Calculate Forest Metrics by Forest Stands
Calculate forest metrics by forest stands for each point cloud data. The metrics include Elevation Metrics, Intensity Metrics, Canopy Cover, Leaf Area Index, and Gap Fraction. For each poitn cloud data, a record will be generated and stored in a CSV file.
Click ALS Forest > Forest Metrics > Calculate Forest Metrics by Forest Stands to generate the selected forest metrics.
- Input: Please ensure that each input point cloud data is normalized data; the input file can be a single point cloud data file or a point cloud data set; to be The processed data must be opened in the LiDAR360 software. -Height threshold (m) (default is "2"): The threshold for dividing the point cloud into different layers, and the point whose height exceeds the threshold will participate in the calculation. The default value is 2 meters. -Leaf inclination angle distribution (default is "0.5"): A mathematical expression of the probability distribution of leaves in a three-dimensional space, which is related to vegetation type, leaf inclination angle and beam direction. The user can determine the value of the leaf inclination angle distribution based on the empirical formula combined with the actual situation of the forest. Studies have shown that the elliptical distribution of leaf inclination angles may be suitable for most forests, with a value of 0.5. -Output Path: Output path. After running, each input point cloud data file will generate a corresponding CSV file or a set of TIFF files, which can be used as independent variables in regression analysis. -Default: Restore the height threshold and leaf inclination angle distribution to the default values.
Note: Only when the point cloud data is loaded in the software, can you use the grid-based calculation of forest parameters function, otherwise, the software will pop up the prompt message "There is no point cloud data meet the conditions of calculation!". If the maximum Z value of the point cloud is greater than 200 or the maximum Z minus the minimum Z is greater than 200, the data is considered to be unnormalized, and the software will pop up the prompt message shown in the figure below, click "YES", this type of data Still participating in the calculation, click "NO", this type of data will not participate in the calculation, and the user can re-select the data that meets the conditions.