landmap: Automated Spatial Prediction using Ensemble Machine Learning

Functions and tools for spatial interpolation and/or prediction of environmental variables (points to grids) based on using Ensemble Machine Learning with geographical distances. Package also provides access to Global Environmental Layers (<https://www.OpenLandMap.org>) produced by the OpenGeoHub.org foundation and collaborators. Some functions have been migrated and adopted from the Global Soil Information Facilities package.

Version: 0.0.13
Depends: R (≥ 3.5.0)
Imports: methods, utils, parallel, matrixStats, mlr, parallelMap, sp, geoR, plyr, rgdal, gdalUtils, raster, ranger, rpart, forestError, nnet, xgboost, kernlab, glmnet, ParamHelpers, spdep, maptools
Suggests: boot, nabor, meteo, mda, psych, fossil, rjson, spatstat, spatstat.core, maxlike, RCurl, deepnet, RSAGA, plotKML
Published: 2021-10-14
Author: Tomislav Hengl [aut, cre]
Maintainer: Tomislav Hengl <tom.hengl at opengeohub.org>
BugReports: https://github.com/envirometrix/landmap/issues/
License: GPL-3
URL: https://github.com/envirometrix/landmap/
NeedsCompilation: no
SystemRequirements: C++11, GDAL (>= 2.0.1), GEOS (>= 3.4.0), PROJ (>= 4.8.0)
CRAN checks: landmap results

Downloads:

Reference manual: landmap.pdf
Package source: landmap_0.0.13.tar.gz
Windows binaries: r-devel: landmap_0.0.13.zip, r-release: landmap_0.0.13.zip, r-oldrel: landmap_0.0.11.zip
macOS binaries: r-release (arm64): landmap_0.0.11.tgz, r-release (x86_64): landmap_0.0.11.tgz, r-oldrel: landmap_0.0.11.tgz
Old sources: landmap archive

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