Leaf Area Index

Summary

Leaf Area Index (LAI) is defined as half of the surface area of all leaves projected on the surface area of a unit.

Principle Description

The algorithm was developed according to Li et al. (Li et al.,2016).For each statistical unit, a three-dimensional network is first constructed with a cell size of 1.5 times the average distance between each two points. Then, for the constructed three-dimensional network, count the total number of three-dimensional cells in each layer and the number of cells containing laser points in that layer. Based on that result, calculate the frequency of laser points in each layer.

Where </img> is the point frequency of the s-th layer, is the number of cells which contains the laser points in the s-th layer; is the total number of three-dimensional cells in the s-th layer. And then calculate the LAI in the s-th layer:

Where is the leaf inclination correction factor. Usually, it is set as 1.1. Finally, accumulate the LAI of each layer to calculate the LAI for the entire statistical unit.

Usage

Click TLS Forestry > Leaf Area Index, to generate TLS leaf area index.

TLS_LAI

Settings

  • Input Data: Ensure that each input point cloud 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.
  • Volex Size Setting
    • Volex Size (meter) (default value is "0"): The size of the cell which is used to divide the statistical unit.
    • Coefficient (default value is "1.5"): The coefficient used to calculate the size of the three-dimensional cell. The cell size is the product of this coefficient and the average distance between each two points in the point cloud.
  • Output Path: Path of the output file. A corresponding raster file (.tif format) will be generated for each input point cloud data. The .tif files can be used as an independent variable of the regression analysis.

Note: Only when the point cloud data is loaded in the software can you use the TLS Leaf Area Index 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.

@inproceedings{ author={ Li Y , Guo Q , Tao S , et al.}, title={Derivation, Validation, and Sensitivity Analysis of Terrestrial Laser Scanning-Based Leaf Area Index}, booktitle={ Canadian Journal of Remote Sensing, 2016, 42(6):719-729.}, year={2016} }

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