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Estimating vegetation coverage from a lidar dataset (LAS), in terms of percentage, can be done using the LAS Point Statistics As Raster tool. However, ground features are identified by classification codes in lidar datasets. Therefore, prior to estimating the percentage of vegetation coverage, the lidar points in the dataset must be classified.
For more information on working with classification codes in lidar datasets, refer to Working with LAS classification in ArcGIS.
The following instructions describe how to use the LAS Point Statistics As Raster tool to quantify, extract, and estimate vegetation coverage in terms of percentage. For more information, refer to ArcGIS Help: LAS Point Statistics As Raster tool.
Once the lidar points are classified, the lidar point 'clouds' can be converted into a raster that shows the land cover, allowing the coverage to be quantified by using the LAS Point Statistics As Raster tool.
Note: Ensure the lidar dataset ground features are identified and classified with the correct classification codes prior to using the LAS Point Statistics As Raster tool.
This method assigns the most frequent class code to the pixel value in a pixel area. For example, in a pixel area covered by trees, lidar returns from layers of the canopy are more than returns from the ground. As a result, this pixel area has the land cover class of vegetation.
The sampling value determines the pixel size of the output raster. With smaller pixel sizes, the accuracy and resolution of the estimation increases. However, if the pixel size is smaller than the point spacing distance in some pixel areas, no lidar returns are captured, resulting in NULL pixels.
Percentage_Coverage = (Count/sum of Count) * 100