Create interactive maps of STAC items and collections without the heavy dependencies and boilerplate of geopandas.GeoDataFrame.explore.
- 🗺️ Explore STAC item footprints
- 🌈 Color-code items by properties
- 🖼️ Preview item thumbnails
- 🪶 Lightweight dependencies (just
foliumandpystac)
$ pip install stacmapstacmap.explore creates an interactive Folium map from STAC items or collections.
import stacmap
from pystac_client import Client
# Find Landsat Collection 2 scenes over an area of interest
catalog = Client.open("https://landsatlook.usgs.gov/stac-server")
items = catalog.search(
bbox=[-120.9519, 37.2455, -113.4812, 45.1025],
collections=["landsat-c2l2-srby"],
datetime="2019-08-01/2019-08-03"
).get_all_items()
# Plot the items on an interactive map, color-coded by cloud cover
stacmap.explore(items, prop="eo:cloud_cover")Check out the docs for details or try out an interactive notebook in Binder.
Let's look at a simple example to see how stacmap simplifies plotting a STAC collection and search bounds over geopandas.
First, we'll load our STAC items:
from pystac_client import Client
catalog = pystac_client.Client.open("https://planetarycomputer.microsoft.com/api/stac/v1")
bbox = (-67.008753, -9.96445, -65.615556, -8.57408)
items = catalog.search(
collections=["sentinel-2-l2a"],
bbox=bbox,
datetime="2019-06-01/2019-06-10"
).get_all_items()Now we'll create an interactive map that shows our items and our bounding box.
| stacmap | geopandas |
|---|---|
!pip install stacmap
import stacmap
stacmap.explore(
items,
prop="eo:cloud_cover",
bbox=bbox
) |
!pip install geopandas folium mapclassify matplotlib
import geopandas as gpd
import shapely
import folium
gdf = gpd.GeoDataFrame.from_features(
items.to_dict(),
crs="EPSG:4326"
)
bbox_geom = shapely.geometry.mapping(shapely.geometry.box(*bbox))
bbox_layer = folium.GeoJson(bbox_geom)
m = gdf.explore(column="eo:cloud_cover")
bbox_layer.add_to(m)
m |
Users coming from geopandas can check out the transition guide for tips on switching to the stacmap API.