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Comparison · Analytics
inbospatial vs spmodel
A side-by-side editorial comparison of inbospatial and spmodel — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
inbospatial vs spmodel: at a glance
What is inbospatial?
A thin R wrapper over Flemish geospatial services, adding one standard at a time
inbospatial gives R users direct access to Flemish and Belgian government spatial services without hand-writing request URLs. Three releases over three years have built it up service by service: WMS and WMTS tile shorthands and projection-distortion utilities first, then the Flanders digital elevation model, and now OGC API Features querying plus layer discovery for WCS services. Much of each release is hardening the MHT-file parsing that these services return.
What is spmodel?
Spatial regression in R, adding block kriging and then tuning the numerics underneath it
spmodel fits spatial linear and generalised linear models, for both point-referenced and areal data, with prediction and diagnostics attached. Block prediction arrived in 0.11.0 and the releases since have refined it. The most recent release changes optimiser behaviour: the default Nelder-Mead relative stopping tolerance tightens from 1e-4 to 1e-6 to reduce convergence on local rather than global maxima.
inbospatial vs spmodel: editorial side-by-side
inbospatial
0.0ANALYTICS
A thin R wrapper over Flemish geospatial services, adding one standard at a time
◆ Current state
inbospatial gives R users direct access to Flemish and Belgian government spatial services without hand-writing request URLs. Three releases over three years have built it up service by service: WMS and WMTS tile shorthands and projection-distortion utilities first, then the Flanders digital elevation model, and now OGC API Features querying plus layer discovery for WCS services. Much of each release is hardening the MHT-file parsing that these services return.
◆ Where it's heading
The package grows by absorbing one more service standard per release rather than by adding abstraction. The 0.1.0 additions point the same way — get_feature_ogc() covers a newer OGC standard alongside the existing WCS and WFS paths, and get_wcs_layers() addresses the practical problem that you cannot query a coverage without first knowing what layers exist. Release cadence is slow and driven by which service the maintainers needed next.
◆ Prediction
Expect the next release to add another regional service endpoint or extend OGC API Features coverage, on a timescale of a year or more given the gaps between the three releases so far.
spmodel
0.0ANALYTICS
Spatial regression in R, adding block kriging and then tuning the numerics underneath it
◆ Current state
spmodel fits spatial linear and generalised linear models, for both point-referenced and areal data, with prediction and diagnostics attached. Block prediction arrived in 0.11.0 and the releases since have refined it. The most recent release changes optimiser behaviour: the default Nelder-Mead relative stopping tolerance tightens from 1e-4 to 1e-6 to reduce convergence on local rather than global maxima.
◆ Where it's heading
Two threads run in parallel. The first is expanding what can be predicted — point predictions, then areal averages over a region via block kriging, then better accuracy and efficiency for that path as the block size default moved from 1000 to 4000 in 0.12.0. The second is numerical trustworthiness, and it is unusually prominent here: a range-constraint option for stability in 0.9.0, a corrected log determinant of the fixed effects in the restricted log likelihood in 0.11.0, a cloud semivariogram that had been doubling the semivariance fixed in 0.11.1, and now a tighter optimiser tolerance. Several of these silently changed results before they were caught.
◆ Prediction
Expect the maintainers to keep publishing explicit reproduction instructions alongside numerical default changes, as 0.13.0 does by documenting the `control = list(reltol = 1e-4)` escape hatch. The entries give no signal of expansion beyond the current model families.
Alternatives to inbospatial and spmodel
Other Analytics 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 inbospatial or spmodel.
tidytransit
tidytransit tracks the GTFS spec as it grows, one reader and one router feature at a time.
oblicubes
A tiny grid renderer for oblique-projection cubes, complete since its first release.
biocro
BioCro swapped an unstable iteration for real root finders, changing what its crop models compute.
redist
redist keeps rewriting the sampler underneath a district-drawing API it has held stable since 4.0.
epiflows
epiflows has shipped four releases in eight years, none of which changed the code.
See all inbospatial alternatives → · See all spmodel alternatives →
Recent activity from inbospatial and spmodel
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 2mo agospmodelTighter optimiser tolerance to avoid local maxima
- 4mo agoinbospatialOGC API Features querying and WCS layer discovery arrive
- 6mo agospmodelEmpirical autocovariance function and better block kriging accuracy
- 9mo agospmodelCloud semivariogram doubling fixed; geometry warnings added
- 1y agospmodelBlock kriging for areal averages and their uncertainty ⚡
- 1y agospmodelRobust semivariogram and new covariance types for areal models
- 1y agoinbospatialFlanders digital elevation model becomes queryable
- 1y agospmodelRange constraint option and redefined covariance type names
- 2y agoinbospatialWMS and WMTS shorthands plus projection distortion utilities
Frequently asked questions
What is the difference between inbospatial and spmodel?
Both compete on the same themes — r-package — within Analytics. inbospatial and spmodel 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.
Is inbospatial better than spmodel?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. inbospatial and spmodel 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 Analytics products to evaluate alongside.
What are the best alternatives to inbospatial?
Top inbospatial alternatives in Analytics are ranked by recent ship velocity. Browse the "inbospatial alternatives" section above for the current picks, or visit /alternatives/inbospatial for the full list with editorial commentary on each.
What are the best alternatives to spmodel?
Top spmodel alternatives in Analytics are ranked by recent ship velocity. Browse the "spmodel alternatives" section above for the current picks, or visit /alternatives/spmodel for the full list with editorial commentary on each.