'proj:geometry': {'type': 'Polygon',
'coordinates': [[[-180.3125, -90.25],
[179.6875, -90.25],
[179.6875, 90.25],
[-180.3125, 90.25],
[-180.3125, -90.25]]]},
'proj:projjson': {'id': {'code': 4326.0, 'authority': 'EPSG'},
'name': 'WGS 84',
'type': 'GeographicCRS',
'datum': {'name': 'World Geodetic System 1984',
'type': 'GeodeticReferenceFrame',
'ellipsoid': {'name': 'WGS 84',
'semi_major_axis': 6378137.0,
'inverse_flattening': 298.257223563}},
'$schema': 'https://proj.org/schemas/v0.4/projjson.schema.json',
'coordinate_system': {'axis': [{'name': 'Geodetic latitude',
'unit': 'degree',
'direction': 'north',
'abbreviation': 'Lat'},
{'name': 'Geodetic longitude',
'unit': 'degree',
'direction': 'east',
'abbreviation': 'Lon'}],
'subtype': 'ellipsoidal'}},
'proj:transform': [0.625, 0.0, -180.3125, 0.0, -0.5, 90.25, 0.0, 0.0, 1.0]},
'xco2prec': {'href': 's3://ghgc-data-store/oco2geos-co2-daygrid-v10r/oco2_GEOS_XCO2PREC_L3CO2_day_B10206Ar_20220228.tif',
'type': 'image/tiff; application=geotiff',
'roles': ['data', 'layer'],
'title': 'Average Dry-Air Column CO₂ Precision (XCO₂PREC)',
'proj:bbox': [-180.3125, -90.25, 179.6875, 90.25],
'proj:epsg': 4326.0,
'proj:shape': [361.0, 576.0],
'description': 'Random errors for daily dry air column-averaged mole fractions of carbon dioxide calculated using a posteriori diagnostics.',
'raster:bands': [{'scale': 1.0,
'offset': 0.0,
'sampling': 'area',
'data_type': 'float64',
'histogram': {'max': 1.0,
'min': 0.09999999999999999,
'count': 11.0,
'buckets': [73789.0,
19836.0,
7943.0,
4684.0,
3634.0,
3060.0,
3094.0,
3093.0,
3814.0,
84989.0]},
'statistics': {'mean': 0.5499856972588942,
'stddev': 0.4024318718400779,
'maximum': 1.0,
'minimum': 0.09999999999999999,
'valid_percent': 0.00048091720529393656}}],
'proj:geometry': {'type': 'Polygon',
'coordinates': [[[-180.3125, -90.25],
[179.6875, -90.25],
[179.6875, 90.25],
[-180.3125, 90.25],
[-180.3125, -90.25]]]},
'proj:projjson': {'id': {'code': 4326.0, 'authority': 'EPSG'},
'name': 'WGS 84',
'type': 'GeographicCRS',
'datum': {'name': 'World Geodetic System 1984',
'type': 'GeodeticReferenceFrame',
'ellipsoid': {'name': 'WGS 84',
'semi_major_axis': 6378137.0,
'inverse_flattening': 298.257223563}},
'$schema': 'https://proj.org/schemas/v0.4/projjson.schema.json',
'coordinate_system': {'axis': [{'name': 'Geodetic latitude',
'unit': 'degree',
'direction': 'north',
'abbreviation': 'Lat'},
{'name': 'Geodetic longitude',
'unit': 'degree',
'direction': 'east',
'abbreviation': 'Lon'}],
'subtype': 'ellipsoidal'}},
'proj:transform': [0.625, 0.0, -180.3125, 0.0, -0.5, 90.25, 0.0, 0.0, 1.0]},
'rendered_preview': {'title': 'Rendered preview',
'href': 'https://earth.gov/ghgcenter/api/raster/collections/oco2geos-co2-daygrid-v10r/items/oco2geos-co2-daygrid-v10r-20220228/preview.png?assets=xco2&nodata=0&rescale=412%2C422&colormap_name=magma',
'rel': 'preview',
'roles': ['overview'],
'type': 'image/png'}},
'geometry': {'type': 'Polygon',
'coordinates': [[[-180.3125, -90.25],
[179.6875, -90.25],
[179.6875, 90.25],
[-180.3125, 90.25],
[-180.3125, -90.25]]]},
'collection': 'oco2geos-co2-daygrid-v10r',
'properties': {'datetime': '2022-02-28T00:00:00+00:00'},
'stac_version': '1.0.0',
'stac_extensions': ['https://stac-extensions.github.io/raster/v1.1.0/schema.json',
'https://stac-extensions.github.io/projection/v1.1.0/schema.json']}Below, we enter minimum and maximum values to provide our upper and lower bounds in rescale_values.
In this notebook, we will explore the temporal impacts of CO₂ emissions. We will visualize the outputs on a map using folium.
# To access the year value from each item more easily, this will let us query more explicitly by year and month (e.g., 2020-02)
items = {item["properties"]["datetime"]: item for item in items}
asset_name = "xco2" #fossil fuel# Fetching the min and max values for a specific item
rescale_values = {"max":items[list(items.keys())[0]]["assets"][asset_name]["raster:bands"][0]["histogram"]["max"], "min":items[list(items.keys())[0]]["assets"][asset_name]["raster:bands"][0]["histogram"]["min"]}Now, we will pass the item id, collection name, and rescaling_factor to the Raster API endpoint. We will do this twice, once for 2022-02-08 and again for 2022-01-27, so that we can visualize each event independently.
color_map = "magma"
oco2_1 = requests.get(
f"{RASTER_API_URL}/collections/{items[list(items.keys())[0]]['collection']}/items/{items[list(items.keys())[0]]['id']}/tilejson.json?"
