`whitebox`

Tool MetadataThis vignette provides an introduction to the data sets included in
the `whitebox`

package. These data sets contain names,
arguments and other metadata for tools available in WhiteboxTools.

- Current version:
**2.3.0**

Internal data sets and functions defined in the R package correspond
to tool names available in the most recent version of WhiteboxTools.
Data sets are *not* dynamically generated from your WhiteboxTools
installation. Relatively recent versions of WhiteboxTools should be
supported backward-compatibly, though any newer functionality will not
be usable.

The first data set describes tool names in WhiteboxTools and the corresponding exported function in the R package, along with the WhiteboxTools Toolbox name and a brief description.

```
data("wbttools", package = "whitebox")
str(wbttools)
#> 'data.frame': 545 obs. of 8 variables:
#> $ tool_name : chr "AbsoluteValue" "AccumulationCurvature" "AdaptiveFilter" "Add" ...
#> $ function_name: chr "wbt_absolute_value" "wbt_accumulation_curvature" "wbt_adaptive_filter" "wbt_add" ...
#> $ toolbox_name : chr "Math and Stats Tools" "Geomorphometric Analysis" "Image Processing Tools" "Math and Stats Tools" ...
#> $ label : chr "Absolute Value" "Accumulation Curvature" "Adaptive Filter" "Add" ...
#> $ description : chr "Calculates the absolute value of every cell in a raster." "This tool calculates accumulation curvature from an input DEM." "Performs an adaptive filter on an image." "Performs an addition operation on two rasters or a raster and a constant value." ...
#> $ github : chr "https://github.com/jblindsay/whitebox-tools/blob/master/whitebox-tools-app/src/tools/math_stat_analysis/abs.rs" "Source code is unavailable due to proprietary license." "https://github.com/jblindsay/whitebox-tools/blob/master/whitebox-tools-app/src/tools/image_analysis/adaptive_filter.rs" "https://github.com/jblindsay/whitebox-tools/blob/master/whitebox-tools-app/src/tools/math_stat_analysis/add.rs" ...
#> $ book : chr "https://www.whiteboxgeo.com/manual/wbt_book/available_tools/mathand_stats_tools.html#AbsoluteValue" "https://www.whiteboxgeo.com/manual/wbt_book/available_tools/geomorphometric_analysis.html#AccumulationCurvature" "https://www.whiteboxgeo.com/manual/wbt_book/available_tools/image_processing_tools.html#AdaptiveFilter" "https://www.whiteboxgeo.com/manual/wbt_book/available_tools/mathand_stats_tools.html#Add" ...
#> $ is_extension : logi FALSE TRUE FALSE FALSE FALSE FALSE ...
#> - attr(*, "version")= chr "2.3.0"
```

The `wbttools`

data set is a data.frame with 545 tools and
7 variables

`"tool_name"`

- WhiteboxTools tool name`"function_name"`

- R function tool name`"toolbox_name"`

- WhiteboxTools toolbox name`"label"`

- WhiteboxTools tool label`"description"`

- Brief description`"github"`

- GitHub link`"book"`

- Reference manual link`"is_extension"`

- Tool is part of General Toolset Extension (GTE), as opposed to the “open core”

```
head(wbttools)
#> tool_name function_name
#> 1 AbsoluteValue wbt_absolute_value
#> 2 AccumulationCurvature wbt_accumulation_curvature
#> 3 AdaptiveFilter wbt_adaptive_filter
#> 4 Add wbt_add
#> 5 AddPointCoordinatesToTable wbt_add_point_coordinates_to_table
#> 6 AggregateRaster wbt_aggregate_raster
#> toolbox_name label
#> 1 Math and Stats Tools Absolute Value
#> 2 Geomorphometric Analysis Accumulation Curvature
#> 3 Image Processing Tools Adaptive Filter
#> 4 Math and Stats Tools Add
#> 5 Data Tools Add Point Coordinates To Table
#> 6 GIS Analysis Aggregate Raster
#> description
#> 1 Calculates the absolute value of every cell in a raster.
#> 2 This tool calculates accumulation curvature from an input DEM.
#> 3 Performs an adaptive filter on an image.
#> 4 Performs an addition operation on two rasters or a raster and a constant value.
#> 5 Modifies the attribute table of a point vector by adding fields containing each point's X and Y coordinates.
#> 6 Aggregates a raster to a lower resolution.
#> github
#> 1 https://github.com/jblindsay/whitebox-tools/blob/master/whitebox-tools-app/src/tools/math_stat_analysis/abs.rs
#> 2 Source code is unavailable due to proprietary license.
#> 3 https://github.com/jblindsay/whitebox-tools/blob/master/whitebox-tools-app/src/tools/image_analysis/adaptive_filter.rs
#> 4 https://github.com/jblindsay/whitebox-tools/blob/master/whitebox-tools-app/src/tools/math_stat_analysis/add.rs
#> 5 https://github.com/jblindsay/whitebox-tools/blob/master/whitebox-tools-app/src/tools/data_tools/add_point_coordinates_to_table.rs
#> 6 https://github.com/jblindsay/whitebox-tools/blob/master/whitebox-tools-app/src/tools/gis_analysis/aggregate_raster.rs
#> book
#> 1 https://www.whiteboxgeo.com/manual/wbt_book/available_tools/mathand_stats_tools.html#AbsoluteValue
#> 2 https://www.whiteboxgeo.com/manual/wbt_book/available_tools/geomorphometric_analysis.html#AccumulationCurvature
#> 3 https://www.whiteboxgeo.com/manual/wbt_book/available_tools/image_processing_tools.html#AdaptiveFilter
#> 4 https://www.whiteboxgeo.com/manual/wbt_book/available_tools/mathand_stats_tools.html#Add
#> 5 https://www.whiteboxgeo.com/manual/wbt_book/available_tools/data_tools.html#AddPointCoordinatesToTable
#> 6 https://www.whiteboxgeo.com/manual/wbt_book/available_tools/gis_analysis.html#AggregateRaster
#> is_extension
#> 1 FALSE
#> 2 TRUE
#> 3 FALSE
#> 4 FALSE
#> 5 FALSE
#> 6 FALSE
```

The R function naming style differs from the tool names in WhiteboxTools, but the core words are the same.

R function names are derived from the WhiteboxTools name as follows:

`PascalCase`

tool names change to`snake_case`

All R function names get the prefix

`wbt_`

For example, `StreamSlopeContinuous`

in WhiteboxTools
becomes `wbt_stream_slope_continuous()`

in R.

The second data set provides details about the available function arguments by tool name.

The `wbttoolparameters`

data set is a *data.frame*
with 2220 parameters and 13 variables:

`"tool_name"`

- WhiteboxTools tool name`"function_name"`

- R function name`"toolbox_name"`

- WhiteboxTools toolbox name`"name"`

- WhiteboxTools tool parameter name`"flags"`

- flags used to specify parameter on command line; comma-separated`"description"`

- parameter description`"default_value"`

- parameter default value, if any`"optional"`

- parameter “optional” flag; note that some combination of optional parameters may be required for certain conditions`"parameter_class"`

- parameter type`"parameter_detail"`

- parameter details; character: data type followed by colon and more specifics, For OptionList possible values, comma-separated (if defined)`"is_input"`

- logical. Classification of ‘input’ parameters`"is_output"`

- logical. Classification of ‘output’ parameters`"argument_name"`

- labels for selected subset of`"flags"`

**used as R function argument names**for`wbt_`

functions

```
head(wbttoolparameters)
#> tool_name function_name toolbox_name
#> 1 AbsoluteValue wbt_absolute_value Math and Stats Tools
#> 2 AbsoluteValue wbt_absolute_value Math and Stats Tools
#> 3 AccumulationCurvature wbt_accumulation_curvature Geomorphometric Analysis
#> 4 AccumulationCurvature wbt_accumulation_curvature Geomorphometric Analysis
#> 5 AccumulationCurvature wbt_accumulation_curvature Geomorphometric Analysis
#> 6 AccumulationCurvature wbt_accumulation_curvature Geomorphometric Analysis
#> name flags
#> 1 Input File -i,--input
#> 2 Output File -o,--output
#> 3 Input Raster DEM -i,--dem
#> 4 Output Raster Image -o,--output
#> 5 Log-transform the output? --log
#> 6 Z-factor --zfactor
#> description default_value optional
#> 1 Input raster file. <NA> FALSE
#> 2 Output raster file. <NA> FALSE
#> 3 Name of the input raster DEM file. <NA> FALSE
#> 4 Name of the output raster image file. <NA> FALSE
#> 5 Display output values using a log-scale. false TRUE
#> 6 Z conversion factor. 1.0 TRUE
#> parameter_class parameter_detail is_input is_output argument_name
#> 1 ExistingFile Raster TRUE FALSE input
#> 2 NewFile Raster FALSE TRUE output
#> 3 ExistingFile Raster TRUE FALSE dem
#> 4 NewFile Raster FALSE TRUE output
#> 5 Boolean Boolean FALSE FALSE log
#> 6 Float Float FALSE FALSE zfactor
```

Several fields in this table such as `flags`

and
`parameter_type`

are “flattened” relative to the nested
`wbt_tool_parameters()`

output.

