pr2database
The protist reference database keeps widening past the rRNA gene it was built on.
A side-by-side editorial comparison of jSDM and sits — release velocity, themes, recent moves, and the top alternatives to consider.
Joint species distribution models in Gibbs-sampled C++, quiet since 2023.
jSDM fits joint species distribution models by Gibbs sampling, with the sampler written in C++ against GSL and Armadillo and exposed through binomial probit, binomial logit, Poisson log and Gaussian entry points. The 0.2 line extended it with species traits, constrained factor loadings and residual-association plots. The one entry since 2023 carries only a compare link.
An R package for satellite time series just grew a Python API.
sits classifies satellite image time series — building data cubes from cloud archives, training deep learning models on them, and producing land-cover maps. The releases here are dense feature lists in a steady 1.5.x line, and two themes recur in every one: more source collections wired in, and more of the classification pipeline made parallel or chunked. Version 1.5.3 added pysits, a Python API onto the same engine.
jSDM fits joint species distribution models by Gibbs sampling, with the sampler written in C++ against GSL and Armadillo and exposed through binomial probit, binomial logit, Poisson log and Gaussian entry points. The 0.2 line extended it with species traits, constrained factor loadings and residual-association plots. The one entry since 2023 carries only a compare link.
The package built out its model family quickly and then stopped: five of the six visible entries are stamped the same day as a backfilled archive, and the only later release says nothing about its contents. The direction the 0.2 line was heading, toward trait-mediated species effects and better convergence on latent variable models, has no visible continuation.
The feed does not support a confident prediction; the latest entry publishes no notes, so whether the package is still developing or only being kept CRAN-clean cannot be read from it.
sits classifies satellite image time series — building data cubes from cloud archives, training deep learning models on them, and producing land-cover maps. The releases here are dense feature lists in a steady 1.5.x line, and two themes recur in every one: more source collections wired in, and more of the classification pipeline made parallel or chunked. Version 1.5.3 added pysits, a Python API onto the same engine.
The package is positioning itself as the interface layer to Earth observation archives rather than as an algorithm library. Each release absorbs another provider — Planetary Computer, Digital Earth Africa and Australia, CDSE, TERRASCOPE, Open Geo Hub, PLANET — so the differentiator is coverage and the uniform cube abstraction over it. The Python API extends the same logic to the language most of that community actually works in. Alongside, the work is increasingly about scale: chunk parallelisation, multicores sampling, GPU classification, WebGL rendering.
With collections still being added release over release, expect more providers and continued performance work on the classification and regularisation paths. The open question the entries do not answer is how far pysits tracks the R API, since it appears once and is not mentioned again in later releases.
Other Infra & APIs products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either jSDM or sits.
The protist reference database keeps widening past the rRNA gene it was built on.
Composable aligned layouts, rebuilt on S7 while ggplot2 4.0 lands underneath.
Conservation planning absorbs the literature's target-setting rules as code.
An ecosystem model starts tracking carbon isotopes and land-use change.
Ten years in, US mapping splits its data out and finally adds Puerto Rico.
Fitness-tracking analysis in slow maintenance, still absorbing upstream breakage.
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. jSDM and sits are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. jSDM and sits are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Infra & APIs products to evaluate alongside.
Top jSDM alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "jSDM alternatives" section above for the current picks, or visit /alternatives/jsdm for the full list with editorial commentary on each.
Top sits alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "sits alternatives" section above for the current picks, or visit /alternatives/sits for the full list with editorial commentary on each.