f"&assets={asset_name}"
f"&color_formula=gamma+r+1.05&colormap_name={color_map}"
f"&rescale={rescale_values['min']},{rescale_values['max']}",
).json()
oco2_1{'tilejson': '2.2.0',
'version': '1.0.0',
'scheme': 'xyz',
'tiles': ['https://earth.gov/ghgcenter/api/raster/collections/oco2geos-co2-daygrid-v10r/items/oco2geos-co2-daygrid-v10r-20220228/tiles/WebMercatorQuad/{z}/{x}/{y}@1x?assets=xco2&color_formula=gamma+r+1.05&colormap_name=magma&rescale=411.7429234611336%2C423.60419320175424'],
'minzoom': 0,
'maxzoom': 24,
'bounds': [-180.3125, -90.25, 179.6875, 90.25],
'center': [-0.3125, 0.0, 0]}oco2_2 = requests.get(
f"{RASTER_API_URL}/collections/{items[list(items.keys())[1]]['collection']}/items/{items[list(items.keys())[1]]['id']}/tilejson.json?"
f"&assets={asset_name}"
f"&color_formula=gamma+r+1.05&colormap_name={color_map}"
f"&rescale={rescale_values['min']},{rescale_values['max']}",
).json()
oco2_2{'tilejson': '2.2.0',
'version': '1.0.0',
'scheme': 'xyz',
'tiles': ['https://earth.gov/ghgcenter/api/raster/collections/oco2geos-co2-daygrid-v10r/items/oco2geos-co2-daygrid-v10r-20220227/tiles/WebMercatorQuad/{z}/{x}/{y}@1x?assets=xco2&color_formula=gamma+r+1.05&colormap_name=magma&rescale=411.7429234611336%2C423.60419320175424'],
'minzoom': 0,
'maxzoom': 24,
'bounds': [-180.3125, -90.25, 179.6875, 90.25],
'center': [-0.3125, 0.0, 0]}# Set initial zoom and center of map for XCO₂ Layer
# Centre of map [latitude,longitude]
map_ = folium.plugins.DualMap(location=(34, -118), zoom_start=6)
map_layer_2020 = TileLayer(
tiles=oco2_1["tiles"][0],
attr="GHG",
opacity=0.5,
)
map_layer_2020.add_to(map_.m1)
map_layer_2019 = TileLayer(
tiles=oco2_2["tiles"][0],
attr="GHG",
opacity=0.5,
)
map_layer_2019.add_to(map_.m2)
# visualising the map
map_To perform zonal statistics, first we need to create a polygon. In this use case we are creating a polygon in Texas (USA).
# Texas, USA
texas_aoi = {
"type": "Feature",
"properties": {},
"geometry": {
"coordinates": [
[
[-95, 29],
[-95, 33],
[-104, 33],
[-104,29],
[-95, 29]
]
],
"type": "Polygon",
},
}# We will plug in the coordinates for a location inside the the polygon and a zoom level
aoi_map = Map(
tiles="OpenStreetMap",
location=[
30,-100
],
zoom_start=6,
)
folium.GeoJson(texas_aoi, name="Texas, USA").add_to(aoi_map)
aoi_map# Check total number of items available
items = requests.get(
f"{STAC_API_URL}/collections/{collection_name}/items?limit=600"
).json()["features"]
print(f"Found {len(items)} items")Found 600 items# Explore the first item
items[0]{'id': 'oco2geos-co2-daygrid-v10r-20220228',
'bbox': [-180.3125, -90.25, 179.6875, 90.25],
'type': 'Feature',
'links': [{'rel': 'collection',
'type': 'application/json',
'href': 'https://earth.gov/ghgcenter/api/stac/collections/oco2geos-co2-daygrid-v10r'},
{'rel': 'parent',
'type': 'application/json',
'href': 'https://earth.gov/ghgcenter/api/stac/collections/oco2geos-co2-daygrid-v10r'},
{'rel': 'root',
'type': 'application/json',
'href': 'https://earth.gov/ghgcenter/api/stac/'},
{'rel': 'self',
'type': 'application/geo+json',
'href': 'https://earth.gov/ghgcenter/api/stac/collections/oco2geos-co2-daygrid-v10r/items/oco2geos-co2-daygrid-v10r-20220228'},
{'title': 'Map of Item',
'href': 'https://earth.gov/ghgcenter/api/raster/collections/oco2geos-co2-daygrid-v10r/items/oco2geos-co2-daygrid-v10r-20220228/map?assets=xco2&nodata=0&rescale=412%2C422&colormap_name=magma',
'rel': 'preview',
'type': 'text/html'}],
'assets': {'xco2': {'href': 's3://ghgc-data-store/oco2geos-co2-daygrid-v10r/oco2_GEOS_XCO2_L3CO2_day_B10206Ar_20220228.tif',
'type': 'image/tiff; application=geotiff',
'roles': ['data', 'layer'],
'title': 'Average Dry-Air Column CO₂ (XCO₂)',
'proj:bbox': [-180.3125, -90.25, 179.6875, 90.25],
'proj:epsg': 4326.0,
'proj:shape': [361.0, 576.0],
'description': 'Daily dry air column-averaged mole fractions of carbon dioxide created from data assimilations of OCO-2 satellite retrievals.',
'raster:bands': [{'scale': 1.0,
'offset': 0.0,
'sampling': 'area',
'data_type': 'float64',
'histogram': {'max': 423.60419320175424,
'min': 411.7429234611336,
'count': 11.0,
'buckets': [37851.0,