The nested `parameter_type`

from the JSON result is
replaced with two variables in the data set:
`parameter_class`

and `parameter_details`

This parameter *data.frame* is useful to construct your own
functions with `wbt_run_tool()`

or for inspecting the types
of tools that can be run on particular data types.

```
str(wbttoolparameters, max.level = 1)
#> 'data.frame': 2220 obs. of 13 variables:
#> $ tool_name : chr "AbsoluteValue" "AbsoluteValue" "AccumulationCurvature" "AccumulationCurvature" ...
#> $ function_name : chr "wbt_absolute_value" "wbt_absolute_value" "wbt_accumulation_curvature" "wbt_accumulation_curvature" ...
#> $ toolbox_name : chr "Math and Stats Tools" "Math and Stats Tools" "Geomorphometric Analysis" "Geomorphometric Analysis" ...
#> $ name : chr "Input File" "Output File" "Input Raster DEM" "Output Raster Image" ...
#> $ flags : chr "-i,--input" "-o,--output" "-i,--dem" "-o,--output" ...
#> $ description : chr "Input raster file." "Output raster file." "Name of the input raster DEM file." "Name of the output raster image file." ...
#> $ default_value : chr NA NA NA NA ...
#> $ optional : logi FALSE FALSE FALSE FALSE TRUE TRUE ...
#> $ parameter_class : chr "ExistingFile" "NewFile" "ExistingFile" "NewFile" ...
#> $ parameter_detail: chr "Raster" "Raster" "Raster" "Raster" ...
#> $ is_input : logi TRUE FALSE TRUE FALSE FALSE FALSE ...
#> $ is_output : logi FALSE TRUE FALSE TRUE FALSE FALSE ...
#> $ argument_name : chr "input" "output" "dem" "output" ...
#> - attr(*, "version")= chr "2.3.0"
```

You will find that both `tool_name`

and
`function_name`

are present, so you can look up by whatever
is convenient.

The variable `argument_name`

is processed to be the subset
of `flags`

that corresponds to arguments to R functions,
which are denoted with `function_name`

.

To find the tools that have an “ExistingFile” argument with file type
“Raster” we can use `subset()`

.

```
head(subset(wbttoolparameters, grepl("ExistingFile", parameter_class) & grepl("Raster", parameter_detail)))
#> tool_name function_name toolbox_name
#> 1 AbsoluteValue wbt_absolute_value Math and Stats Tools
#> 3 AccumulationCurvature wbt_accumulation_curvature Geomorphometric Analysis
#> 7 AdaptiveFilter wbt_adaptive_filter Image Processing Tools
#> 12 Add wbt_add Math and Stats Tools
#> 13 Add wbt_add Math and Stats Tools
#> 16 AggregateRaster wbt_aggregate_raster GIS Analysis
#> name flags description
#> 1 Input File -i,--input Input raster file.
#> 3 Input Raster DEM -i,--dem Name of the input raster DEM file.
#> 7 Input File -i,--input Input raster file.
#> 12 Input File Or Constant Value --input1 Input raster file or constant value.
#> 13 Input File Or Constant Value --input2 Input raster file or constant value.
#> 16 Input File -i,--input Input raster file.
#> default_value optional parameter_class parameter_detail is_input
#> 1 <NA> FALSE ExistingFile Raster TRUE
#> 3 <NA> FALSE ExistingFile Raster TRUE
#> 7 <NA> FALSE ExistingFile Raster TRUE
#> 12 <NA> FALSE ExistingFileOrFloat Raster TRUE
#> 13 <NA> FALSE ExistingFileOrFloat Raster TRUE
#> 16 <NA> FALSE ExistingFile Raster TRUE
#> is_output argument_name
#> 1 FALSE input
#> 3 FALSE dem
#> 7 FALSE input
#> 12 FALSE input1
#> 13 FALSE input2
#> 16 FALSE input
```

The remainder of this vignette is tables of R function names and tool
descriptions from `wbttoolparameters`

, organized by
WhiteboxTools toolbox/extension name.

Function Name | Description |
---|---|

`wbt_add_point_coordinates_to_table()` |
Modifies the attribute table of a point vector by adding fields containing each point’s X and Y coordinates. |

`wbt_clean_vector()` |
Removes null features and lines/polygons with fewer than the required number of vertices. |

`wbt_convert_nodata_to_zero()` |
Converts nodata values in a raster to zero. |

`wbt_convert_raster_format()` |
Converts raster data from one format to another. |

`wbt_csv_points_to_vector()` |
Converts a CSV text file to vector points. |

`wbt_export_table_to_csv()` |
Exports an attribute table to a CSV text file. |

`wbt_fix_dangling_arcs()` |
This tool fixes undershot and overshot arcs, two common topological errors, in an input vector lines file. |

`wbt_join_tables()` |
Merge a vector’s attribute table with another table based on a common field. |

`wbt_lines_to_polygons()` |
Converts vector polylines to polygons. |

`wbt_merge_table_with_csv()` |
Merge a vector’s attribute table with a table contained within a CSV text file. |

`wbt_merge_vectors()` |
Combines two or more input vectors of the same ShapeType creating a single, new output vector. |

`wbt_modify_no_data_value()` |
Modifies nodata values in a raster. |

`wbt_multi_part_to_single_part()` |
Converts a vector file containing multi-part features into a vector containing only single-part features. |

`wbt_new_raster_from_base()` |
Creates a new raster using a base image. |

`wbt_polygons_to_lines()` |
Converts vector polygons to polylines. |

`wbt_print_geo_tiff_tags()` |
Prints the tags within a GeoTIFF. |

`wbt_raster_to_vector_lines()` |
Converts a raster lines features into a vector of the POLYLINE shapetype |

`wbt_raster_to_vector_points()` |
Converts a raster dataset to a vector of the POINT shapetype. |

`wbt_raster_to_vector_polygons()` |
Converts a raster dataset to a vector of the POLYGON shapetype. |

`wbt_reinitialize_attribute_table()` |
Reinitializes a vector’s attribute table deleting all fields but the feature ID (FID). |

`wbt_remove_polygon_holes()` |
Removes holes within the features of a vector polygon file. |

`wbt_remove_raster_polygon_holes()` |
Removes polygon holes, or ‘donut-holes’, from raster polygons. |

`wbt_set_nodata_value()` |
Assign the NoData value for an input image. |

`wbt_single_part_to_multi_part()` |
Converts a vector file containing multi-part features into a vector containing only single-part features. |

`wbt_vector_lines_to_raster()` |
Converts a vector containing polylines into a raster. |

`wbt_vector_points_to_raster()` |
Converts a vector containing points into a raster. |

`wbt_vector_polygons_to_raster()` |
Converts a vector containing polygons into a raster. |

Function Name | Description |
---|---|

`wbt_aggregate_raster()` |
Aggregates a raster to a lower resolution. |

`wbt_average_overlay()` |
Calculates the average for each grid cell from a group of raster images. |

`wbt_block_maximum_gridding()` |
Creates a raster grid based on a set of vector points and assigns grid values using a block maximum scheme. |

`wbt_block_minimum_gridding()` |
Creates a raster grid based on a set of vector points and assigns grid values using a block minimum scheme. |

`wbt_boundary_shape_complexity()` |
Calculates the complexity of the boundaries of raster polygons. |

`wbt_buffer_raster()` |
Maps a distance-based buffer around each non-background (non-zero/non-nodata) grid cell in an input image. |

`wbt_centroid()` |
Calculates the centroid, or average location, of raster polygon objects. |

`wbt_centroid_vector()` |
Identifies the centroid point of a vector polyline or polygon feature or a group of vector points. |

`wbt_clip()` |
Extract all the features, or parts of features, that overlap with the features of the clip vector. |

`wbt_clip_raster_to_polygon()` |
Clips a raster to a vector polygon. |

`wbt_clump()` |
Groups cells that form discrete areas, assigning them unique identifiers. |

`wbt_compactness_ratio()` |
Calculates the compactness ratio (A/P), a measure of shape complexity, for vector polygons. |

`wbt_construct_vector_tin()` |
Creates a vector triangular irregular network (TIN) for a set of vector points. |

`wbt_cost_allocation()` |
Identifies the source cell to which each grid cell is connected by a least-cost pathway in a cost-distance analysis. |

`wbt_cost_distance()` |
Performs cost-distance accumulation on a cost surface and a group of source cells. |

`wbt_cost_pathway()` |
Performs cost-distance pathway analysis using a series of destination grid cells. |

`wbt_count_if()` |
Counts the number of occurrences of a specified value in a cell-stack of rasters. |

`wbt_create_hexagonal_vector_grid()` |
Creates a hexagonal vector grid. |

`wbt_create_plane()` |
Creates a raster image based on the equation for a simple plane. |

