## Intensity Metrics

### Summary

The intensity metrics are similar to the elevation metrics with the exception that point intensity is used rather than point elevation. Therefore, this function can be used only if the point cloud data contains intensity information. Overall, 42 statistical parameters related to intensity can be calculated, and the resultant product is a table in CSV format or a set of TIFF files.

### Principle

**Average Absolute Deviation**: Computed using the following equation:, where I_{i}represents the intensity of i^{th}point within a statistical unit, I represents the average intensity of all points within a statistical unit, and n is the number of points in a statistical unit.**AII (15)**: Within a statistical unit, all normalized lidar point clouds are sorted according to their intensity values and the cumulative intensities of all points are calculated. The cumulative intensity of X% points in each statistical unit is the statistical unit's AIH. In LiDAR360, 15 AIH can be calculated, including 1%, 5%, 10%, 20%, 25%, 30%, 40%, 50%, 60%, 70%, 75%, 80%, 90%, 95% and 99%.**Coefficient of Variation**: Computed using the following equation:, where I_{std}represents the standard deviation of intensity within a statistical unit, and I_{mean}represents the average intensity within a statistical unit.**Kurtosis**：The kurtosis of the intensity values of all points in a statistical unit. The calculation formula is , in which Z_{i}is the intensity value of the i-th point in each statistical unit, Z is the average intensity of all points in each statistical unit, n is the point number in each statistical unit, and σ is the standard deviation of point cloud intensity distribution within a statistical unit.**MADMedian**：The median of median absolute deviation of the intensity values of all points in a statistical unit.**Maximum**：The maximum of the intensity values of all points in a statistical unit.**Minimum**：The minimum of the intensity values of all points in a statistical unit.**Mean**：The mean of the intensity values of all points in a statistical unit.**Median**：The median of the intensity values of all points in a statistical unit.**Skewness**: This value shows the symmetry of intensity values of all the points in each statistical unit. The calculation formula is , in which Z_{i}is the intensity value of the i-th point in each statistical unit, Z is the average intensity of all points in each statistical unit, n is the point number in each statistical unit, and σ is the standard deviation of point cloud intensity distribution within a statistical unit.**Standard Deviation**：The standard deviation of the intensity values of all points in a statistical unit.**Variance**: The variance of the intensity values of all points in a statistical unit.**Intensity Percentile (15)**：Within a statistical unit, all normalized lidar point clouds are sorted by intensity, and then the intensity at which X% of points in each statistical unit is located is the intensity percentile of this statistical unit. In LiDAR360, 15 intensity percentiles are calculated, including 1%, 5%, 10%, 20%, 25%, 30%, 40%, 50%, 60%, 70%, 75%, 80%, 90%, 95% and 99%.**Intensity Percentile Interquartile Distance**: Computed using the following equation:, where Int75% represents the 75% intensity statistical layer, and Int25% represents the 25% intensity statistical layer.

### Usage

To generate Intensity Metrics, navigate to *ALS Forest > Forest Metrics > Intensity Metrics*.

### Settings

**Input Data**: Make sure that each input point cloud data contains intensity information, and each data is Normalize by DEM or Normalize by Ground Points. The input file can be a single file or multiple data files. Point cloud data should be opened in LiDAR360 before being processed.**XSize (meter)(default value is "15")**: The length of a grid size should be greater than an individual tree crown width. For most forest types, the grid size should be greater than 15 meters.**YSize (meter)(default value is "15")**: The width of a grid size should be greater than an individual tree crown width. For most forest types, the grid size should be greater than 15 meters.**Output Path**: Path of the output file. A corresponding CSV file or a set of corresponding TIFF files will be generated for each input point cloud data, which can be used as an independent variable in the regression analysis**DefaultValue**: Restore the default parameters.

Note: Only when the point cloud data is loaded in the software can you use the Intensity Metrics function; otherwise, the message "There is no point cloud data meeting the conditions of calculation!" will pop up. If the maximum Z value of the point cloud is greater than 200 m or the maximum Z minus the minimum Z is greater than 200 m, the data is not considered to have been normalized, and the prompt information shown in the figure below will pop up. Click “YES” to keep using this type of data in the operation; otherwise, click "NO" and reselect the input data file.