Whitebox Workflows for Python
Whitebox Workflows for Python Pro
Whitebox Worfklows for Python Pro (WbW-Pro) contains all of the same functions as the standard WbW product and adds the 65+ tools found in the Whitebox Toolset Extension (WTE), allowing users to access this powerful functionality in the same great geo-processing environment.
Like all of our products, WbW-Pro has transparent pricing. A single-user license is $400USD and each additional user is only $60 more. We also offer an academic discount for qualified customers.
WbW-Pro List of Tools
WbW-Pro contains each of the functions listed below. Click on each function name to view the help documentation, parameters, and instructions on how to use it. Please note, although you are able to install the the WbW-Pro using the same convenient pip install as WbW, you will not be able to use it until you purchase a valid license.
- DEM Processing Tools
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accumulation_curvature
Calculates accumulation curvature from an input DEM. -
assess_route
Assesses a route for slope, elevation, and visibility variation. -
breakline_mapping
Automatically maps breaklines from an input DEM. -
curvedness
Calculates curvedness from an input DEM. -
dem_void_filling
Fills the void areas of a DEM using another fill DEM data set. -
difference_curvature
Calculates difference curvature from an input DEM. -
generating_function
Calculates generating function from an input DEM. -
horizontal_excess_curvature
Calculates horizontal excess curvature from an input DEM. -
local_hypsometric_analysis
Calculates the hypsometric integral from the elevation distribution contained within the local neighbourhood surrounding each grid cell in an input DEM. -
low_points_on_headwater_divides
Locates saddle points along ridges within a DEM. -
multiscale_curvatures
Calculates several multiscale curvatures and curvature-based indices from an input DEM. -
openness
Calculates the topographic openness index from an input DEM. -
ring_curvature
Calculates ring curvature from an input DEM. -
rotor
Calculates rotor from an input DEM. -
shadow_animation
Creates an animated GIF of shadows based on an input DEM. -
shadow_image
Creates a raster of shadow areas based on an input DEM. -
shape_index
Calculates shape index from an input DEM. -
slope_vs_aspect_plot
Creates a slope-aspect relation plot from an input DEM. -
topographic_position_animation
Creates an animated GIF of multi-scale local topographic position. -
topo_render
Creates a pseudo-3D rendering from an input DEM, for the purpose of effective topographic visualization. -
unsphericity
Calculates unsphericity curvature from an input DEM. -
vertical_excess_curvature
Calculates vertical excess curvature from an input DEM. - LiDAR Tools
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classify_lidar
Classifies LiDAR point clouds into ground, building, and vegetation points. -
colourize_based_on_class
Sets the RGB values of a LiDAR point cloud based on the point classification values. -
colourize_based_on_point_returns
Sets the RGB values of a LiDAR point cloud based on the point return values. -
filter_lidar
Filters points within a LiDAR point cloud based on point properties. -
lidar_contour
Creates a vector contour coverage from an input LiDAR point file. -
lidar_eigenvalue_features
Calculate eigenvalue-based metrics from a LiDAR point cloud, including linearity, planarity, sphericity, omnivariance, eigentropy, and others. -
lidar_point_return_analysis
Performs a quality control check on the return values of points in a LiDAR file. -
lidar_sibson_interpolation
Interpolates one or more LiDAR tiles using Sibson's natural neighbour method. -
modify_lidar
Modify points within a LiDAR point cloud based on point properties. -
recover_flightline_info
Associates LiDAR points by their flightlines. -
smooth_vegetation_residual
Smoothes the residual roughness due to vegetation cover in LiDAR DEMs. -
sort_lidar
Sorts the points in a LiDAR file based on point properties. -
split_lidar
Splits LiDAR points up into a series of new files based on their properties. - Machine Learning Tools
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dbscan
Performs a DBSCAN-based unsupervised clustering operation. -
knn_classification
Performs a k-nearest neighbour classification using training site polygons/points and predictor rasters. -
knn_regression
Performs a k-nearest neighbour regression analysis using training site points and predictor rasters. -
logistic_regression
Performs a logistic regression analysis using training site polygons/points and predictor rasters. -
random_forest_classification
Performs a random forest classification using training site polygons/points and predictor rasters. -
random_forest_regression
Performs a random forest regression analysis using training site points and predictor rasters. -
svm_classification
Performs a SVM classification using training site polygons/points and predictor rasters. -
svm_regression
Performs a SVM regression analysis using training site points and predictor rasters. - Hydrological and Hydrographic Tools
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depth_to_water
Calculates cartographic depth-to-water (DTW) index. -
hydrologic_connectivity
Calculates two indices related to hydrologic connectivity within catchments, the downslope unsaturated length and the upslope disconnected saturated area. -
river_centerlines
Maps river centerlines from an input water raster. - Remote Sensing Tools
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canny_edge_detection
Performs a Canny edge-detection filter on an input image. -
evaluate_training_sites
Inspects the overlap in spectral signatures of training sites for various classes. -
generalize_classified_raster
Generalizes a raster containing class or object features by removing small features. -
generalize_with_similarity
Generalizes a raster containing class features by reassigning the identifier values of small features to those of neighbouring features based on similarity in spectral space. -
image_segmentation
Performs a region-growing based segmentation on a set of multi-spectral images. -
image_slider
Creates an image slider from two input images. -
inverse_pca
Performs an inverse principal component analysis on a series of input component images. -
min_dist_classification
Performs a supervised minimum-distance classification using training sites and multi-spectral images. -
parallelepiped_classification
Performs a supervised parallelepiped classification using training sites and multi-spectral images. -
phi_coefficient
Performs a binary classification accuracy assessment. -
piecewise_contrast_stretch
Performs a piecewise contrast stretch on an input image. - GIS Tools
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fix_dangling_arcs
Fixes undershot and overshot arcs, two common topological errors, in an input vector lines file. -
remove_raster_polygon_holes
Remove raster polygon holes or "donut-holes", from raster polygons. - Agriculture Tools
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reconcile_multiple_headers
Adjusts the crop yield values for data sets collected with multiple headers or combines. -
remove_field_edge_points
Remove or flag most of the points along the edges from a crop yield data set. -
recreate_pass_lines
Approximates the harvester pass lines from yield points. -
yield_filter
Filters crop yield values of point data derived from combine harvester yield monitors. -
yield_map
Creates a segmented-vector polygon yield map from a set of harvester points. -
yield_normalization
Normalizes the yield points for a field.