`wbt_create_rectangular_vector_grid()` |
Creates a rectangular vector grid. |

`wbt_difference()` |
Outputs the features that occur in one of the two vector inputs but not both, i.e. no overlapping features. |

`wbt_dissolve()` |
Removes the interior, or shared, boundaries within a vector polygon coverage. |

`wbt_edge_proportion()` |
Calculate the proportion of cells in a raster polygon that are edge cells. |

`wbt_eliminate_coincident_points()` |
Removes any coincident, or nearly coincident, points from a vector points file. |

`wbt_elongation_ratio()` |
Calculates the elongation ratio for vector polygons. |

`wbt_erase()` |
Removes all the features, or parts of features, that overlap with the features of the erase vector polygon. |

`wbt_erase_polygon_from_raster()` |
Erases (cuts out) a vector polygon from a raster. |

`wbt_euclidean_allocation()` |
Assigns grid cells in the output raster the value of the nearest target cell in the input image, measured by the Shih and Wu (2004) Euclidean distance transform. |

`wbt_euclidean_distance()` |
Calculates the Shih and Wu (2004) Euclidean distance transform. |

`wbt_extend_vector_lines()` |
Extends vector lines by a specified distance. |

`wbt_extract_nodes()` |
Converts vector lines or polygons into vertex points. |

`wbt_extract_raster_values_at_points()` |
Extracts the values of raster(s) at vector point locations. |

`wbt_filter_raster_features_by_area()` |
Removes small-area features from a raster. |

`wbt_find_lowest_or_highest_points()` |
Locates the lowest and/or highest valued cells in a raster. |

`wbt_find_patch_or_class_edge_cells()` |
Finds all cells located on the edge of patch or class features. |

`wbt_heat_map()` |
Calculates a heat map, or kernel density estimation (KDE), for an input point set. |

`wbt_highest_position()` |
Identifies the stack position of the maximum value within a raster stack on a cell-by-cell basis. |

`wbt_hole_proportion()` |
Calculates the proportion of the total area of a polygon’s holes relative to the area of the polygon’s hull. |

`wbt_idw_interpolation()` |
Interpolates vector points into a raster surface using an inverse-distance weighted scheme. |

`wbt_intersect()` |
Identifies the parts of features in common between two input vector layers. |

`wbt_layer_footprint()` |
Creates a vector polygon footprint of the area covered by a raster grid or vector layer. |

`wbt_linearity_index()` |
Calculates the linearity index for vector polygons. |

`wbt_line_intersections()` |
Identifies points where the features of two vector line layers intersect. |

`wbt_lowest_position()` |
Identifies the stack position of the minimum value within a raster stack on a cell-by-cell basis. |

`wbt_max_absolute_overlay()` |
Evaluates the maximum absolute value for each grid cell from a stack of input rasters. |

`wbt_max_overlay()` |
Evaluates the maximum value for each grid cell from a stack of input rasters. |

`wbt_medoid()` |
Calculates the medoid for a series of vector features contained in a shapefile. |

`wbt_merge_line_segments()` |
Merges vector line segments into larger features. |

`wbt_min_absolute_overlay()` |
Evaluates the minimum absolute value for each grid cell from a stack of input rasters. |

`wbt_minimum_bounding_box()` |
Creates a vector minimum bounding rectangle around vector features. |

`wbt_minimum_bounding_circle()` |
Delineates the minimum bounding circle (i.e. smallest enclosing circle) for a group of vectors. |

`wbt_minimum_bounding_envelope()` |
Creates a vector axis-aligned minimum bounding rectangle (envelope) around vector features. |

`wbt_minimum_convex_hull()` |
Creates a vector convex polygon around vector features. |

`wbt_min_overlay()` |
Evaluates the minimum value for each grid cell from a stack of input rasters. |

`wbt_multiply_overlay()` |
Calculates the sum for each grid cell from a group of raster images. |

`wbt_narrowness_index()` |
Calculates the narrowness of raster polygons. |

`wbt_natural_neighbour_interpolation()` |
Creates a raster grid based on Sibson’s natural neighbour method. |

`wbt_nearest_neighbour_gridding()` |
Creates a raster grid based on a set of vector points and assigns grid values using the nearest neighbour. |

`wbt_patch_orientation()` |
Calculates the orientation of vector polygons. |

`wbt_percent_equal_to()` |
Calculates the percentage of a raster stack that have cell values equal to an input on a cell-by-cell basis. |

`wbt_percent_greater_than()` |
Calculates the percentage of a raster stack that have cell values greater than an input on a cell-by-cell basis. |

`wbt_percent_less_than()` |
Calculates the percentage of a raster stack that have cell values less than an input on a cell-by-cell basis. |

`wbt_perimeter_area_ratio()` |
Calculates the perimeter-area ratio of vector polygons. |

`wbt_pick_from_list()` |
Outputs the value from a raster stack specified by a position raster. |

`wbt_polygon_area()` |
Calculates the area of vector polygons. |

`wbt_polygonize()` |
Creates a polygon layer from two or more intersecting line features contained in one or more input vector line files. |

`wbt_polygon_long_axis()` |
Used to map the long axis of polygon features. |

`wbt_polygon_perimeter()` |
Calculates the perimeter of vector polygons. |

`wbt_polygon_short_axis()` |
Used to map the short axis of polygon features. |

`wbt_radial_basis_function_interpolation()` |
Interpolates vector points into a raster surface using a radial basis function scheme. |

`wbt_radius_of_gyration()` |
Calculates the distance of cells from their polygon’s centroid. |

`wbt_raster_area()` |
Calculates the area of polygons or classes within a raster image. |

`wbt_raster_cell_assignment()` |
Assign row or column number to cells. |

`wbt_raster_perimeter()` |
Calculates the perimeters of polygons or classes within a raster image. |

`wbt_reclass()` |
Reclassifies the values in a raster image. |

`wbt_reclass_equal_interval()` |
Reclassifies the values in a raster image based on equal-ranges. |

`wbt_reclass_from_file()` |
Reclassifies the values in a raster image using reclass ranges in a text file. |

`wbt_related_circumscribing_circle()` |
Calculates the related circumscribing circle of vector polygons. |

`wbt_shape_complexity_index()` |
Calculates overall polygon shape complexity or irregularity. |

`wbt_shape_complexity_index_raster()` |
Calculates the complexity of raster polygons or classes. |

`wbt_smooth_vectors()` |
Smooths a vector coverage of either a POLYLINE or POLYGON base ShapeType. |

`wbt_split_vector_lines()` |
Used to split a vector line coverage into even-lengthed segments. |

`wbt_split_with_lines()` |
Splits the lines or polygons in one layer using the lines in another layer. |

`wbt_sum_overlay()` |
Calculates the sum for each grid cell from a group of raster images. |

`wbt_symmetrical_difference()` |
Outputs the features that occur in one of the two vector inputs but not both, i.e. no overlapping features. |

`wbt_tin_gridding()` |
Creates a raster grid based on a triangular irregular network (TIN) fitted to vector points. |

`wbt_travelling_salesman_problem()` |
Finds approximate solutions to travelling salesman problems, the goal of which is to identify the shortest route connecting a set of locations. |

`wbt_union()` |
Splits vector layers at their overlaps, creating a layer containing all the portions from both input and overlay layers. |

`wbt_update_nodata_cells()` |
Replaces the NoData values in an input raster with the corresponding values contained in a second update layer. |

`wbt_vector_hex_binning()` |
Hex-bins a set of vector points. |

`wbt_voronoi_diagram()` |
Creates a vector Voronoi diagram for a set of vector points. |

`wbt_weighted_overlay()` |
Performs a weighted sum on multiple input rasters after converting each image to a common scale. The tool performs a multi-criteria evaluation (MCE). |

`wbt_weighted_sum()` |
Performs a weighted-sum overlay on multiple input raster images. |

Function Name | Description |
---|---|

`wbt_accumulation_curvature()` |
This tool calculates accumulation curvature from an input DEM. |

`wbt_aspect()` |
Calculates an aspect raster from an input DEM. |

`wbt_assess_route()` |
This tool assesses a route for slope, elevation, and visibility variation. |

`wbt_average_normal_vector_angular_deviation()` |
Calculates the circular variance of aspect at a scale for a DEM. |

`wbt_breakline_mapping()` |
This tool maps breaklines from an input DEM. |

`wbt_circular_variance_of_aspect()` |
Calculates the circular variance of aspect at a scale for a DEM. |

`wbt_contours_from_points()` |
Creates a contour coverage from a set of input points. |

`wbt_contours_from_raster()` |
Derives a vector contour coverage from a raster surface. |

`wbt_curvedness()` |
This tool calculates curvedness from an input DEM. |

`wbt_dem_void_filling()` |
This tool can be used to fill the void areas of a DEM using another fill DEM data set. |

