point-collocation
Point-based lat/lon/time matchups against cloud-hosted NASA EarthData granules.
Key Features
- Search — find granules that cover your points using NASA Earthdata (
earthaccess) - Plan — preview point-to-granule routing before committing to a full extraction
- Matchup — extract variables at each (lat, lon, time) location in one call
- Grid & Swath — works with L3/gridded (1-D lat/lon) and L2/swath (2-D lat/lon) data
Quick Install
Available on PyPI.
Minimal Example
import earthaccess
import point_collocation as pc
import pandas as pd
earthaccess.login()
df = pd.DataFrame({
"lat": [34.5, 35.1],
"lon": [-120.3, -119.8],
"time": pd.to_datetime(["2023-06-01", "2023-06-02"]),
})
p = pc.plan(
df,
data_source="earthaccess",
source_kwargs={"short_name": "PACE_OCI_L3M_RRS", "granule_name": "*.DAY.*.4km.*"},
)
p.summary()
out = pc.matchup(p, geometry="grid", variables=["Rrs"])
print(out)
Navigation
- Installation — full install options
- Quickstart — end-to-end example for gridded (L3) data
- More Examples — L2 swath data, multi-file, diagnostics
- API Reference — auto-generated from source docstrings
- Contributing — dev setup, tests, local docs preview