## Description

This tool sets the RGB colour values of a LiDAR point cloud (`input`) based on the point returns. It specifically renders only-return, first-return, intermediate-return, and last-return points in different colours, storing these data in the RGB colour data of the output LiDAR file (`output`). Colourizing the points in a LiDAR point cloud based on return properties can aid with the visual inspection of point distributions, and therefore, the quality assurance/quality control (QA/QC) of LiDAR data tiles. For example, this visualization process can help to determine if there are areas of vegetation where there is insufficient coverage of ground points, perhaps due to acquisition of the data during leaf-on conditions. There is often an assumption in LiDAR data processing that the ground surface can be modelled using a subset of the only-return and last-return points (beige and blue in the image below). However, under heavy forest cover, and in particular if the data were collected during leaf-on conditions or if there is significant coverage of conifer trees, the only-return and last-return points may be poor approximations of the ground surface. This tool can help to determine the extent to which this is the case for a particular data set.

The specific colours used to render each return type can be set by the user with the `only`, `first`, `intermediate`, and `last` parameters. Each parameter takes either a red-green-blue (RGB) colour triplet, of the form `(r,g,b)`, or a hex-colour, of either form `#e6d6aa` or `0xe6d6aa` (note the `#` and `0x` prefixes used to indicate hexadecimal numbers; also either lowercase or capital letter values are acceptable).

The point RGB colour values can be blended with the intensity data to create a particularly effective visualization, further enhancing the visual interpretation of point return properties. The `intensity_blending` parameter value, which must range from 0% (no intensity blending) to 100% (all intensity), is used to set the degree of intensity/RGB blending.

Because the output file contains RGB colour data, it is possible that it will be larger than the input file. If the input file does contain valid RGB data, the output will be similarly sized, but the input colour data will be replaced in the output file with the point-return colours.

The output file can be visualized using any point cloud renderer capable of displaying point RGB information. We recommend the plas.io LiDAR renderer but many similar open-source options exist.

This tool is a convenience function and can alternatively be achieved using the modify_lidar tool with the statement:

`rgb=if(is_only, (230,214,170), if(is_last, (0,0,255), if(is_first, (0,255,0), (255,0,255))))`

The colourize_based_on_point_returns tool is however significantly faster for this operation than the modify_lidar tool because the expression above must be executed dynamically for each point.

## See Also

modify_lidar, lidar_colourize

## Function Signature

`def colourize_based_on_point_returns(self, input_lidar: Optional[Lidar], intensity_blending_amount: float = 50.0, only_ret_colour: str = "(230,214,170)", first_ret_colour:str = "(0,140,0)", intermediate_ret_colour: str = "(255,0,255)", last_ret_colour: str = "(0,0,255)") -> Optional[Lidar]: ...`

## Project Links

WbW Homepage User Manual Support WbW