`wbt_dev_from_mean_elev()` |
Calculates deviation from mean elevation. |

`wbt_difference_curvature()` |
This tool calculates difference curvature from an input DEM. |

`wbt_diff_from_mean_elev()` |
Calculates difference from mean elevation (equivalent to a high-pass filter). |

`wbt_directional_relief()` |
Calculates relief for cells in an input DEM for a specified direction. |

`wbt_downslope_index()` |
Calculates the Hjerdt et al. (2004) downslope index. |

`wbt_edge_density()` |
Calculates the density of edges, or breaks-in-slope within DEMs. |

`wbt_elev_above_pit()` |
Calculate the elevation of each grid cell above the nearest downstream pit cell or grid edge cell. |

`wbt_elev_percentile()` |
Calculates the elevation percentile raster from a DEM. |

`wbt_elev_relative_to_min_max()` |
Calculates the elevation of a location relative to the minimum and maximum elevations in a DEM. |

`wbt_elev_relative_to_watershed_min_max()` |
Calculates the elevation of a location relative to the minimum and maximum elevations in a watershed. |

`wbt_embankment_mapping()` |
Maps and/or removes road embankments from an input fine-resolution DEM. |

`wbt_exposure_towards_wind_flux()` |
Evaluates hydrologic connectivity within a DEM |

`wbt_feature_preserving_smoothing()` |
Reduces short-scale variation in an input DEM using a modified Sun et al. (2007) algorithm. |

`wbt_fetch_analysis()` |
Performs an analysis of fetch or upwind distance to an obstacle. |

`wbt_fill_missing_data()` |
Fills NoData holes in a DEM. |

`wbt_find_ridges()` |
Identifies potential ridge and peak grid cells. |

`wbt_gaussian_curvature()` |
Calculates a mean curvature raster from an input DEM. |

`wbt_gaussian_scale_space()` |
Uses the fast Gaussian approximation algorithm to produce scaled land-surface parameter measurements from an input DEM. |

`wbt_generating_function()` |
This tool calculates generating function from an input DEM. |

`wbt_geomorphons()` |
Computes geomorphon patterns. |

`wbt_hillshade()` |
Calculates a hillshade raster from an input DEM. |

`wbt_horizon_angle()` |
Calculates horizon angle (maximum upwind slope) for each grid cell in an input DEM. |

`wbt_horizontal_excess_curvature()` |
This tool calculates horizontal excess curvature from an input DEM. |

`wbt_hypsometrically_tinted_hillshade()` |
Creates an colour shaded relief image from an input DEM. |

`wbt_hypsometric_analysis()` |
Calculates a hypsometric curve for one or more DEMs. |

`wbt_local_hypsometric_analysis()` |
This tool calculates a local, neighbourhood-based hypsometric integral raster. |

`wbt_local_quadratic_regression()` |
An implementation of the constrained quadratic regression algorithm using a flexible window size described in Wood (1996). |

`wbt_map_off_terrain_objects()` |
Maps off-terrain objects in a digital elevation model (DEM). |

`wbt_max_anisotropy_dev()` |
Calculates the maximum anisotropy (directionality) in elevation deviation over a range of spatial scales. |

`wbt_max_anisotropy_dev_signature()` |
Calculates the anisotropy in deviation from mean for points over a range of spatial scales. |

`wbt_max_branch_length()` |
Lindsay and Seibert’s (2013) branch length index is used to map drainage divides or ridge lines. |

`wbt_max_difference_from_mean()` |
Calculates the maximum difference from mean elevation over a range of spatial scales. |

`wbt_max_downslope_elev_change()` |
Calculates the maximum downslope change in elevation between a grid cell and its eight downslope neighbors. |

`wbt_max_elevation_deviation()` |
Calculates the maximum elevation deviation over a range of spatial scales. |

`wbt_max_elev_dev_signature()` |
Calculates the maximum elevation deviation over a range of spatial scales and for a set of points. |

`wbt_maximal_curvature()` |
Calculates a mean curvature raster from an input DEM. |

`wbt_max_upslope_elev_change()` |
Calculates the maximum upslope change in elevation between a grid cell and its eight downslope neighbors. |

`wbt_mean_curvature()` |
Calculates a mean curvature raster from an input DEM. |

`wbt_min_downslope_elev_change()` |
Calculates the minimum downslope change in elevation between a grid cell and its eight downslope neighbors. |

`wbt_minimal_curvature()` |
Calculates a mean curvature raster from an input DEM. |

`wbt_multidirectional_hillshade()` |
Calculates a multi-direction hillshade raster from an input DEM. |

`wbt_multiscale_curvatures()` |
This tool calculates several multiscale curvatures and curvature-based indices from an input DEM. |

`wbt_multiscale_elevation_percentile()` |
Calculates surface roughness over a range of spatial scales. |

`wbt_multiscale_roughness()` |
Calculates surface roughness over a range of spatial scales. |

`wbt_multiscale_roughness_signature()` |
Calculates the surface roughness for points over a range of spatial scales. |

`wbt_multiscale_std_dev_normals()` |
Calculates surface roughness over a range of spatial scales. |

`wbt_multiscale_std_dev_normals_signature()` |
Calculates the surface roughness for points over a range of spatial scales. |

`wbt_multiscale_topographic_position_image()` |
Creates a multiscale topographic position image from three DEVmax rasters of differing spatial scale ranges. |

`wbt_num_downslope_neighbours()` |
Calculates the number of downslope neighbours to each grid cell in a DEM. |

`wbt_num_upslope_neighbours()` |
Calculates the number of upslope neighbours to each grid cell in a DEM. |

`wbt_openness()` |
This tool calculates the topographic openness index from an input DEM. |

`wbt_pennock_landform_class()` |
Classifies hillslope zones based on slope, profile curvature, and plan curvature. |

`wbt_percent_elev_range()` |
Calculates percent of elevation range from a DEM. |

`wbt_plan_curvature()` |
Calculates a plan (contour) curvature raster from an input DEM. |

`wbt_profile()` |
Plots profiles from digital surface models. |

`wbt_profile_curvature()` |
Calculates a profile curvature raster from an input DEM. |

`wbt_relative_aspect()` |
Calculates relative aspect (relative to a user-specified direction) from an input DEM. |

`wbt_relative_topographic_position()` |
Calculates the relative topographic position index from a DEM. |

`wbt_remove_off_terrain_objects()` |
Removes off-terrain objects from a raster digital elevation model (DEM). |

`wbt_ring_curvature()` |
This tool calculates ring curvature from an input DEM. |

`wbt_rotor()` |
This tool calculates rotor from an input DEM. |

`wbt_ruggedness_index()` |
Calculates the Riley et al.’s (1999) terrain ruggedness index from an input DEM. |

`wbt_sediment_transport_index()` |
Calculates the sediment transport index. |

`wbt_shadow_animation()` |
This tool creates an animated GIF of shadows based on an input DEM. |

`wbt_shadow_image()` |
This tool creates a raster of shadow areas based on an input DEM. |

`wbt_shape_index()` |
This tool calculates the shape index from an input DEM. |

`wbt_slope()` |
Calculates a slope raster from an input DEM. |

`wbt_slope_vs_aspect_plot()` |
This tool creates a slope-aspect relation plot from an input DEM. |

`wbt_slope_vs_elevation_plot()` |
Creates a slope vs. elevation plot for one or more DEMs. |

`wbt_smooth_vegetation_residual()` |
This tool can smooth the residual roughness due to vegetation cover in LiDAR DEMs. |

`wbt_spherical_std_dev_of_normals()` |
Calculates the spherical standard deviation of surface normals for a DEM. |

`wbt_standard_deviation_of_slope()` |
Calculates the standard deviation of slope from an input DEM. |

`wbt_stream_power_index()` |
Calculates the relative stream power index. |

`wbt_surface_area_ratio()` |
Calculates a the surface area ratio of each grid cell in an input DEM. |

`wbt_tangential_curvature()` |
Calculates a tangential curvature raster from an input DEM. |

`wbt_time_in_daylight()` |
Calculates the proportion of time a location is not within an area of shadow. |

`wbt_topographic_position_animation()` |
This tool creates an animated GIF of multi-scale local topographic position (elevation deviation). |

`wbt_topo_render()` |
This tool creates a pseudo-3D rendering from an input DEM, for the purpose of effective topographic visualization. |

`wbt_total_curvature()` |
Calculates a total curvature raster from an input DEM. |

`wbt_unsphericity()` |
This tool calculates the unsphericity curvature from an input DEM. |

`wbt_vertical_excess_curvature()` |
This tool calculates vertical excess curvature from an input DEM. |

`wbt_viewshed()` |
Identifies the viewshed for a point or set of points. |

`wbt_visibility_index()` |
Estimates the relative visibility of sites in a DEM. |

`wbt_wetness_index()` |
Calculates the topographic wetness index, Ln(A / tan(slope)). |

Function Name | Description |
---|---|

`wbt_average_flowpath_slope()` |
Measures the average slope gradient from each grid cell to all upslope divide cells. |

