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Recent Proceedings

Esri Proceedings

2009 Esri Southeast Regional User Group Conference

ENR—GIS: An Effective Tool for Environmental Research

Automatic Classification of Southern Pine Stands Using LiDAR and Timber Cruise Data

—Mitch Koyle, Milliken Forestry Company, Inc.

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LiDAR (Light Detection and Ranging) data has a wide range of applications in the world of GIS. One of the areas that LiDAR has been used extensively is in the field of forestry. One of the most basic applications is acquiring tree canopy heights. Aside from location and elevation, LiDAR sensors typically collect intensity information as well. The intensity is measured as the "peak voltage of the return signal" of the laser from the LiDAR sensor. Laser light is monochromatic and thus has an extremely small bandwidth. Because of this, atmospheric influences and other concerns, the intensity data is sometimes difficult to interpret without extensive calibration. This difficulty, in many cases, has led to the intensity data largely being ignored. However, research has shown that intensity values can be related to biophysical characteristics of forests. This research deals specifically with southern pine stands in the coastal plain region of South Carolina. The focus of this study is a 2,700 acre tract of land in the coastal plain region of South Carolina. The LiDAR data used in this research is obtained from NOAA's digital coast website. It was collected in March of 2007. The timber cruise data was collected in July of 2007. The tract has a variety of loblolly pine age classes. The goal of this project is to use data collected in the field coupled with LiDAR data to determine if LiDAR alone can be used for determining some forest characteristics. This is accomplished by correlating the location, elevation and the intensity data acquired by LiDAR with timber cruise data collected in the field by foresters. Extensive analysis is performed using the intensity data as it is correlated with specific age classes of basal area and tree density. It is expected that certain metrics will be discovered which will provide an accurate way to estimate height, basal area and tree density using only LiDAR data. This would be a valuable tool for forestry applications, as it would greatly increase the efficiency with which the data normally acquired in the field timber cruises is collected and analyzed. It would also have a positive impact on how consulting foresters assess timber values across large land holdings. It would at the very least provide a valuable verification of measurements collected in the field by foresters. Results would undoubtedly vary greatly in different regions. The results of this research will apply specifically to the coastal plain region in South Carolina.


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