License Information

Use of this function requires a license for Whitebox Workflows for Python Professional (WbW-Pro). Please visit www.whiteboxgeo.com to purchase a license.

Description

This tool can be used to create a contour (i.e. isolines of elevation values) vector coverage from an input LiDAR points data set (input). The tool works by first creating a triangulation of the input LiDAR points. The user must specify the contour interval (interval), or vertical spacing between contour lines. The smooth parameter can be used to increase or decrease the degree to which contours are smoothed. This parameter should be an odd integer value (0, 1, 3, 5...), with 0 indicating no smoothing. The tool can interpolate contours based on the LiDAR point elevation values, intensity data, or the user data field (parameter), with 'elevation' as the default parameter. LiDAR points may be excluded from the contouring process based on a number of criteria, including their return value (returns, which may be 'all', 'last', 'first'), their class value (exclude_cls), and whether they fall outside of a user-specified elevation range (minz and maxz). The optional max_triangle_edge_length parameter can be used to exclude the output of contours within areas that are sparsely populated areas of the data set, where the triangles formed by the Delaunay triangulation are too large. This is often the case within bodies of water; long and narrow triangular facets can also occur within the concave portions of the hull, or polygon enclosing, the points, when the data have an irregular shaped extent. Setting this parameter can help alleviate the problem of contouring beyond the data footprint.

Like many of the LiDAR tools, both the input and output parameters are optional. If these parameters are not specified by the user, the tool will search for all LAS files contained within the current WhiteboxTools working directory. This feature can be useful when you need to contour a large number of LiDAR tiles. This batch processing mode enables the tool to enable parallel data processing, which can significantly improve the efficiency of data conversion for datasets with many LiDAR tiles. When run in this batch mode, the output file (output) also need not be specified; the tool will instead create an output file with the same name as each input LiDAR file, but with the .shp extension.

It is important to note that contouring is better suited to well-defined surfaces (e.g. the ground surface or building heights), rather than volume features, such as vegetation, which tend to produce extremely complex contour sets. It is advisable to use this tool with last-returns and/or ground-classified point returns. If the input data set does not contain ground classification, consider pre-processing with the lidar_ground_point_filter tool.

See Also

contours_from_points, contours_from_raster, lidar_ground_point_filter

Function Signature

def lidar_contour(self, input_lidar: Optional[Lidar], contour_interval: float = 10.0, base_contour: float = 0.0, smooth: int = 5, interpolation_parameter: str = "elevation", returns_included: str = "all", excluded_classes: Optional[List[int]] = None, min_elev: float = float('-inf'), max_elev: float = float('inf'), tile_overlap: float = 0.0, max_triangle_edge_length: float = float('inf')) -> Optional[Vector]: ...

Project Links

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