`wbt_average_upslope_flowpath_length()` |
Measures the average length of all upslope flowpaths draining each grid cell. |

`wbt_basins()` |
Identifies drainage basins that drain to the DEM edge. |

`wbt_breach_depressions()` |
Breaches all of the depressions in a DEM using Lindsay’s (2016) algorithm. This should be preferred over depression filling in most cases. |

`wbt_breach_depressions_least_cost()` |
Breaches the depressions in a DEM using a least-cost pathway method. |

`wbt_breach_single_cell_pits()` |
Removes single-cell pits from an input DEM by breaching. |

`wbt_burn_streams_at_roads()` |
Burns-in streams at the sites of road embankments. |

`wbt_d8_flow_accumulation()` |
Calculates a D8 flow accumulation raster from an input DEM or flow pointer. |

`wbt_d8_mass_flux()` |
Performs a D8 mass flux calculation. |

`wbt_d8_pointer()` |
Calculates a D8 flow pointer raster from an input DEM. |

`wbt_depth_in_sink()` |
Measures the depth of sinks (depressions) in a DEM. |

`wbt_depth_to_water()` |
This tool calculates cartographic depth-to-water (DTW) index. |

`wbt_d_inf_flow_accumulation()` |
Calculates a D-infinity flow accumulation raster from an input DEM. |

`wbt_d_inf_mass_flux()` |
Performs a D-infinity mass flux calculation. |

`wbt_d_inf_pointer()` |
Calculates a D-infinity flow pointer (flow direction) raster from an input DEM. |

`wbt_downslope_distance_to_stream()` |
Measures distance to the nearest downslope stream cell. |

`wbt_downslope_flowpath_length()` |
Calculates the downslope flowpath length from each cell to basin outlet. |

`wbt_edge_contamination()` |
Identifies grid cells within an input DEM that may be impacted by edge contamination for hydrological applications. |

`wbt_elevation_above_stream()` |
Calculates the elevation of cells above the nearest downslope stream cell. |

`wbt_elevation_above_stream_euclidean()` |
Calculates the elevation of cells above the nearest (Euclidean distance) stream cell. |

`wbt_fd8_flow_accumulation()` |
Calculates an FD8 flow accumulation raster from an input DEM. |

`wbt_fd8_pointer()` |
Calculates an FD8 flow pointer raster from an input DEM. |

`wbt_fill_burn()` |
Burns streams into a DEM using the FillBurn (Saunders, 1999) method. |

`wbt_fill_depressions()` |
Fills all of the depressions in a DEM. Depression breaching should be preferred in most cases. |

`wbt_fill_depressions_planchon_and_darboux()` |
Fills all of the depressions in a DEM using the Planchon and Darboux (2002) method. |

`wbt_fill_depressions_wang_and_liu()` |
Fills all of the depressions in a DEM using the Wang and Liu (2006) method. Depression breaching should be preferred in most cases. |

`wbt_fill_single_cell_pits()` |
Raises pit cells to the elevation of their lowest neighbour. |

`wbt_find_no_flow_cells()` |
Finds grid cells with no downslope neighbours. |

`wbt_find_parallel_flow()` |
Finds areas of parallel flow in D8 flow direction rasters. |

`wbt_flatten_lakes()` |
Flattens lake polygons in a raster DEM. |

`wbt_flood_order()` |
Assigns each DEM grid cell its order in the sequence of inundations that are encountered during a search starting from the edges, moving inward at increasing elevations. |

`wbt_flow_accumulation_full_workflow()` |
Resolves all of the depressions in a DEM, outputting a breached DEM, an aspect-aligned non-divergent flow pointer, and a flow accumulation raster. |

`wbt_flow_length_diff()` |
Calculates the local maximum absolute difference in downslope flowpath length, useful in mapping drainage divides and ridges. |

`wbt_hillslopes()` |
Identifies the individual hillslopes draining to each link in a stream network. |

`wbt_hydrologic_connectivity()` |
This tool evaluates hydrologic connectivity within a DEM |

`wbt_impoundment_size_index()` |
Calculates the impoundment size resulting from damming a DEM. |

`wbt_insert_dams()` |
Calculates the impoundment size resulting from damming a DEM. |

`wbt_isobasins()` |
Divides a landscape into nearly equal sized drainage basins (i.e. watersheds). |

`wbt_jenson_snap_pour_points()` |
Moves outlet points used to specify points of interest in a watershedding operation to the nearest stream cell. |

`wbt_longest_flowpath()` |
Delineates the longest flowpaths for a group of subbasins or watersheds. |

`wbt_low_points_on_headwater_divides()` |
This tool locates saddle points along ridges within a digital elevation model (DEM) |

`wbt_max_upslope_flowpath_length()` |
Measures the maximum length of all upslope flowpaths draining each grid cell. |

`wbt_max_upslope_value()` |
Calculates the maximum upslope value from an input values raster along flowpaths. |

`wbt_md_inf_flow_accumulation()` |
Calculates an FD8 flow accumulation raster from an input DEM. |

`wbt_num_inflowing_neighbours()` |
Computes the number of inflowing neighbours to each cell in an input DEM based on the D8 algorithm. |

`wbt_qin_flow_accumulation()` |
Calculates Qin et al. (2007) flow accumulation. |

`wbt_quinn_flow_accumulation()` |
Calculates Quinn et al. (1995) flow accumulation. |

`wbt_raise_walls()` |
Raises walls in a DEM along a line or around a polygon, e.g. a watershed. |

`wbt_rho8_flow_accumulation()` |
Calculates Fairfield and Leymarie (1991) flow accumulation. |

`wbt_rho8_pointer()` |
Calculates a stochastic Rho8 flow pointer raster from an input DEM. |

`wbt_river_centerlines()` |
Maps river centerlines from an input water raster. |

`wbt_sink()` |
Identifies the depressions in a DEM, giving each feature a unique identifier. |

`wbt_snap_pour_points()` |
Moves outlet points used to specify points of interest in a watershedding operation to the cell with the highest flow accumulation in its neighbourhood. |

`wbt_stochastic_depression_analysis()` |
Performs a stochastic analysis of depressions within a DEM. |

`wbt_strahler_order_basins()` |
Identifies Strahler-order basins from an input stream network. |

`wbt_subbasins()` |
Identifies the catchments, or sub-basin, draining to each link in a stream network. |

`wbt_trace_downslope_flowpaths()` |
Traces downslope flowpaths from one or more target sites (i.e. seed points). |

`wbt_unnest_basins()` |
Extract whole watersheds for a set of outlet points. |

`wbt_upslope_depression_storage()` |
Estimates the average upslope depression storage depth. |

`wbt_watershed()` |
Identifies the watershed, or drainage basin, draining to a set of target cells. |

Function Name | Description |
---|---|

`wbt_adaptive_filter()` |
Performs an adaptive filter on an image. |

`wbt_balance_contrast_enhancement()` |
Performs a balance contrast enhancement on a colour-composite image of multispectral data. |

`wbt_bilateral_filter()` |
A bilateral filter is an edge-preserving smoothing filter introduced by Tomasi and Manduchi (1998). |

`wbt_canny_edge_detection()` |
This tool performs a Canny edge-detection filter on an input image. |

`wbt_change_vector_analysis()` |
Performs a change vector analysis on a two-date multi-spectral dataset. |

`wbt_closing()` |
A closing is a mathematical morphology operation involving an erosion (min filter) of a dilation (max filter) set. |

`wbt_conservative_smoothing_filter()` |
Performs a conservative-smoothing filter on an image. |

`wbt_corner_detection()` |
Identifies corner patterns in boolean images using hit-and-miss pattern matching. |

`wbt_correct_vignetting()` |
Corrects the darkening of images towards corners. |

`wbt_create_colour_composite()` |
Creates a colour-composite image from three bands of multispectral imagery. |

`wbt_diff_of_gaussian_filter()` |
Performs a Difference of Gaussian (DoG) filter on an image. |

`wbt_direct_decorrelation_stretch()` |
Performs a direct decorrelation stretch enhancement on a colour-composite image of multispectral data. |

`wbt_diversity_filter()` |
Assigns each cell in the output grid the number of different values in a moving window centred on each grid cell in the input raster. |

`wbt_edge_preserving_mean_filter()` |
Performs a simple edge-preserving mean filter on an input image. |

`wbt_emboss_filter()` |
Performs an emboss filter on an image, similar to a hillshade operation. |

`wbt_evaluate_training_sites()` |
This tool can be used to inspect the overlap in spectral signatures of training sites for various classes. |

`wbt_fast_almost_gaussian_filter()` |
Performs a fast approximate Gaussian filter on an image. |

`wbt_flip_image()` |
Reflects an image in the vertical or horizontal axis. |

`wbt_gamma_correction()` |
Performs a gamma correction on an input images. |

`wbt_gaussian_contrast_stretch()` |
Performs a Gaussian contrast stretch on input images. |

