agribound 1.0.0 is a major release. Most of it is not new functionality but correctness: an audit of 0.1.3 found defects that changed what the engines received and what the pipeline returned, and 1.0.0 fixes them. If you have results from agribound 0.1.x, please read the list of affected results before reusing them.
Historical post
This post describes agribound 0.1.3 and is kept as it was published,
except that Jeremy Rapp's name now links to the ORCID record (the
Michigan State directory page it linked to no longer exists).
Several statements in it no longer hold for agribound 1.0, and some
0.1.x results were affected by defects fixed in 1.0.0 (see the
v1.0.0 release post, the
migration guide and the
CHANGELOG).
The AOI file examples/data/small_aoi.geojson in the examples below is
a placeholder for your own AOI; it is not in the repository. For the
1.0 API, see the FTW Polygon Query guide.
Agribound v0.1.3 adds a data-access helper for the published Fields of The World (FTW) global field-boundary polygons. Instead of running FTW inference end-to-end, you can now pull pre-computed FTW predictions for any area of interest with a single function call -- backed by a PyArrow GeoParquet reader against the public Source Cooperative dataset.
This is agribound's second community contribution from Jeremy Rapp at the Department of Earth and Environmental Sciences, Michigan State University -- following his USGS NAIP Plus contribution in v0.1.2.
Historical post
This post describes agribound 0.1.x and is kept as it was published,
except for these changes made in 1.0.0: a comparison with other tools was
removed; the statement that the New Mexico linework "approaches the
quality of manual human digitization", for which no evaluation was made,
was removed; the gallery sentence now links to the archived 0.1.x
gallery and no longer says it covered nine regions, five satellites and
all engines (it had ten study areas and no GeoAI example); the manuscript
title in the citation was updated (see the note there); and links were
updated: the images now point to assets/gallery_0.1x/, the TESSERA
post is named and linked through the TESSERA blog index, and Jeremy
Rapp's name links to the ORCID record (the Michigan State directory page
it linked to no longer exists).
Several statements in it no longer hold for agribound 1.0, and some
0.1.x results were affected by defects fixed in 1.0.0 (see the
v1.0.0 release post, the
migration guide and the
CHANGELOG).
We are excited to announce the public release of agribound, a Python package that unifies seven complementary approaches to agricultural field boundary delineation into a single, reproducible pipeline. Whether you are working with 1 m NAIP imagery over U.S. croplands or 10 m Sentinel-2 composites anywhere in the world, agribound lets you go from raw satellite data to clean, vectorized field boundary polygons in a single function call.