30550.0,
19173.0,
11220.0,
15304.0,
31151.0,
45205.0,
15819.0,
1524.0,
139.0]},
'statistics': {'mean': 416.40504944204235,
'stddev': 2.967704894550985,
'maximum': 423.60419320175424,
'minimum': 411.7429234611336,
'valid_percent': 0.00048091720529393656}}],
'proj:geometry': {'type': 'Polygon',
'coordinates': [[[-180.3125, -90.25],
[179.6875, -90.25],
[179.6875, 90.25],
[-180.3125, 90.25],
[-180.3125, -90.25]]]},
'proj:projjson': {'id': {'code': 4326.0, 'authority': 'EPSG'},
'name': 'WGS 84',
'type': 'GeographicCRS',
'datum': {'name': 'World Geodetic System 1984',
'type': 'GeodeticReferenceFrame',
'ellipsoid': {'name': 'WGS 84',
'semi_major_axis': 6378137.0,
'inverse_flattening': 298.257223563}},
'$schema': 'https://proj.org/schemas/v0.4/projjson.schema.json',
'coordinate_system': {'axis': [{'name': 'Geodetic latitude',
'unit': 'degree',
'direction': 'north',
'abbreviation': 'Lat'},
{'name': 'Geodetic longitude',
'unit': 'degree',
'direction': 'east',
'abbreviation': 'Lon'}],
'subtype': 'ellipsoidal'}},
'proj:transform': [0.625, 0.0, -180.3125, 0.0, -0.5, 90.25, 0.0, 0.0, 1.0]},
'xco2prec': {'href': 's3://ghgc-data-store/oco2geos-co2-daygrid-v10r/oco2_GEOS_XCO2PREC_L3CO2_day_B10206Ar_20220228.tif',
'type': 'image/tiff; application=geotiff',
'roles': ['data', 'layer'],
'title': 'Average Dry-Air Column CO₂ Precision (XCO₂PREC)',
'proj:bbox': [-180.3125, -90.25, 179.6875, 90.25],
'proj:epsg': 4326.0,
'proj:shape': [361.0, 576.0],
'description': 'Random errors for daily dry air column-averaged mole fractions of carbon dioxide calculated using a posteriori diagnostics.',
'raster:bands': [{'scale': 1.0,
'offset': 0.0,
'sampling': 'area',
'data_type': 'float64',
'histogram': {'max': 1.0,
'min': 0.09999999999999999,
'count': 11.0,
'buckets': [73789.0,
19836.0,
7943.0,
4684.0,
3634.0,
3060.0,
3094.0,
3093.0,
3814.0,
84989.0]},
'statistics': {'mean': 0.5499856972588942,
'stddev': 0.4024318718400779,
'maximum': 1.0,
'minimum': 0.09999999999999999,
'valid_percent': 0.00048091720529393656}}],
'proj:geometry': {'type': 'Polygon',
'coordinates': [[[-180.3125, -90.25],
[179.6875, -90.25],
[179.6875, 90.25],
[-180.3125, 90.25],
[-180.3125, -90.25]]]},
'proj:projjson': {'id': {'code': 4326.0, 'authority': 'EPSG'},
'name': 'WGS 84',
'type': 'GeographicCRS',
'datum': {'name': 'World Geodetic System 1984',
'type': 'GeodeticReferenceFrame',
'ellipsoid': {'name': 'WGS 84',
'semi_major_axis': 6378137.0,
'inverse_flattening': 298.257223563}},
'$schema': 'https://proj.org/schemas/v0.4/projjson.schema.json',
'coordinate_system': {'axis': [{'name': 'Geodetic latitude',
'unit': 'degree',
'direction': 'north',
'abbreviation': 'Lat'},
{'name': 'Geodetic longitude',
'unit': 'degree',
'direction': 'east',
'abbreviation': 'Lon'}],
'subtype': 'ellipsoidal'}},
'proj:transform': [0.625, 0.0, -180.3125, 0.0, -0.5, 90.25, 0.0, 0.0, 1.0]},
'rendered_preview': {'title': 'Rendered preview',
'href': 'https://earth.gov/ghgcenter/api/raster/collections/oco2geos-co2-daygrid-v10r/items/oco2geos-co2-daygrid-v10r-20220228/preview.png?assets=xco2&nodata=0&rescale=412%2C422&colormap_name=magma',
'rel': 'preview',
'roles': ['overview'],
'type': 'image/png'}},
'geometry': {'type': 'Polygon',
'coordinates': [[[-180.3125, -90.25],
[179.6875, -90.25],
[179.6875, 90.25],
[-180.3125, 90.25],
[-180.3125, -90.25]]]},
'collection': 'oco2geos-co2-daygrid-v10r',
'properties': {'datetime': '2022-02-28T00:00:00+00:00'},
'stac_version': '1.0.0',
'stac_extensions': ['https://stac-extensions.github.io/raster/v1.1.0/schema.json',
'https://stac-extensions.github.io/projection/v1.1.0/schema.json']}# The bounding box should be passed to the geojson param as a geojson Feature or FeatureCollection
def generate_stats(item, geojson):
result = requests.post(
f"{RASTER_API_URL}/cog/statistics",
params={"url": item["assets"][asset_name]["href"]},
json=geojson,
).json()
print(result)
return {
**result["properties"],
"datetime": item["properties"]["datetime"],
}for item in items:
print(item["properties"]["datetime"])
break2022-02-28T00:00:00+00:00With the function above we can generate the statistics for the AOI.
