Introduction

coincident simplifies access to a curated set of datasets of relevance to NASA STV studies. It is designed to simplify working with disparate metadata for areal and satellite remote sensing datasets. coincident relies heavily on GeoPandas in that metadata records are always returned as GeoDataFrame objects, and most methods are written to operate either on entire dataframes or single rows within a dataframe.

Dataset aliases

import coincident

coincident.datasets.aliases

Unified search function

the coincident package provides a search() method that has the same syntax regardless of which dataset you are searching. Behind the scenes, polygons intersecting your area of interest are efficiently located and returned as a geodataframe.

aoi = gpd.read_file(
    "https://raw.githubusercontent.com/unitedstates/districts/refs/heads/gh-pages/states/CO/shape.geojson"
)
gf = coincident.search(
    dataset="3dep",
    intersects=aoi,
    datetime=["2018", "2024"],
)
gf.explore(column="workunit", popup=True)

Convenience functions

coincident also provides a number of convenience functions, some of which only pertain to specific datasets. For example, loading raster imagery via Xarray or creating visualizations of browse imagery. Refer to the API Docs for a listing of functions.