`wbt_gaussian_filter()` |
Performs a Gaussian filter on an image. |

`wbt_generalize_classified_raster()` |
Generalizes a raster containing class or object features by removing small features. |

`wbt_generalize_with_similarity()` |
Generalizes a raster containing class or object features by removing small features using similarity criteria of neighbouring features. |

`wbt_high_pass_bilateral_filter()` |
Performs a high-pass bilateral filter, by differencing an input image by the bilateral filter by Tomasi and Manduchi (1998). |

`wbt_high_pass_filter()` |
Performs a high-pass filter on an input image. |

`wbt_high_pass_median_filter()` |
Performs a high pass median filter on an input image. |

`wbt_histogram_equalization()` |
Performs a histogram equalization contrast enhancement on an image. |

`wbt_histogram_matching()` |
Alters the statistical distribution of a raster image matching it to a specified PDF. |

`wbt_histogram_matching_two_images()` |
Alters the cumulative distribution function of a raster image to that of another image. |

`wbt_ihs_to_rgb()` |
Converts intensity, hue, and saturation (IHS) images into red, green, and blue (RGB) images. |

`wbt_image_segmentation()` |
Performs a region-growing based segmentation on a set of multi-spectral images. |

`wbt_image_slider()` |
This tool creates an image slider from two input images. |

`wbt_image_stack_profile()` |
Plots an image stack profile (i.e. signature) for a set of points and multispectral images. |

`wbt_integral_image()` |
Transforms an input image (summed area table) into its integral image equivalent. |

`wbt_k_nearest_mean_filter()` |
A k-nearest mean filter is a type of edge-preserving smoothing filter. |

`wbt_laplacian_filter()` |
Performs a Laplacian filter on an image. |

`wbt_laplacian_of_gaussian_filter()` |
Performs a Laplacian-of-Gaussian (LoG) filter on an image. |

`wbt_lee_sigma_filter()` |
Performs a Lee (Sigma) smoothing filter on an image. |

`wbt_line_detection_filter()` |
Performs a line-detection filter on an image. |

`wbt_line_thinning()` |
Performs line thinning a on Boolean raster image; intended to be used with the RemoveSpurs tool. |

`wbt_majority_filter()` |
Assigns each cell in the output grid the most frequently occurring value (mode) in a moving window centred on each grid cell in the input raster. |

`wbt_maximum_filter()` |
Assigns each cell in the output grid the maximum value in a moving window centred on each grid cell in the input raster. |

`wbt_mean_filter()` |
Performs a mean filter (low-pass filter) on an input image. |

`wbt_median_filter()` |
Performs a median filter on an input image. |

`wbt_min_dist_classification()` |
Performs a supervised minimum-distance classification using training site polygons and multi-spectral images. |

`wbt_minimum_filter()` |
Assigns each cell in the output grid the minimum value in a moving window centred on each grid cell in the input raster. |

`wbt_min_max_contrast_stretch()` |
Performs a min-max contrast stretch on an input greytone image. |

`wbt_mosaic()` |
Mosaics two or more images together. |

`wbt_mosaic_with_feathering()` |
Mosaics two images together using a feathering technique in overlapping areas to reduce edge-effects. |

`wbt_normalized_difference_index()` |
Calculate a normalized-difference index (NDI) from two bands of multispectral image data. |

`wbt_olympic_filter()` |
Performs an olympic smoothing filter on an image. |

`wbt_opening()` |
An opening is a mathematical morphology operation involving a dilation (max filter) of an erosion (min filter) set. |

`wbt_panchromatic_sharpening()` |
Increases the spatial resolution of image data by combining multispectral bands with panchromatic data. |

`wbt_parallelepiped_classification()` |
Performs a supervised parallelepiped classification using training site polygons and multi-spectral images. |

`wbt_percentage_contrast_stretch()` |
Performs a percentage linear contrast stretch on input images. |

`wbt_percentile_filter()` |
Performs a percentile filter on an input image. |

`wbt_piecewise_contrast_stretch()` |
Performs a piecewise contrast stretch on an input image. |

`wbt_prewitt_filter()` |
Performs a Prewitt edge-detection filter on an image. |

`wbt_range_filter()` |
Assigns each cell in the output grid the range of values in a moving window centred on each grid cell in the input raster. |

`wbt_remove_spurs()` |
Removes the spurs (pruning operation) from a Boolean line image; intended to be used on the output of the LineThinning tool. |

`wbt_resample()` |
Resamples one or more input images into a destination image. |

`wbt_rgb_to_ihs()` |
Converts red, green, and blue (RGB) images into intensity, hue, and saturation (IHS) images. |

`wbt_roberts_cross_filter()` |
Performs a Robert’s cross edge-detection filter on an image. |

`wbt_scharr_filter()` |
Performs a Scharr edge-detection filter on an image. |

`wbt_sigmoidal_contrast_stretch()` |
Performs a sigmoidal contrast stretch on input images. |

`wbt_sobel_filter()` |
Performs a Sobel edge-detection filter on an image. |

`wbt_split_colour_composite()` |
Splits an RGB colour composite image into separate multispectral images. |

`wbt_standard_deviation_contrast_stretch()` |
Performs a standard-deviation contrast stretch on input images. |

`wbt_standard_deviation_filter()` |
Assigns each cell in the output grid the standard deviation of values in a moving window centred on each grid cell in the input raster. |

`wbt_thicken_raster_line()` |
Thickens single-cell wide lines within a raster image. |

`wbt_tophat_transform()` |
Performs either a white or black top-hat transform on an input image. |

`wbt_total_filter()` |
Performs a total filter on an input image. |

`wbt_unsharp_masking()` |
An image sharpening technique that enhances edges. |

`wbt_user_defined_weights_filter()` |
Performs a user-defined weights filter on an image. |

`wbt_write_function_memory_insertion()` |
Performs a write function memory insertion for single-band multi-date change detection. |

Function Name | Description |
---|---|

`wbt_ascii_to_las()` |
Converts one or more ASCII files containing LiDAR points into LAS files. |

`wbt_classify_buildings_in_lidar()` |
Reclassifies a LiDAR points that lie within vector building footprints. |

`wbt_classify_lidar()` |
Classify points within a LiDAR point cloud based on point properties. |

`wbt_classify_overlap_points()` |
Classifies or filters LAS points in regions of overlapping flight lines. |

`wbt_clip_lidar_to_polygon()` |
Clips a LiDAR point cloud to a vector polygon or polygons. |

`wbt_colourize_based_on_class()` |
Sets the RGB values of a LiDAR point cloud based on the point classification values. |

`wbt_colourize_based_on_point_returns()` |
Sets the RGB values of a LiDAR point cloud based on the point returns. |

`wbt_erase_polygon_from_lidar()` |
Erases (cuts out) a vector polygon or polygons from a LiDAR point cloud. |

`wbt_filter_lidar()` |
Filters points within a LiDAR point cloud based on point properties. |

`wbt_filter_lidar_classes()` |
Removes points in a LAS file with certain specified class values. |

`wbt_filter_lidar_scan_angles()` |
Removes points in a LAS file with scan angles greater than a threshold. |

`wbt_find_flightline_edge_points()` |
Identifies points along a flightline’s edge in a LAS file. |

`wbt_flightline_overlap()` |
Reads a LiDAR (LAS) point file and outputs a raster containing the number of overlapping flight-lines in each grid cell. |

`wbt_height_above_ground()` |
Normalizes a LiDAR point cloud, providing the height above the nearest ground-classified point. |

`wbt_individual_tree_detection()` |
Identifies points in a LiDAR point cloud that are associated with the tops of individual trees. |

`wbt_las_to_ascii()` |
Converts one or more LAS files into ASCII text files. |

`wbt_las_to_laz()` |
This tool converts one or more LAS files into the LAZ format |

`wbt_las_to_multipoint_shapefile()` |
Converts one or more LAS files into MultipointZ vector Shapefiles. When the input parameter is not specified, the tool grids all LAS files contained within the working directory. |

`wbt_las_to_shapefile()` |
Converts one or more LAS files into a vector Shapefile of POINT ShapeType. |

`wbt_las_to_zlidar()` |
Converts one or more LAS files into the zlidar compressed LiDAR data format. |

`wbt_laz_to_las()` |
This tool converts one or more LAZ files into the LAS format |

`wbt_lidar_block_maximum()` |
Creates a block-maximum raster from an input LAS file. When the input/output parameters are not specified, the tool grids all LAS files contained within the working directory. |

`wbt_lidar_block_minimum()` |
Creates a block-minimum raster from an input LAS file. When the input/output parameters are not specified, the tool grids all LAS files contained within the working directory. |

`wbt_lidar_classify_subset()` |
Classifies the values in one LiDAR point cloud that correspond with points in a subset cloud. |

`wbt_lidar_colourize()` |
Adds the red-green-blue colour fields of a LiDAR (LAS) file based on an input image. |

`wbt_lidar_contour()` |
This tool creates a vector contour coverage from an input LiDAR point file. |

