This tool can be used to create a bare-earth DEM from a fine-resolution digital surface model. The tool is typically applied to LiDAR DEMs which frequently contain numerous off-terrain objects (OTOs) such as buildings, trees and other vegetation, cars, fences and other anthropogenic objects. The algorithm works by finding and removing steep-sided peaks within the DEM. All peaks within a sub-grid, with a dimension of the user-specified maximum OTO size (`filter`), in pixels, are identified and removed. Each of the edge cells of the peaks are then examined to see if they have a slope that is less than the user-specified minimum OTO edge slope (slope) and a back-filling procedure is used. This ensures that OTOs are distinguished from natural topographic features such as hills. The DEM is preprocessed using a white top-hat transform, such that elevations are normalized for the underlying ground surface.

Note that this tool is appropriate to apply to rasterized LiDAR DEMs. Use the lidar_ground_point_filter tool to remove or classify OTOs within a LiDAR point-cloud.

## Reference

J.B. Lindsay (2018) A new method for the removal of off-terrain objects from LiDAR-derived raster surface models. Available online, DOI: 10.13140/RG.2.2.21226.62401

## See Also

map_off_terrain_objects, tophat_transform, lidar_ground_point_filter

## Function Signature

`def remove_off_terrain_objects(self, dem: Raster, filter_size: int = 11, slope_threshold: float = 15.0) -> Raster: ...`

## Project Links

WbW Homepage User Manual Support WbW