Package: mlr3spatial 0.7.0

Marc Becker

mlr3spatial: Support for Spatial Objects Within the 'mlr3' Ecosystem

Extends the 'mlr3' ML framework with methods for spatial objects. Data storage and prediction are supported for packages 'terra', 'raster' and 'stars'.

Authors:Marc Becker [aut, cre], Patrick Schratz [aut]

mlr3spatial_0.7.0.tar.gz
mlr3spatial_0.7.0.zip(r-4.7)mlr3spatial_0.7.0.zip(r-4.6)mlr3spatial_0.7.0.zip(r-4.5)
mlr3spatial_0.7.0.tgz(r-4.6-any)mlr3spatial_0.7.0.tgz(r-4.5-any)
mlr3spatial_0.7.0.tar.gz(r-4.7-any)mlr3spatial_0.7.0.tar.gz(r-4.6-any)
mlr3spatial_0.7.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
mlr3spatial/json (API)

# Install 'mlr3spatial' in R:

install.packages('mlr3spatial', repos = c('https://mlr-org.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/mlr-org/mlr3spatial/issues

Pkgdown/docs site:https://mlr3spatial.mlr-org.com

Datasets:

leipzig - Leipzig Land Cover Task

On CRAN:

mlr3 raster-prediction spatial spatial-modelling

8.06 score 44 stars 52 scripts 2.1k downloads 30 exports 38 dependencies

Last updated from:4e7b917c92 (on v0.7.0). Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	312
source / vignettes	OK	237
linux-release-x86_64	OK	276
macos-release-arm64	OK	255
macos-oldrel-arm64	OK	208
windows-devel	OK	230
windows-release	OK	214
windows-oldrel	OK	240
wasm-release	OK	160

Exports:as_data_backend.RasterBrick as_data_backend.RasterStack as_data_backend.sf as_data_backend.SpatRaster as_data_backend.stars as_task_classif_st as_task_classif_st.data.frame as_task_classif_st.DataBackend as_task_classif_st.sf as_task_classif_st.TaskClassifST as_task_classif_st.TaskRegrST as_task_regr_st as_task_regr_st.data.frame as_task_regr_st.DataBackend as_task_regr_st.sf as_task_regr_st.TaskClassifST as_task_regr_st.TaskRegrST block_size DataBackendRaster DataBackendVector factor_layer generate_stack mask_stack numeric_layer predict_spatial sample_stack TaskClassifST TaskRegrST weights_layer write_raster

Dependencies:backports checkmate class classInt cli codetools data.table DBI digest e1071 evaluate future future.apply globals KernSmooth lgr listenv MASS mirai mlbench mlr3 mlr3measures mlr3misc nanonext palmerpenguins paradox parallelly proxy PRROC R6 Rcpp rlang s2 sf terra units uuid wk

Benchmark Parallel Predictions

Preparations | Benchmark

Rendered frombenchmark.Rmdusingknitr::rmarkdown

Last update: 2026-06-11
Started: 2021-08-11

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
mlr3spatial: Support for Spatial Objects Within the 'mlr3' Ecosystem	mlr3spatial-package mlr3spatial
Coerce to spatial DataBackend	as_data_backend.RasterBrick as_data_backend.RasterStack as_data_backend.sf as_data_backend.SpatRaster as_data_backend.stars
Convert to a Spatiotemporal Classification Task	as_task_classif_st as_task_classif_st.data.frame as_task_classif_st.DataBackend as_task_classif_st.sf as_task_classif_st.TaskClassifST as_task_classif_st.TaskRegrST
Convert to a Spatiotemporal Regression Task	as_task_regr_st as_task_regr_st.data.frame as_task_regr_st.DataBackend as_task_regr_st.sf as_task_regr_st.TaskClassifST as_task_regr_st.TaskRegrST
DataBackend for Raster Objects	DataBackendRaster
DataBackend for Vector Objects	DataBackendVector
Leipzig Land Cover Task	leipzig mlr_tasks_leipzig
Predict on Spatial Objects with mlr3 Learners	predict_spatial
Spatiotemporal Classification Task	TaskClassifST
Spatiotemporal Regression Task	TaskRegrST