Forest Structure Change Detection

Summary

The LiDAR PAC (profile area change) metric, as a simple and integrated method, demonstrated promising potential in characterizing fine-grained changes in forest structure. The method can be beneficial for forest managers in evaluating fire-induced environmental and economic losses, and provide useful information for forest restoration design.

Principle Description

First, this function divides the data into different grids according to the XSize and YSize set by the users. For each grid, normalize the height value of all the points to the range of 0 to 1. And then, sort the points by height and calculate its cumulative height percentile. Calculate the height value for each integer cumulative percentile from 0 to 99% (100 values in total). Then fit the 100 cumulative height percentiles to the profile curve, and calculate the profile area (PA) delineated by the percentile profile curve and the X axis. After calculating the PA value of the curve area before and after the change, use the PA after the change minus the PA value before the change to get the PAC value.

Usage

Click ALS Forest > Forest Structure Change Detection

Settings

• Input: Make sure that all the input files are normalized. The input file(s) can be a single file or a file set. The file(s) to be processed must be opened in LiDAR360 before using this function.
• XSize (meter) (default value is "30"): The grid size in X direction. This value should be larger than the crown size of the trees. For the data acquired from most of the forest, this value should be larger than 15.
• YSize (meter) (default value is "30"): The grid size in Y direction. This value should be larger than the crown size of the trees. For the data acquired from most of the forest, this value should be larger than 15.
• Height Threshold (meter) (default value is "2"): The threshold to divide the data in vertical direction. The point cloud above this height will be used to calculate the forest metrics. The default value is 2.
• Output Path: Path of the output file. Two PA images (before and after the change), a PAC image, and a report will be generated.
• DefaultValue: Restore the default parameters.

Note: The selected point cloud data must be normalized ALS data.

    @inproceedings{
        author={Tianyu Hu,Qin Ma,Yanjun Su,John J.Battles,Brandon M.Collins,Scott L.Stephens,Maggi Kelly,Qinghua Guo},
        title={A simple and integrated approach for fire severity assessment using bitemporal airborne LiDAR data},
        booktitle={Int J Appl Earth Obs Geoinformation,78(2019): 25-38},
        year={2019}
    }