%%time
stats = [generate_stats(item, texas_aoi) for item in items]{'type': 'Feature', 'geometry': {'type': 'Polygon', 'coordinates': [[[-95.0, 29.0], [-95.0, 33.0], [-104.0, 33.0], [-104.0, 29.0], [-95.0, 29.0]]]}, 'properties': {'statistics': {'b1': {'min': 418.2305856375024, 'max': 419.41294693970116, 'mean': 418.84807499634246, 'count': 115.20000457763672, 'sum': 48251.30015691298, 'std': 0.25036812587510676, 'median': 418.7834456388373, 'majority': 418.2305856375024, 'minority': 418.2305856375024, 'unique': 135.0, 'histogram': [[3.0, 4.0, 6.0, 22.0, 41.0, 12.0, 10.0, 15.0, 9.0, 13.0], [418.2305856375024, 418.34882176772226, 418.46705789794214, 418.585294028162, 418.7035301583819, 418.8217662886018, 418.9400024188216, 419.0582385490415, 419.1764746792614, 419.2947108094813, 419.41294693970116]], 'valid_percent': 100.0, 'masked_pixels': 0.0, 'valid_pixels': 135.0, 'percentile_2': 418.3893688605167, 'percentile_98': 419.3659042357467}}}}
{'type': 'Feature', 'geometry': {'type': 'Polygon', 'coordinates': [[[-95.0, 29.0], [-95.0, 33.0], [-104.0, 33.0], [-104.0, 29.0], [-95.0, 29.0]]]}, 'properties': {'statistics': {'b1': {'min': 418.6847545497585, 'max': 420.117827161448, 'mean': 419.50975926283064, 'count': 115.20000457763672, 'sum': 48327.52618744137, 'std': 0.33164544808095336, 'median': 419.4695684418548, 'majority': 418.6847545497585, 'minority': 418.6847545497585, 'unique': 135.0, 'histogram': [[4.0, 4.0, 9.0, 11.0, 29.0, 16.0, 23.0, 10.0, 17.0, 12.0], [418.6847545497585, 418.82806181092747, 418.9713690720964, 419.1146763332654, 419.25798359443434, 419.4012908556033, 419.5445981167722, 419.68790537794115, 419.8312126391101, 419.97451990027906, 420.117827161448]], 'valid_percent': 100.0, 'masked_pixels': 0.0, 'valid_pixels': 135.0, 'percentile_2': 418.8113416603301, 'percentile_98': 420.09016033262014}}}}
{'type': 'Feature', 'geometry': {'type': 'Polygon', 'coordinates': [[[-95.0, 29.0], [-95.0, 33.0], [-104.0, 33.0], [-104.0, 29.0], [-95.0, 29.0]]]}, 'properties': {'statistics': {'b1': {'min': 417.77668957365677, 'max': 419.3491913611069, 'mean': 418.780854087903, 'count': 115.20000457763672, 'sum': 48243.55630795304, 'std': 0.2843476819639469, 'median': 418.7747799733188, 'majority': 417.77668957365677, 'minority': 417.77668957365677, 'unique': 135.0, 'histogram': [[1.0, 3.0, 4.0, 7.0, 7.0, 32.0, 32.0, 21.0, 17.0, 11.0], [417.77668957365677, 417.9339397524018, 418.0911899311468, 418.2484401098918, 418.40569028863683, 418.56294046738185, 418.7201906461268, 418.8774408248718, 419.03469100361684, 419.19194118236186, 419.3491913611069]], 'valid_percent': 100.0, 'masked_pixels': 0.0, 'valid_pixels': 135.0, 'percentile_2': 418.04159627645276, 'percentile_98': 419.3299428152386}}}}
{'type': 'Feature', 'geometry': {'type': 'Polygon', 'coordinates': [[[-95.0, 29.0], [-95.0, 33.0], [-104.0, 33.0], [-104.0, 29.0], [-95.0, 29.0]]]}, 'properties': {'statistics': {'b1': {'min': 417.9413153906353, 'max': 419.45298289647326, 'mean': 418.7028609668949, 'count': 115.20000457763672, 'sum': 48234.571500055885, 'std': 0.3277881006588393, 'median': 418.68947664625006, 'majority': 417.9413153906353, 'minority': 417.9413153906353, 'unique': 135.0, 'histogram': [[6.0, 3.0, 13.0, 23.0, 21.0, 27.0, 13.0, 11.0, 10.0, 8.0], [417.9413153906353, 418.0924821412191, 418.2436488918029, 418.3948156423867, 418.5459823929705, 418.69714914355427, 418.84831589413807, 418.99948264472187, 419.15064939530566, 419.30181614588946, 419.45298289647326]], 'valid_percent': 100.0, 'masked_pixels': 0.0, 'valid_pixels': 135.0, 'percentile_2': 418.07206434896216, 'percentile_98': 419.35966874007136}}}}
{'type': 'Feature', 'geometry': {'type': 'Polygon', 'coordinates': [[[-95.0, 29.0], [-95.0, 33.0], [-104.0, 33.0], [-104.0, 29.0], [-95.0, 29.0]]]}, 'properties': {'statistics': {'b1': {'min': 417.85604844335467, 'max': 419.5758046989794, 'mean': 418.7884695773465, 'count': 115.20000457763672, 'sum': 48244.433612371795, 'std': 0.30063415289532397, 'median': 418.76762770698406, 'majority': 417.85604844335467, 'minority': 417.85604844335467, 'unique': 135.0, 'histogram': [[3.0, 4.0, 5.0, 8.0, 30.0, 39.0, 22.0, 9.0, 9.0, 6.0], [417.85604844335467, 418.02802406891715, 418.19999969447963, 418.3719753200421, 418.5439509456046, 418.7159265711671, 418.8879021967295, 419.059877822292, 419.23185344785446, 419.40382907341694, 419.5758046989794]], 'valid_percent': 100.0, 'masked_pixels': 0.0, 'valid_pixels': 135.0, 'percentile_2': 418.0337637080811, 'percentile_98': 419.41854578908533}}}}
