Use of this function requires a license for Whitebox Workflows for Python Professional (WbW-Pro). Please visit www.whiteboxgeo.com to purchase a license.
Raw airborne LiDAR data are collected along flightlines and multiple flightlines are typically merged into square tiles to simplify data handling and processing. Commonly the Point Source ID attribute is used to store information about the origin flightline of each point. However, sometimes this information is lost (e.g. during data format conversion) or is omitted from some data sets. This tool can be used to identify groups of points within a LiDAR file (input
) that belong to the same flightline.
The tool works by sorting points based on their timestamp and then identifying points for which the time difference from the previous point is greater than a user-specified maximum time difference (max_time_diff
), which are deemed to be the start of a different flightline. The operational assumption is that the time between consecutive points within a flightline is usually quite small (usually a fraction of a second), while the time between points in different flightlines is often relatively large (consider the aircraft turning time needed to take multiple passes of the study area). By default the maximum time difference is set to 5.0 seconds, although it may be necessary to increase this value depending on the characteristics of a particular data set.
The tool works on individual LiDAR tiles and the flightline identifiers will range from 0 to the number of flightlines detected within the tile, minus one. Therefore, the flightline identifier created by this tool will not extend beyond the boundaries of the tile and into adjacent tiles. That is, a flightline that extends across multiple adjacent LiDAR tiles may have different flightline identifiers used in each tile. The identifiers are intended to discriminate between flighlines within a single file. The flightline identifier value can be optionally assigned to the Point Source ID point attribute (pt_src_id
), the User Data point attribute (user_data
), and the red-green-blue point colour data (rgb
) within the output file (output
). At least one of these output options must be selected and it is possible to select multiple output options. Notice that if the input file contains any information within the selected output fields, the original information will be over-written, and therefore lost--of course, it will remain unaltered within the input file, which this tool does not modify. If the input file does not contain RGB colour data and the rgb
output option is selected, the output file point format will be altered from the input file to accommodate the addition of RGB colour data. Flightlines are assigned random colours. The LAS User Data point attribute is stored as a single byte and, therefore, if this output option is selected and the input file contains more than 256 flightlines, the tool will assign the same flightline identifier to more than one flightline. It is very rare for this condition to be the case in a typical 1 km-square tiles. The Point Source ID attribute is stored as a 16-bit integer and can therefore store 65,536 unique flightline identifiers.
Outputting flightline information within the colour data point attribute can be useful for visualizing areas of flightline overlap within a file. This can be an important quality assurance/quality control (QA/QC) step after acquiring a new LiDAR data set.
Please note that because this tool sorts points by their timestamps, the order of points in the output file may not match that of the input file.
flightline_overlap, find_flightline_edge_points, LidarSortByTime
def recover_flightline_info(self, input: Lidar, max_time_diff: float = 5.0, pt_src_id: bool = False, user_data: bool = False, rgb: bool = False) -> Lidar: ...