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Comparison · Analytics
FedData vs mlr3spatial
A side-by-side editorial comparison of FedData and mlr3spatial — release velocity, themes, recent moves, and the top alternatives to consider.
FedData vs mlr3spatial: at a glance
What is FedData?
FedData has spent two major versions migrating US federal geodata off R's retiring spatial stack.
FedData downloads and standardises US federal geospatial datasets — NLCD, NHD, NED, SSURGO, Daymet, GHCN, PAD-US, NASS — into consistent R objects. Two breaking majors define the current package: 3.0.0 moved returns to sf and raster and pulled data from cloud-optimised GeoTIFFs, and 4.0.0 finished the job by dropping sp and raster entirely for terra and sf. Recent releases are dataset refreshes, most recently PAD-US 4.0.
What is mlr3spatial?
Raster prediction in mlr3 finally returns class probabilities, not just hard labels.
mlr3spatial connects mlr3 learners to raster and vector spatial data, handling chunked prediction over large rasters through DataBackendRaster. Development is slow and fix-heavy: most releases in the last two years were compatibility work against mlr3 and paradox rather than new capability. 0.7.0 is the exception.
FedData vs mlr3spatial: editorial side-by-side
FedData
0.0ANALYTICS
FedData has spent two major versions migrating US federal geodata off R's retiring spatial stack.
◆ Current state
FedData downloads and standardises US federal geospatial datasets — NLCD, NHD, NED, SSURGO, Daymet, GHCN, PAD-US, NASS — into consistent R objects. Two breaking majors define the current package: 3.0.0 moved returns to sf and raster and pulled data from cloud-optimised GeoTIFFs, and 4.0.0 finished the job by dropping sp and raster entirely for terra and sf. Recent releases are dataset refreshes, most recently PAD-US 4.0.
◆ Where it's heading
The package tracks two moving targets at once: the R spatial stack, which it has now fully migrated onto terra and sf, and the federal agencies whose URLs, file naming and hosting keep shifting. With the dependency migration finished, releases have shrunk to single-dataset updates such as annual NLCD and PAD-US 4.0, which suggests the structural work is done and the ongoing cost is data-source maintenance.
◆ Prediction
Expect continued small releases pinned to new vintages of the underlying federal datasets, plus fixes when an agency moves or reformats a source; no further dependency-level upheaval is visible in these entries.
mlr3spatial
0.0ANALYTICS
Raster prediction in mlr3 finally returns class probabilities, not just hard labels.
◆ Current state
mlr3spatial connects mlr3 learners to raster and vector spatial data, handling chunked prediction over large rasters through DataBackendRaster. Development is slow and fix-heavy: most releases in the last two years were compatibility work against mlr3 and paradox rather than new capability. 0.7.0 is the exception.
◆ Where it's heading
The package tracks the mlr3 core rather than leading it — 0.5.0 and 0.6.1 exist to absorb upstream changes in paradox and mlr3. Against that background, 0.7.0 adding probability predictions to predict_spatial() is the first genuine capability increase in a while, arriving alongside two DataBackendRaster fixes for multi-band sources and similarly-named layers. Cadence is roughly one release per year.
◆ Prediction
Given the pattern, the next release is more likely to be compatibility work against a new mlr3 or terra version than another feature; further raster-backend edge cases around layer naming are the visible loose end.
Alternatives to FedData and mlr3spatial
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 FedData or mlr3spatial.
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logrx
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lobstr
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GSODR
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giscoR
giscoR's 1.0 moved its dataset index into the cache, so new Eurostat releases arrive without a package update.
See all FedData alternatives → · See all mlr3spatial alternatives →
Recent activity from FedData and mlr3spatial
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agomlr3spatialpredict_spatial() gains probability predictions
- 10mo agomlr3spatialCompatibility with mlr3 1.2.0
- 1y agomlr3spatialError on conflicting X/Y columns in sf objects
- 1y agoFedDataget_padus() updated to PAD-US 4.0
- 1y agoFedDataAnnual NLCD access added; get_nass() retired
- 2y agomlr3spatialCompatibility with paradox 1.0.0
- 2y agoFedDatasp and raster dropped; everything returns terra or sf ⚡
- 3y agoFedDataGHCN moves to https; NHD handles empty and odd geometries
- 3y agomlr3spatialUse terra::inMemory() instead of the @ptr slot
- 3y agoFedDataAll raster writing moves to terra
- 3y agomlr3spatialspatial_predict() accepts stars, sf and Raster* inputs
- 3y agoFedDataVersion 3 rebuilds on sf and cloud-optimised GeoTIFFs ⚡
Frequently asked questions
What is the difference between FedData and mlr3spatial?
They serve adjacent needs but don't currently overlap on shipped themes. FedData and mlr3spatial 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 FedData better than mlr3spatial?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. FedData and mlr3spatial 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 FedData?
Top FedData alternatives in Analytics are ranked by recent ship velocity. Browse the "FedData alternatives" section above for the current picks, or visit /alternatives/feddata for the full list with editorial commentary on each.
What are the best alternatives to mlr3spatial?
Top mlr3spatial alternatives in Analytics are ranked by recent ship velocity. Browse the "mlr3spatial alternatives" section above for the current picks, or visit /alternatives/mlr3spatial for the full list with editorial commentary on each.