{'type': 'Feature', 'geometry': {'type': 'Polygon', 'coordinates': [[[-95.0, 29.0], [-95.0, 33.0], [-104.0, 33.0], [-104.0, 29.0], [-95.0, 29.0]]]}, 'properties': {'statistics': {'b1': {'min': 417.67429502215236, 'max': 419.48383659473615, 'mean': 418.68559111570704, 'count': 115.20000457763672, 'sum': 48232.58201311999, 'std': 0.3763560584398085, 'median': 418.6174992355518, 'majority': 417.67429502215236, 'minority': 417.67429502215236, 'unique': 135.0, 'histogram': [[3.0, 7.0, 3.0, 17.0, 28.0, 24.0, 16.0, 12.0, 12.0, 13.0], [417.67429502215236, 417.85524917941075, 418.03620333666913, 418.2171574939275, 418.3981116511859, 418.5790658084443, 418.7600199657026, 418.940974122961, 419.1219282802194, 419.30288243747776, 419.48383659473615]], 'valid_percent': 100.0, 'masked_pixels': 0.0, 'valid_pixels': 135.0, 'percentile_2': 417.89051465457305, 'percentile_98': 419.38557842513546}}}}
{'type': 'Feature', 'geometry': {'type': 'Polygon', 'coordinates': [[[-95.0, 29.0], [-95.0, 33.0], [-104.0, 33.0], [-104.0, 29.0], [-95.0, 29.0]]]}, 'properties': {'statistics': {'b1': {'min': 417.33726175152697, 'max': 418.41128768282937, 'mean': 417.85008901465176, 'count': 115.20000457763672, 'sum': 48136.33216725379, 'std': 0.24384000570863074, 'median': 417.8136914561037, 'majority': 417.33726175152697, 'minority': 417.33726175152697, 'unique': 135.0, 'histogram': [[10.0, 9.0, 15.0, 24.0, 18.0, 15.0, 16.0, 10.0, 12.0, 6.0], [417.33726175152697, 417.4446643446572, 417.55206693778746, 417.6594695309177, 417.76687212404795, 417.8742747171782, 417.9816773103084, 418.08907990343863, 418.1964824965689, 418.3038850896991, 418.41128768282937]], 'valid_percent': 100.0, 'masked_pixels': 0.0, 'valid_pixels': 135.0, 'percentile_2': 417.3856541456189, 'percentile_98': 418.3290839137044}}}}
{'type': 'Feature', 'geometry': {'type': 'Polygon', 'coordinates': [[[-95.0, 29.0], [-95.0, 33.0], [-104.0, 33.0], [-104.0, 29.0], [-95.0, 29.0]]]}, 'properties': {'statistics': {'b1': {'min': 417.18078136909753, 'max': 418.87410043273115, 'mean': 417.96739473227973, 'count': 115.20000457763672, 'sum': 48149.84578646152, 'std': 0.37096477092214697, 'median': 417.9669485893101, 'majority': 417.18078136909753, 'minority': 417.18078136909753, 'unique': 135.0, 'histogram': [[11.0, 7.0, 9.0, 27.0, 21.0, 23.0, 16.0, 8.0, 9.0, 4.0], [417.18078136909753, 417.3501132754609, 417.51944518182427, 417.68877708818763, 417.858108994551, 418.02744090091437, 418.1967728072777, 418.36610471364105, 418.5354366200044, 418.7047685263678, 418.87410043273115]], 'valid_percent': 100.0, 'masked_pixels': 0.0, 'valid_pixels': 135.0, 'percentile_2': 417.3019879090134, 'percentile_98': 418.68801781674847}}}}
{'type': 'Feature', 'geometry': {'type': 'Polygon', 'coordinates': [[[-95.0, 29.0], [-95.0, 33.0], [-104.0, 33.0], [-104.0, 29.0], [-95.0, 29.0]]]}, 'properties': {'statistics': {'b1': {'min': 417.9257921350654, 'max': 419.1924708720762, 'mean': 418.6990498763579, 'count': 115.20000457763672, 'sum': 48234.132462408576, 'std': 0.29165282986122426, 'median': 418.72919246088713, 'majority': 417.9257921350654, 'minority': 417.9257921350654, 'unique': 135.0, 'histogram': [[4.0, 5.0, 9.0, 7.0, 16.0, 17.0, 27.0, 17.0, 16.0, 17.0], [417.9257921350654, 418.0524600087665, 418.1791278824676, 418.30579575616866, 418.43246362986974, 418.5591315035708, 418.6857993772719, 418.812467250973, 418.93913512467407, 419.06580299837515, 419.1924708720762]], 'valid_percent': 100.0, 'masked_pixels': 0.0, 'valid_pixels': 135.0, 'percentile_2': 418.01999395829625, 'percentile_98': 419.1418738628272}}}}
{'type': 'Feature', 'geometry': {'type': 'Polygon', 'coordinates': [[[-95.0, 29.0], [-95.0, 33.0], [-104.0, 33.0], [-104.0, 29.0], [-95.0, 29.0]]]}, 'properties': {'statistics': {'b1': {'min': 417.936455050949, 'max': 419.3355161987711, 'mean': 418.7195976359443, 'count': 115.20000457763672, 'sum': 48236.499564406986, 'std': 0.2840015536928068, 'median': 418.71234498103144, 'majority': 417.936455050949, 'minority': 417.936455050949, 'unique': 135.0, 'histogram': [[3.0, 4.0, 5.0, 16.0, 20.0, 18.0, 22.0, 30.0, 12.0, 5.0], [417.936455050949, 418.0763611657312, 418.2162672805134, 418.3561733952956, 418.49607951007783, 418.63598562486004, 418.77589173964225, 418.91579785442445, 419.05570396920666, 419.19561008398887, 419.3355161987711]], 'valid_percent': 100.0, 'masked_pixels': 0.0, 'valid_pixels': 135.0, 'percentile_2': 418.0879004707094, 'percentile_98': 419.2052547296044}}}}
{'type': 'Feature', 'geometry': {'type': 'Polygon', 'coordinates': [[[-95.0, 29.0], [-95.0, 33.0], [-104.0, 33.0], [-104.0, 29.0], [-95.0, 29.0]]]}, 'properties': {'statistics': {'b1': {'min': 418.2181946816855, 'max': 419.3920976831578, 'mean': 418.8331630624568, 'count': 115.20000457763672, 'sum': 48249.582302061084, 'std': 0.26588725750350356, 'median': 418.7950507912319, 'majority': 418.2181946816855, 'minority': 418.2181946816855, 'unique': 135.0, 'histogram': [[3.0, 5.0, 19.0, 16.0, 24.0, 12.0, 15.0, 19.0, 18.0, 4.0], [418.2181946816855, 418.3355849818327, 418.45297528197995, 418.5703655821272, 418.6877558822744, 418.8051461824216, 418.92253648256883, 419.03992678271607, 419.1573170828633, 419.27470738301054, 419.3920976831578]], 'valid_percent': 100.0, 'masked_pixels': 0.0, 'valid_pixels': 135.0, 'percentile_2': 418.37579919956625, 'percentile_98': 419.2733067611698}}}}
