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| buffer.dist | Derive buffer distances for a list of points |
| buffer.dist-method | Derive buffer distances for a list of points |
| cookfarm | The Cook Agronomy Farm data set |
| download.landgis | Access and download layers from OpenLandMap.org (LandGIS data service) |
| edgeroi | The Edgeroi Data Set |
| edgeroi.grids | The Edgeroi Data Set |
| edgeroi.grids100 | The Edgeroi Data Set |
| fit.vgmModel | Fit variogram using point data |
| fit.vgmModel-method | Fit variogram using point data |
| getSpatialTiles | Split a Spatial object into tiles |
| getSpatialTiles-method | Estimate a tiling system |
| getSpatialTiles-method | Split a Spatial object into tiles |
| isis | ISRIC Soil Information System |
| landgis.tables | OpenLandMap list of GeoTIFFs global mosaics |
| landmap | landmap: Automated Spatial Prediction using Ensemble Machine Learning |
| makeTiles | Make a tiling system from a bounding box |
| model.data | Overlay points and grids and prepare regression matrix |
| munsell | Standard color palettes for soil properties and classes |
| predict.spLearner | Predict using spLearner at new locations |
| print.spLearner | Print object of type 'spLearner' |
| sample.grid | Sample spatial points by grids |
| sample.grid-method | Sample spatial points by grids |
| search.landgis | Search for available landgis layers |
| sic1997 | The SIC 1997 Data Set |
| soil.classes | Soil classification tables |
| soil.legends | Standard color palettes for soil properties and classes |
| soil.vars | Standard color palettes for soil properties and classes |
| SpatialComponents-class | A class for gridded components derived using the 'spc' method |
| SpatialMemberships-class | A class for membership maps derived using the 'fkmeans' classification |
| spc | Generate Principal Components using SpatialPixelsDataFrame object |
| spc-method | Generate Principal Components using SpatialPixelsDataFrame object |
| spfkm | Fit a supervised fuzzy kmeans model and predict memberships |
| spfkm-method | Fit a supervised fuzzy kmeans model and predict memberships |
| spmultinom | Fits a multinomial logistic regression to spatial data |
| spmultinom-method | Fits a multinomial logistic regression to spatial data |
| spsample.prob | Estimate occurrence probabilities of a sampling plan (points) |
| spsample.prob-method | Estimate occurrence probabilities of a sampling plan (points) |
| tile | Tile spatial layers |
| tile-method | Tile spatial layers |
| train.spLearner | Train a spatial prediction and/or interpolation model using Ensemble Machine Learning |
| train.spLearner-method | Train a spatial prediction and/or interpolation model using Ensemble Machine Learning |
| train.spLearner.matrix | Train a spatial prediction and/or interpolation model using Ensemble Machine Learning from a regression/classification matrix |
| TT2tri | Soil texture class to texture fractions conversion |
| tune.spLearner | Optimize spLearner by fine-tuning parameters and running feature selection |
| tune.spLearner-method | Optimize spLearner by fine-tuning parameters and running feature selection |
| USDA.TT.im | Probability density for texture triangle |