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# System prepended metadata

title: 1.1 Introduction

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# 1.1 Introduction
## Features this code extract
This code is desinged for extracting LiDAR features, including:
- Total number of points: number of non-ground pints in each plot 
- Height/Intensity percent features: 30% height/intensity derived from non-ground points
![](https://i.imgur.com/EjUozFn.png)

- Height/Intensity statistic features: only based on non-ground points, calculated the following 
    1. Standard deviation
    2. Quadratic mean: A type of average, calculated as the square root of the mean of the squares. $\large Q=\sqrt{\frac{x^2_1+x^2_2+...+x^2_n}{n}}$
    3. Skewness: For normally distributed data, the skewness should be about zero. For unimodal continuous distributions, a skewness value greater than zero means that there is more weight in the right tail of the distribution. 
    4. Kurtosis: The fourth central moment divided by the square of the variance. (default is using Fisher’s definition, which means abstract another 3 to make the kurtosis of normal distribution equal to 0, here is not using Fisher’s definition)![](https://i.imgur.com/b3FTZnL.png)
     5. Coefficient of variation: The ratio of the biased standard deviation to the mean. The higher the coefficient of variation, the greater the level of dispersion around the mean. 
         - $\large CV=\huge \frac{\sigma}{\mu}$
- Canopy cover features: calculate number of points above each red line, divided by number of all points in each plot 
    - $Plot\_LII_{30\%}= \huge \frac{\# NG\ points\ above\ 30\%\ height}{\# all\ points}$
    - NG: non-ground
![](https://i.imgur.com/UpeNvDf.png)
 
 
- Plots volume feature: 
    - calculate an average height of each grid:
$\large Average\ Height_{grid}= \huge \frac{95\%\ height\ of\ NG\ points+min\ height\ of\ NG\ points}{2}$
    - Find grids belong to each plot based on the location of grid center as following, the blue area is one plot (row2&3), the red dash line is all the grids belong to this plot. 
    $\large Volume_{plot}=\huge \frac{\Sigma Average\ Height\times (grid\_resolution)^2}{\#\ grids}$
![](https://i.imgur.com/aXXWrsb.png)