`wbt_lidar_digital_surface_model()` |
Creates a top-surface digital surface model (DSM) from a LiDAR point cloud. |

`wbt_lidar_eigenvalue_features()` |
Calculate eigenvalue-based metrics from a LiDAR point cloud. |

`wbt_lidar_elevation_slice()` |
Outputs all of the points within a LiDAR (LAS) point file that lie between a specified elevation range. |

`wbt_lidar_ground_point_filter()` |
Identifies ground points within LiDAR dataset using a slope-based method. |

`wbt_lidar_hex_binning()` |
Hex-bins a set of LiDAR points. |

`wbt_lidar_hillshade()` |
Calculates a hillshade value for points within a LAS file and stores these data in the RGB field. |

`wbt_lidar_histogram()` |
Creates a histogram of LiDAR data. |

`wbt_lidar_idw_interpolation()` |
Interpolates LAS files using an inverse-distance weighted (IDW) scheme. When the input/output parameters are not specified, the tool interpolates all LAS files contained within the working directory. |

`wbt_lidar_info()` |
Prints information about a LiDAR (LAS) dataset, including header, point return frequency, and classification data and information about the variable length records (VLRs) and geokeys. |

`wbt_lidar_join()` |
Joins multiple LiDAR (LAS) files into a single LAS file. |

`wbt_lidar_kappa_index()` |
Performs a kappa index of agreement (KIA) analysis on the classifications of two LAS files. |

`wbt_lidar_nearest_neighbour_gridding()` |
Grids LiDAR files using nearest-neighbour scheme. When the input/output parameters are not specified, the tool grids all LAS files contained within the working directory. |

`wbt_lidar_point_density()` |
Calculates the spatial pattern of point density for a LiDAR data set. When the input/output parameters are not specified, the tool grids all LAS files contained within the working directory. |

`wbt_lidar_point_return_analysis()` |
This tool performs a quality control check on the return values of points in a LiDAR file. |

`wbt_lidar_point_stats()` |
Creates several rasters summarizing the distribution of LAS point data. When the input/output parameters are not specified, the tool works on all LAS files contained within the working directory. |

`wbt_lidar_ransac_planes()` |
Performs a RANSAC analysis to identify points within a LiDAR point cloud that belong to linear planes. |

`wbt_lidar_rbf_interpolation()` |
Interpolates LAS files using a radial basis function (RBF) scheme. When the input/output parameters are not specified, the tool interpolates all LAS files contained within the working directory. |

`wbt_lidar_remove_duplicates()` |
Removes duplicate points from a LiDAR data set. |

`wbt_lidar_remove_outliers()` |
Removes outliers (high and low points) in a LiDAR point cloud. |

`wbt_lidar_rooftop_analysis()` |
Identifies roof segments in a LiDAR point cloud. |

`wbt_lidar_segmentation()` |
Segments a LiDAR point cloud based on differences in the orientation of fitted planar surfaces and point proximity. |

`wbt_lidar_segmentation_based_filter()` |
Identifies ground points within LiDAR point clouds using a segmentation based approach. |

`wbt_lidar_shift()` |
Shifts the x,y,z coordinates of a LiDAR file. |

`wbt_lidar_sibson_interpolation()` |
This tool interpolates one or more LiDAR tiles using Sibson’s natural neighbour method. |

`wbt_lidar_thin()` |
Thins a LiDAR point cloud, reducing point density. |

`wbt_lidar_thin_high_density()` |
Thins points from high density areas within a LiDAR point cloud. |

`wbt_lidar_tile()` |
Tiles a LiDAR LAS file into multiple LAS files. |

`wbt_lidar_tile_footprint()` |
Creates a vector polygon of the convex hull of a LiDAR point cloud. When the input/output parameters are not specified, the tool works with all LAS files contained within the working directory. |

`wbt_lidar_tin_gridding()` |
Creates a raster grid based on a Delaunay triangular irregular network (TIN) fitted to LiDAR points. |

`wbt_lidar_tophat_transform()` |
Performs a white top-hat transform on a Lidar dataset; as an estimate of height above ground, this is useful for modelling the vegetation canopy. |

`wbt_modify_lidar()` |
Modify points within a LiDAR point cloud based on point properties. |

`wbt_normalize_lidar()` |
Normalizes a LiDAR point cloud. |

`wbt_normal_vectors()` |
Calculates normal vectors for points within a LAS file and stores these data (XYZ vector components) in the RGB field. |

`wbt_recover_flightline_info()` |
Associates LiDAR points by their flightlines. |

`wbt_select_tiles_by_polygon()` |
Copies LiDAR tiles overlapping with a polygon into an output directory. |

`wbt_sort_lidar()` |
Sorts LiDAR points based on their properties. |

`wbt_split_lidar()` |
Splits LiDAR points up into a series of new files based on their properties. |

`wbt_zlidar_to_las()` |
Converts one or more zlidar files into the LAS data format. |

Function Name | Description |
---|---|

`wbt_dbscan()` |
Performs a DBSCAN-based unsupervised clustering operation. |

`wbt_k_means_clustering()` |
Performs a k-means clustering operation on a multi-spectral dataset. |

`wbt_knn_classification()` |
Performs a supervised k-nearest neighbour classification using training site polygons/points and predictor rasters. |

`wbt_knn_regression()` |
Performs a supervised k-nearest neighbour regression using training site points and predictor rasters. |

`wbt_logistic_regression()` |
Performs a logistic regression analysis using training site polygons/points and predictor rasters. |

`wbt_modified_k_means_clustering()` |
Performs a modified k-means clustering operation on a multi-spectral dataset. |

`wbt_random_forest_classification()` |
Performs a supervised random forest classification using training site polygons/points and predictor rasters. |

`wbt_random_forest_regression()` |
Performs a random forest regression analysis using training site data and predictor rasters. |

`wbt_svm_classification()` |
Performs an SVM binary classification using training site polygons/points and multiple input images. |

`wbt_svm_regression()` |
Performs a supervised SVM regression analysis using training site points and predictor rasters. |

Function Name | Description |
---|---|

`wbt_absolute_value()` |
Calculates the absolute value of every cell in a raster. |

`wbt_add()` |
Performs an addition operation on two rasters or a raster and a constant value. |

`wbt_and()` |
Performs a logical AND operator on two Boolean raster images. |

`wbt_anova()` |
Performs an analysis of variance (ANOVA) test on a raster dataset. |

`wbt_arc_cos()` |
Returns the inverse cosine (arccos) of each values in a raster. |

`wbt_arcosh()` |
Returns the inverse hyperbolic cosine (arcosh) of each values in a raster. |

`wbt_arc_sin()` |
Returns the inverse sine (arcsin) of each values in a raster. |

`wbt_arc_tan()` |
Returns the inverse tangent (arctan) of each values in a raster. |

`wbt_arsinh()` |
Returns the inverse hyperbolic sine (arsinh) of each values in a raster. |

`wbt_artanh()` |
Returns the inverse hyperbolic tangent (arctanh) of each values in a raster. |

`wbt_atan2()` |
Returns the 2-argument inverse tangent (atan2). |

`wbt_attribute_correlation()` |
Performs a correlation analysis on attribute fields from a vector database. |

`wbt_attribute_correlation_neighbourhood_analysis()` |
Performs a correlation on two input vector attributes within a neighbourhood search windows. |

`wbt_attribute_histogram()` |
Creates a histogram for the field values of a vector’s attribute table. |

`wbt_attribute_scattergram()` |
Creates a scattergram for two field values of a vector’s attribute table. |

`wbt_ceil()` |
Returns the smallest (closest to negative infinity) value that is greater than or equal to the values in a raster. |

`wbt_conditional_evaluation()` |
Performs a conditional evaluation (if-then-else) operation on a raster. |

`wbt_conditioned_latin_hypercube()` |
Implements conditioned Latin Hypercube sampling. |

`wbt_cos()` |
Returns the cosine (cos) of each values in a raster. |

`wbt_cosh()` |
Returns the hyperbolic cosine (cosh) of each values in a raster. |

`wbt_crispness_index()` |
Calculates the Crispness Index, which is used to quantify how crisp (or conversely how fuzzy) a probability image is. |

`wbt_cross_tabulation()` |
Performs a cross-tabulation on two categorical images. |

`wbt_cumulative_distribution()` |
Converts a raster image to its cumulative distribution function. |

`wbt_decrement()` |
Decreases the values of each grid cell in an input raster by 1.0 (see also InPlaceSubtract). |

`wbt_divide()` |
Performs a division operation on two rasters or a raster and a constant value. |

`wbt_equal_to()` |
Performs a equal-to comparison operation on two rasters or a raster and a constant value. |

`wbt_exp()` |
Returns the exponential (base e) of values in a raster. |

`wbt_exp2()` |
Returns the exponential (base 2) of values in a raster. |

`wbt_floor()` |
Returns the largest (closest to positive infinity) value that is less than or equal to the values in a raster. |