{'type': 'Feature', 'geometry': {'type': 'Polygon', 'coordinates': [[[-95.0, 29.0], [-95.0, 33.0], [-104.0, 33.0], [-104.0, 29.0], [-95.0, 29.0]]]}, 'properties': {'statistics': {'b1': {'min': 417.5934045633766, 'max': 418.85400787577964, 'mean': 418.2622949584963, 'count': 115.20000457763672, 'sum': 48183.81829387161, 'std': 0.26309325885448903, 'median': 418.2429147476796, 'majority': 417.5934045633766, 'minority': 417.5934045633766, 'unique': 135.0, 'histogram': [[5.0, 7.0, 4.0, 17.0, 23.0, 30.0, 18.0, 14.0, 9.0, 8.0], [417.5934045633766, 417.7194648946169, 417.8455252258572, 417.9715855570975, 418.0976458883378, 418.22370621957816, 418.34976655081846, 418.47582688205875, 418.60188721329905, 418.72794754453935, 418.85400787577964]], 'valid_percent': 100.0, 'masked_pixels': 0.0, 'valid_pixels': 135.0, 'percentile_2': 417.6444635959342, 'percentile_98': 418.7770828139037}}}}
{'type': 'Feature', 'geometry': {'type': 'Polygon', 'coordinates': [[[-95.0, 29.0], [-95.0, 33.0], [-104.0, 33.0], [-104.0, 29.0], [-95.0, 29.0]]]}, 'properties': {'statistics': {'b1': {'min': 417.62231921893544, 'max': 418.5573889117222, 'mean': 418.10896264511047, 'count': 115.20000457763672, 'sum': 48166.15441066767, 'std': 0.20324802285199642, 'median': 418.1081385468133, 'majority': 417.62231921893544, 'minority': 417.62231921893544, 'unique': 135.0, 'histogram': [[6.0, 7.0, 8.0, 11.0, 26.0, 28.0, 15.0, 13.0, 15.0, 6.0], [417.62231921893544, 417.7158261882141, 417.8093331574928, 417.9028401267715, 417.99634709605016, 418.08985406532884, 418.1833610346075, 418.2768680038862, 418.37037497316487, 418.46388194244355, 418.5573889117222]], 'valid_percent': 100.0, 'masked_pixels': 0.0, 'valid_pixels': 135.0, 'percentile_2': 417.67202128539793, 'percentile_98': 418.46690510283224}}}}
{'type': 'Feature', 'geometry': {'type': 'Polygon', 'coordinates': [[[-95.0, 29.0], [-95.0, 33.0], [-104.0, 33.0], [-104.0, 29.0], [-95.0, 29.0]]]}, 'properties': {'statistics': {'b1': {'min': 417.5560861767736, 'max': 418.9195315120742, 'mean': 418.3652775214227, 'count': 115.20000457763672, 'sum': 48195.68188559215, 'std': 0.37052140494330665, 'median': 418.4036661172286, 'majority': 417.5560861767736, 'minority': 417.5560861767736, 'unique': 135.0, 'histogram': [[6.0, 11.0, 10.0, 6.0, 16.0, 13.0, 14.0, 17.0, 21.0, 21.0], [417.5560861767736, 417.69243071030365, 417.8287752438337, 417.9651197773638, 418.10146431089385, 418.23780884442385, 418.3741533779539, 418.510497911484, 418.64684244501404, 418.7831869785441, 418.9195315120742]], 'valid_percent': 100.0, 'masked_pixels': 0.0, 'valid_pixels': 135.0, 'percentile_2': 417.6400434516836, 'percentile_98': 418.8933708064724}}}}
{'type': 'Feature', 'geometry': {'type': 'Polygon', 'coordinates': [[[-95.0, 29.0], [-95.0, 33.0], [-104.0, 33.0], [-104.0, 29.0], [-95.0, 29.0]]]}, 'properties': {'statistics': {'b1': {'min': 417.7913288003765, 'max': 419.00600990629755, 'mean': 418.375245165685, 'count': 115.20000457763672, 'sum': 48196.830158256795, 'std': 0.2785801795589886, 'median': 418.3290402579587, 'majority': 417.7913288003765, 'minority': 417.7913288003765, 'unique': 135.0, 'histogram': [[5.0, 10.0, 18.0, 21.0, 18.0, 14.0, 11.0, 21.0, 13.0, 4.0], [417.7913288003765, 417.9127969109686, 418.0342650215607, 418.1557331321528, 418.2772012427449, 418.398669353337, 418.52013746392913, 418.64160557452124, 418.76307368511334, 418.88454179570545, 419.00600990629755]], 'valid_percent': 100.0, 'masked_pixels': 0.0, 'valid_pixels': 135.0, 'percentile_2': 417.87197551457217, 'percentile_98': 418.8945422356482}}}}
{'type': 'Feature', 'geometry': {'type': 'Polygon', 'coordinates': [[[-95.0, 29.0], [-95.0, 33.0], [-104.0, 33.0], [-104.0, 29.0], [-95.0, 29.0]]]}, 'properties': {'statistics': {'b1': {'min': 418.09239701251505, 'max': 419.11455264198594, 'mean': 418.68147209174833, 'count': 115.20000457763672, 'sum': 48232.10750154109, 'std': 0.26184321236944064, 'median': 418.68646803777665, 'majority': 418.09239701251505, 'minority': 418.09239701251505, 'unique': 135.0, 'histogram': [[3.0, 9.0, 12.0, 15.0, 12.0, 17.0, 12.0, 11.0, 27.0, 17.0], [418.09239701251505, 418.19461257546214, 418.29682813840924, 418.39904370135633, 418.5012592643034, 418.60347482725047, 418.70569039019756, 418.80790595314465, 418.91012151609175, 419.01233707903884, 419.11455264198594]], 'valid_percent': 100.0, 'masked_pixels': 0.0, 'valid_pixels': 135.0, 'percentile_2': 418.1957083346787, 'percentile_98': 419.0633808320854}}}}
