This tool performs a kappa index of agreement (KIA) analysis on the classification values of two LiDAR (LAS) files. The output report HTML file should be displayed automatically but can also be displayed afterwards in any web browser. As a measure of overall classification accuracy, the KIA is more robust than the percent agreement calculation because it takes into account the agreement occurring by random chance. In addition to the KIA, the tool will output the producer's and user's accuracy, the overall accuracy, and the error matrix. The KIA is often used as a means of assessing the accuracy of an image classification analysis; however the `LidarKappaIndex` tool performs the analysis on a point-to-point basis, comparing the class values of the points in one input LAS file with the corresponding nearest points in the second input LAS file.

The user must also specify the name and resolution of an output raster file, which is used to show the spatial distribution of class accuracy. Each grid cell contains the overall accuracy, i.e. the points correctly classified divided by the total number of points contained within the cell, expressed as a percentage.

## Function Signature

`def lidar_kappa(self, input_lidar1: Lidar, input_lidar2: Lidar, output_html_file: str, cell_size: float = 1.0, output_class_accuracy: bool = False) -> Raster: ...`

## Project Links

WbW Homepage User Manual Support WbW