Exploring an ItemCollection

Let’s load an ItemCollection of Landsat 8 scenes from the Planetary Computer STAC and preview them with stacmap.explore.

[1]:

import stacmap
import pystac_client

[2]:

catalog = pystac_client.Client.open("https://planetarycomputer.microsoft.com/api/stac/v1")

aoi = {"type": "Polygon", "coordinates": [[
    [-112.2068359375, 42.41050500280784],
    [-112.2068359375, 39.25270077697571],
    [-107.9880859375, 39.25270077697571],
    [-107.9880859375, 42.41050500280784],
    [-112.2068359375, 42.41050500280784]
]]}

items = catalog.search(
    collections=["landsat-8-c2-l2"],
    intersects=aoi,
    datetime="2019-06-01/2019-06-10"
).get_all_items()

Calling stacmap.explore with a STAC Collection* will preview the item footprints on an interactive map. Hover over each footprint to see its STAC metadata.

*Currently supported STAC-like types are: pystac.Catalog, pystac.ItemCollection, pystac.Item, collection dictionaries, item dictionaries, and lists of item dictionaries.

[5]:

stacmap.explore(items)

[5]:

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Color-Coding

Footprints can be color-coded based on STAC properties using the prop parameter. The default colormap can be replaced with any colorbrewer name using cmap. Additional color maps are supported if matplotlib is installed.

Continuous Properties

By default, numeric properties are colored continuously and given continuous legends. Color map bounds are calculated automatically, but can be overriden by providing vmin and vmax arguments.

[15]:

stacmap.explore(items, prop="view:sun_elevation", cmap="Reds")

[15]:

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Categorical Properties

Non-numeric properties are treated categorically by default, with a color assigned to each unique value. You can force a numerical field to plot categorically using categorical=True.

[13]:

stacmap.explore(items, prop="proj:epsg", categorical=True)

[13]:

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Search Extents

Pass a bounding box to bbox or a GeoJSON geometry to intersects to overlay your search bounds.

[14]:

stacmap.explore(items, prop="landsat:wrs_path", intersects=aoi)

[14]:

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