{'type': 'Feature', 'geometry': {'type': 'Polygon', 'coordinates': [[[-95.0, 29.0], [-95.0, 33.0], [-104.0, 33.0], [-104.0, 29.0], [-95.0, 29.0]]]}, 'properties': {'statistics': {'b1': {'min': 418.1292424618733, 'max': 419.33653847081587, 'mean': 418.7633269115488, 'count': 115.20000457763672, 'sum': 48241.5371771568, 'std': 0.2749718221731183, 'median': 418.74792441376485, 'majority': 418.1292424618733, 'minority': 418.1292424618733, 'unique': 135.0, 'histogram': [[8.0, 3.0, 12.0, 23.0, 19.0, 15.0, 14.0, 16.0, 21.0, 4.0], [418.1292424618733, 418.24997206276754, 418.3707016636618, 418.49143126455607, 418.61216086545033, 418.73289046634454, 418.8536200672388, 418.9743496681331, 419.09507926902734, 419.2158088699216, 419.33653847081587]], 'valid_percent': 100.0, 'masked_pixels': 0.0, 'valid_pixels': 135.0, 'percentile_2': 418.2062220934313, 'percentile_98': 419.1992884443607}}}}
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{'type': 'Feature', 'geometry': {'type': 'Polygon', 'coordinates': [[[-95.0, 29.0], [-95.0, 33.0], [-104.0, 33.0], [-104.0, 29.0], [-95.0, 29.0]]]}, 'properties': {'statistics': {'b1': {'min': 413.6154093430378, 'max': 414.4218110013753, 'mean': 414.01380619542937, 'count': 115.20000457763672, 'sum': 47694.39236891826, 'std': 0.15383991456619886, 'median': 413.99568362976424, 'majority': 413.6154093430378, 'minority': 413.6154093430378, 'unique': 135.0, 'histogram': [[3.0, 7.0, 10.0, 27.0, 27.0, 23.0, 16.0, 12.0, 7.0, 3.0], [413.6154093430378, 413.69604950887157, 413.7766896747053, 413.8573298405391, 413.93797000637284, 414.01861017220654, 414.0992503380403, 414.17989050387405, 414.2605306697078, 414.34117083554156, 414.4218110013753]], 'valid_percent': 100.0, 'masked_pixels': 0.0, 'valid_pixels': 135.0, 'percentile_2': 413.7082287343219, 'percentile_98': 414.3284932069946}}}}
{'type': 'Feature', 'geometry': {'type': 'Polygon', 'coordinates': [[[-95.0, 29.0], [-95.0, 33.0], [-104.0, 33.0], [-104.0, 29.0], [-95.0, 29.0]]]}, 'properties': {'statistics': {'b1': {'min': 414.07335083931684, 'max': 414.64257810730487, 'mean': 414.2401453746762, 'count': 115.20000457763672, 'sum': 47720.4666434036, 'std': 0.08932405353097873, 'median': 414.23293441766873, 'majority': 414.07335083931684, 'minority': 414.07335083931684, 'unique': 135.0, 'histogram': [[11.0, 32.0, 27.0, 32.0, 21.0, 8.0, 0.0, 1.0, 2.0, 1.0], [414.07335083931684, 414.13027356611565, 414.18719629291445, 414.24411901971325, 414.30104174651206, 414.35796447331086, 414.41488720010966, 414.47180992690846, 414.52873265370727, 414.58565538050607, 414.64257810730487]], 'valid_percent': 100.0, 'masked_pixels': 0.0, 'valid_pixels': 135.0, 'percentile_2': 414.08167089684866, 'percentile_98': 414.4031881878618}}}}
{'type': 'Feature', 'geometry': {'type': 'Polygon', 'coordinates': [[[-95.0, 29.0], [-95.0, 33.0], [-104.0, 33.0], [-104.0, 29.0], [-95.0, 29.0]]]}, 'properties': {'statistics': {'b1': {'min': 413.8769618293736, 'max': 414.4926060689613, 'mean': 414.0766919599859, 'count': 115.20000457763672, 'sum': 47701.636809283045, 'std': 0.11449538158699511, 'median': 414.04915100429207, 'majority': 413.8769618293736, 'minority': 413.8769618293736, 'unique': 135.0, 'histogram': [[9.0, 32.0, 35.0, 15.0, 18.0, 10.0, 4.0, 7.0, 4.0, 1.0], [413.8769618293736, 413.9385262533324, 414.00009067729115, 414.0616551012499, 414.1232195252087, 414.18478394916747, 414.24634837312624, 414.307912797085, 414.3694772210438, 414.43104164500255, 414.4926060689613]], 'valid_percent': 100.0, 'masked_pixels': 0.0, 'valid_pixels': 135.0, 'percentile_2': 413.9032644161489, 'percentile_98': 414.3582555116154}}}}
{'type': 'Feature', 'geometry': {'type': 'Polygon', 'coordinates': [[[-95.0, 29.0], [-95.0, 33.0], [-104.0, 33.0], [-104.0, 29.0], [-95.0, 29.0]]]}, 'properties': {'statistics': {'b1': {'min': 413.88225508853793, 'max': 414.3805199419148, 'mean': 414.06020590057466, 'count': 115.20000457763672, 'sum': 47699.7376151634, 'std': 0.10172649448593125, 'median': 414.04588773730217, 'majority': 413.88225508853793, 'minority': 413.88225508853793, 'unique': 135.0, 'histogram': [[12.0, 16.0, 22.0, 36.0, 14.0, 16.0, 9.0, 4.0, 4.0, 2.0], [413.88225508853793, 413.9320815738756, 413.9819080592133, 414.031734544551, 414.0815610298887, 414.1313875152264, 414.18121400056407, 414.23104048590176, 414.28086697123945, 414.33069345657714, 414.3805199419148]], 'valid_percent': 100.0, 'masked_pixels': 0.0, 'valid_pixels': 135.0, 'percentile_2': 413.89060424990015, 'percentile_98': 414.302725403104}}}}
{'type': 'Feature', 'geometry': {'type': 'Polygon', 'coordinates': [[[-95.0, 29.0], [-95.0, 33.0], [-104.0, 33.0], [-104.0, 29.0], [-95.0, 29.0]]]}, 'properties': {'statistics': {'b1': {'min': 413.8595249969512, 'max': 414.43683949182747, 'mean': 414.1013446241451, 'count': 115.20000457763672, 'sum': 47704.47679630703, 'std': 0.14015944443389658, 'median': 414.1040444665123, 'majority': 413.8595249969512, 'minority': 413.8595249969512, 'unique': 135.0, 'histogram': [[15.0, 13.0, 12.0, 19.0, 20.0, 25.0, 10.0, 10.0, 7.0, 4.0], [413.8595249969512, 413.91725644643884, 413.97498789592646, 414.0327193454141, 414.0904507949017, 414.1481822443893, 414.205913693877, 414.2636451433646, 414.32137659285223, 414.37910804233985, 414.43683949182747]], 'valid_percent': 100.0, 'masked_pixels': 0.0, 'valid_pixels': 135.0, 'percentile_2': 413.8741860515438, 'percentile_98': 414.4011363678146}}}}
