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.


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install.packages("landmap")

0.0.7 by Tomislav Hengl, 2 months ago


https://github.com/envirometrix/landmap/


Report a bug at https://github.com/envirometrix/landmap/issues/


Browse source code at https://github.com/cran/landmap


Authors: Tomislav Hengl [aut, cre]


Documentation:   PDF Manual  


GPL-3 license


Imports methods, utils, parallel, matrixStats, ranger, glmnet, mlr, parallelMap, sp, rgdal, gdalUtils, raster

Suggests geoR, ParamHelpers, mda, psych, spdep, fossil, xgboost, plyr, kernlab, nnet, rjson, spatstat, maptools, maxlike, RCurl, aqp, deepnet, RSAGA, soiltexture, snowfall, plotKML, boot

System requirements: C++11, GDAL (>= 2.0.1), GEOS (>= 3.4.0), PROJ (>= 4.8.0)


Imported by plotKML.


See at CRAN