`wbt_greater_than()` |
Performs a greater-than comparison operation on two rasters or a raster and a constant value. |

`wbt_image_autocorrelation()` |
Performs Moran’s I analysis on two or more input images. |

`wbt_image_correlation()` |
Performs image correlation on two or more input images. |

`wbt_image_correlation_neighbourhood_analysis()` |
Performs image correlation on two input images neighbourhood search windows. |

`wbt_image_regression()` |
Performs image regression analysis on two input images. |

`wbt_increment()` |
Increases the values of each grid cell in an input raster by 1.0. (see also InPlaceAdd) |

`wbt_in_place_add()` |
Performs an in-place addition operation (input1 += input2). |

`wbt_in_place_divide()` |
Performs an in-place division operation (input1 /= input2). |

`wbt_in_place_multiply()` |
Performs an in-place multiplication operation (input1 *= input2). |

`wbt_in_place_subtract()` |
Performs an in-place subtraction operation (input1 -= input2). |

`wbt_integer_division()` |
Performs an integer division operation on two rasters or a raster and a constant value. |

`wbt_inverse_pca()` |
This tool performs an inverse principal component analysis on a series of input component images. |

`wbt_is_no_data()` |
Identifies NoData valued pixels in an image. |

`wbt_kappa_index()` |
Performs a kappa index of agreement (KIA) analysis on two categorical raster files. |

`wbt_ks_test_for_normality()` |
Evaluates whether the values in a raster are normally distributed. |

`wbt_less_than()` |
Performs a less-than comparison operation on two rasters or a raster and a constant value. |

`wbt_list_unique_values()` |
Lists the unique values contained in a field within a vector’s attribute table. |

`wbt_list_unique_values_raster()` |
Lists the unique values contained in a field within a vector’s attribute table. |

`wbt_ln()` |
Returns the natural logarithm of values in a raster. |

`wbt_log10()` |
Returns the base-10 logarithm of values in a raster. |

`wbt_log2()` |
Returns the base-2 logarithm of values in a raster. |

`wbt_max()` |
Performs a MAX operation on two rasters or a raster and a constant value. |

`wbt_min()` |
Performs a MIN operation on two rasters or a raster and a constant value. |

`wbt_modulo()` |
Performs a modulo operation on two rasters or a raster and a constant value. |

`wbt_multiply()` |
Performs a multiplication operation on two rasters or a raster and a constant value. |

`wbt_negate()` |
Changes the sign of values in a raster or the 0-1 values of a Boolean raster. |

`wbt_not()` |
Performs a logical NOT operator on two Boolean raster images. |

`wbt_not_equal_to()` |
Performs a not-equal-to comparison operation on two rasters or a raster and a constant value. |

`wbt_or()` |
Performs a logical OR operator on two Boolean raster images. |

`wbt_paired_sample_t_test()` |
Performs a 2-sample K-S test for significant differences on two input rasters. |

`wbt_phi_coefficient()` |
This tool performs a binary classification accuracy assessment. |

`wbt_power()` |
Raises the values in grid cells of one rasters, or a constant value, by values in another raster or constant value. |

`wbt_principal_component_analysis()` |
Performs a principal component analysis (PCA) on a multi-spectral dataset. |

`wbt_quantiles()` |
Transforms raster values into quantiles. |

`wbt_random_field()` |
Creates an image containing random values. |

`wbt_random_sample()` |
Creates an image containing randomly located sample grid cells with unique IDs. |

`wbt_raster_calculator()` |
Performs a complex mathematical operations on one or more input raster images on a cell-to-cell basis. |

`wbt_raster_histogram()` |
Creates a histogram from raster values. |

`wbt_raster_summary_stats()` |
Measures a rasters min, max, average, standard deviation, num. non-nodata cells, and total. |

`wbt_reciprocal()` |
Returns the reciprocal (i.e. 1 / z) of values in a raster. |

`wbt_rescale_value_range()` |
Performs a min-max contrast stretch on an input greytone image. |

`wbt_root_mean_square_error()` |
Calculates the RMSE and other accuracy statistics. |

`wbt_round()` |
Rounds the values in an input raster to the nearest integer value. |

`wbt_sin()` |
Returns the sine (sin) of each values in a raster. |

`wbt_sinh()` |
Returns the hyperbolic sine (sinh) of each values in a raster. |

`wbt_square()` |
Squares the values in a raster. |

`wbt_square_root()` |
Returns the square root of the values in a raster. |

`wbt_subtract()` |
Performs a differencing operation on two rasters or a raster and a constant value. |

`wbt_tan()` |
Returns the tangent (tan) of each values in a raster. |

`wbt_tanh()` |
Returns the hyperbolic tangent (tanh) of each values in a raster. |

`wbt_to_degrees()` |
Converts a raster from radians to degrees. |

`wbt_to_radians()` |
Converts a raster from degrees to radians. |

`wbt_trend_surface()` |
Estimates the trend surface of an input raster file. |

`wbt_trend_surface_vector_points()` |
Estimates a trend surface from vector points. |

`wbt_truncate()` |
Truncates the values in a raster to the desired number of decimal places. |

`wbt_turning_bands_simulation()` |
Creates an image containing random values based on a turning-bands simulation. |

`wbt_two_sample_ks_test()` |
Performs a 2-sample K-S test for significant differences on two input rasters. |

`wbt_wilcoxon_signed_rank_test()` |
Performs a 2-sample K-S test for significant differences on two input rasters. |

`wbt_xor()` |
Performs a logical XOR operator on two Boolean raster images. |

`wbt_zonal_statistics()` |
Extracts descriptive statistics for a group of patches in a raster. |

`wbt_z_scores()` |
Standardizes the values in an input raster by converting to z-scores. |

Function Name | Description |
---|---|

`wbt_reconcile_multiple_headers()` |
This tool adjusts the crop yield values for data sets collected with multiple headers or combines. |

`wbt_recreate_pass_lines()` |
This tool can be used to approximate the harvester pass lines from yield points. |

`wbt_remove_field_edge_points()` |
This tool can be used to remove, or flag, most of the points along the edges from a crop yield data set. |

`wbt_yield_filter()` |
Filters crop yield values of point data derived from combine harvester yield monitors. |

`wbt_yield_map()` |
This tool can be used to create a segmented-vector polygon yield map from a set of harvester points. |

`wbt_yield_normalization()` |
This tool can be used to normalize the yield points for a field. |

Function Name | Description |
---|---|

`wbt_distance_to_outlet()` |
Calculates the distance of stream grid cells to the channel network outlet cell. |

`wbt_extract_streams()` |
Extracts stream grid cells from a flow accumulation raster. |

`wbt_extract_valleys()` |
Identifies potential valley bottom grid cells based on local topolography alone. |

`wbt_farthest_channel_head()` |
Calculates the distance to the furthest upstream channel head for each stream cell. |

`wbt_find_main_stem()` |
Finds the main stem, based on stream lengths, of each stream network. |

`wbt_hack_stream_order()` |
Assigns the Hack stream order to each tributary in a stream network. |

`wbt_horton_stream_order()` |
Assigns the Horton stream order to each tributary in a stream network. |

`wbt_length_of_upstream_channels()` |
Calculates the total length of channels upstream. |

`wbt_long_profile()` |
Plots the stream longitudinal profiles for one or more rivers. |

`wbt_long_profile_from_points()` |
Plots the longitudinal profiles from flow-paths initiating from a set of vector points. |

`wbt_rasterize_streams()` |
Rasterizes vector streams based on Lindsay (2016) method. |

`wbt_raster_streams_to_vector()` |
Converts a raster stream file into a vector file. |

`wbt_remove_short_streams()` |
Removes short first-order streams from a stream network. |

`wbt_repair_stream_vector_topology()` |
This tool resolves topological errors and inconsistencies associated with digitized vector streams. |

`wbt_shreve_stream_magnitude()` |
Assigns the Shreve stream magnitude to each link in a stream network. |

`wbt_strahler_stream_order()` |
Assigns the Strahler stream order to each link in a stream network. |

`wbt_stream_link_class()` |
Identifies the exterior/interior links and nodes in a stream network. |

`wbt_stream_link_identifier()` |
Assigns a unique identifier to each link in a stream network. |

`wbt_stream_link_length()` |
Estimates the length of each link (or tributary) in a stream network. |

`wbt_stream_link_slope()` |
Estimates the average slope of each link (or tributary) in a stream network. |

`wbt_stream_slope_continuous()` |
Estimates the slope of each grid cell in a stream network. |

`wbt_topological_stream_order()` |
Assigns each link in a stream network its topological order. |

`wbt_tributary_identifier()` |
Assigns a unique identifier to each tributary in a stream network. |

`wbt_vector_stream_network_analysis()` |
This tool performs common stream network analysis operations on an input vector stream file. |

Function Name | Description |
---|---|

`wbt_install_wb_extension()` |
Use to install a Whitebox extension product. |

`wbt_launch_wb_runner()` |
Opens the Whitebox Runner application. |