CPU times: user 6.82 s, sys: 1.39 s, total: 8.22 s
Wall time: 5min 22sstats[0]{'statistics': {'b1': {'min': 418.2305856375024,
'max': 419.41294693970116,
'mean': 418.84807499634246,
'count': 115.20000457763672,
'sum': 48251.30015691298,
'std': 0.25036812587510676,
'median': 418.7834456388373,
'majority': 418.2305856375024,
'minority': 418.2305856375024,
'unique': 135.0,
'histogram': [[3.0, 4.0, 6.0, 22.0, 41.0, 12.0, 10.0, 15.0, 9.0, 13.0],
[418.2305856375024,
418.34882176772226,
418.46705789794214,
418.585294028162,
418.7035301583819,
418.8217662886018,
418.9400024188216,
419.0582385490415,
419.1764746792614,
419.2947108094813,
419.41294693970116]],
'valid_percent': 100.0,
'masked_pixels': 0.0,
'valid_pixels': 135.0,
'percentile_2': 418.3893688605167,
'percentile_98': 419.3659042357467}},
'datetime': '2022-02-28T00:00:00+00:00'}def clean_stats(stats_json) -> pd.DataFrame:
df = pd.json_normalize(stats_json)
df.columns = [col.replace("statistics.b1.", "") for col in df.columns]
df["date"] = pd.to_datetime(df["datetime"])
return df
df = clean_stats(stats)
df.head(5)| datetime | min | max | mean | count | sum | std | median | majority | minority | unique | histogram | valid_percent | masked_pixels | valid_pixels | percentile_2 | percentile_98 | date | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 2022-02-28T00:00:00+00:00 | 418.230586 | 419.412947 | 418.848075 | 115.200005 | 48251.300157 | 0.250368 | 418.783446 | 418.230586 | 418.230586 | 135.0 | [[3.0, 4.0, 6.0, 22.0, 41.0, 12.0, 10.0, 15.0,... | 100.0 | 0.0 | 135.0 | 418.389369 | 419.365904 | 2022-02-28 00:00:00+00:00 |
| 1 | 2022-02-27T00:00:00+00:00 | 418.684755 | 420.117827 | 419.509759 | 115.200005 | 48327.526187 | 0.331645 | 419.469568 | 418.684755 | 418.684755 | 135.0 | [[4.0, 4.0, 9.0, 11.0, 29.0, 16.0, 23.0, 10.0,... | 100.0 | 0.0 | 135.0 | 418.811342 | 420.090160 | 2022-02-27 00:00:00+00:00 |
| 2 | 2022-02-26T00:00:00+00:00 | 417.776690 | 419.349191 | 418.780854 | 115.200005 | 48243.556308 | 0.284348 | 418.774780 | 417.776690 | 417.776690 | 135.0 | [[1.0, 3.0, 4.0, 7.0, 7.0, 32.0, 32.0, 21.0, 1... | 100.0 | 0.0 | 135.0 | 418.041596 | 419.329943 | 2022-02-26 00:00:00+00:00 |
| 3 | 2022-02-25T00:00:00+00:00 | 417.941315 | 419.452983 | 418.702861 | 115.200005 | 48234.571500 | 0.327788 | 418.689477 | 417.941315 | 417.941315 | 135.0 | [[6.0, 3.0, 13.0, 23.0, 21.0, 27.0, 13.0, 11.0... | 100.0 | 0.0 | 135.0 | 418.072064 | 419.359669 | 2022-02-25 00:00:00+00:00 |
| 4 | 2022-02-24T00:00:00+00:00 | 417.856048 | 419.575805 | 418.788470 | 115.200005 | 48244.433612 | 0.300634 | 418.767628 | 417.856048 | 417.856048 | 135.0 | [[3.0, 4.0, 5.0, 8.0, 30.0, 39.0, 22.0, 9.0, 9... | 100.0 | 0.0 | 135.0 | 418.033764 | 419.418546 | 2022-02-24 00:00:00+00:00 |
We can now explore the XCO₂ concentrations time series (January 1, 2015 - February 28, 2022) available for the Dallas, Texas area of the U.S. We can plot the data set using the code below:
fig = plt.figure(figsize=(20, 10))
plt.plot(
df["datetime"],
df["max"],
color="red",
linestyle="-",
linewidth=0.5,
label="CO₂ concentrations",
)
plt.legend()
plt.xlabel("Years")
plt.ylabel("CO2 concentrations ppm")
plt.title("CO₂ concentrations Values for Texas, Dallas (Jan 2015- Feb 2022)")Text(0.5, 1.0, 'CO₂ concentrations Values for Texas, Dallas (Jan 2015- Feb 2022)')
print(items[2]["properties"]["datetime"])2022-02-26T00:00:00+00:00oco2_3 = requests.get(
f"{RASTER_API_URL}/collections/{items[2]['collection']}/items/{items[2]['id']}/tilejson.json?"
f"&assets={asset_name}"
f"&color_formula=gamma+r+1.05&colormap_name={color_map}"
f"&rescale={rescale_values['min']},{rescale_values['max']}",
).json()
oco2_3{'tilejson': '2.2.0',
'version': '1.0.0',
'scheme': 'xyz',
'tiles': ['https://earth.gov/ghgcenter/api/raster/collections/oco2geos-co2-daygrid-v10r/items/oco2geos-co2-daygrid-v10r-20220226/tiles/WebMercatorQuad/{z}/{x}/{y}@1x?assets=xco2&color_formula=gamma+r+1.05&colormap_name=magma&rescale=411.7429234611336%2C423.60419320175424'],
'minzoom': 0,
'maxzoom': 24,
'bounds': [-180.3125, -90.25, 179.6875, 90.25],
'center': [-0.3125, 0.0, 0]}# Use bbox initial zoom and map
# Set up a map located w/in event bounds
aoi_map_bbox = Map(
tiles="OpenStreetMap",
location=[
30,-100
],
zoom_start=6.8,
)
map_layer = TileLayer(
tiles=oco2_3["tiles"][0],
attr="GHG", opacity = 0.7
)
map_layer.add_to(aoi_map_bbox)
aoi_map_bboxIn this notebook, we have successfully explored, analyzed, and visualized the STAC collection for OCO-2 GEOS Column CO₂ Concentrations.
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