<?xml version="1.0" encoding="utf-8" ?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:r="https://r-universe.dev"><channel><title>james-longo.r-universe.dev</title><link>https://james-longo.r-universe.dev</link><description>Recent package updates in james-longo</description><generator>R-universe</generator><image><url>https://github.com/james-longo.png</url><title>R packages by james-longo</title><link>https://james-longo.r-universe.dev</link></image><lastBuildDate>Wed, 23 Sep 2026 11:00:49 GMT</lastBuildDate><item><title>[james-longo] AlphaSDM 0.2.0</title><author>james.longo.birds@gmail.com (James Longo)</author><description>Fits species distribution models and maps habitat
suitability at up to 10 m resolution from occurrence records
alone, using the 'AlphaEarth' Foundations satellite embeddings
(Brown et al. 2025) &lt;doi:10.48550/arXiv.2507.22291&gt;. The
embeddings, 64 values per pixel per year from a geospatial
foundation model, replace environmental layers, so none need to
be sourced or aligned. Provides tools to format occurrence
records, place pseudo-absences, train and evaluate an ensemble
of machine learning models, and export habitat-suitability
rasters. Sampling, model training and prediction all run on
'Google Earth Engine', which requires a free account for
noncommercial use.</description><link>https://github.com/r-universe/james-longo/actions/runs/37302245591</link><pubDate>Wed, 23 Sep 2026 11:00:49 GMT</pubDate><r:package>AlphaSDM</r:package><r:version>0.2.0</r:version><r:status>success</r:status><r:repository>https://james-longo.r-universe.dev</r:repository><r:upstream>https://github.com/james-longo/alphasdm</r:upstream><r:article><r:source>AlphaSDM.Rmd</r:source><r:filename>AlphaSDM.html</r:filename><r:title>Getting started with AlphaSDM</r:title><r:created>2026-09-22 21:21:53</r:created><r:modified>2026-09-23 09:50:03</r:modified></r:article></item></channel></rss>