Abstract
In recent years, light detection and ranging (LiDAR) has been increasingly utilized to estimate forest resources. This study was conducted to identify the applicability of a LiDAR sensor for such estimations by comparing data on a tree’s position, height, and diameter at breast height (DBH) obtained using the sensor with those by existing forest inventory methods for a Cryptomeria japonica forest in Jeju Island, South Korea. For this purpose, a backpack personal laser scanning device (BPLS, Greenvalley International, Model D50) was employed in a protected forest, where cutting is not allowed, as a non-invasive means, simultaneously assessing the device’s field applicability. The data collected by the sensor were divided into seven different pathway variations, or “patterns” to consider the density of the sample plots and enhance the efficiency. The accuracy of estimating the variables of each tree was then assessed. The time spent acquiring and processing real-time data was also analyzed for each method, as well as total time and the time required for each measurement. The findings showed that the rate of detection of standing trees by LiDAR was 100%. Additionally, a high statistical accuracy was observed in pattern 5 (DBH: RMSE 1.22 cm, bias—0.90 cm, Height: RMSE 1.66 m, bias—1.18 m) and pattern 7 (DBH: RMSE 1.22 cm, bias—0.92 cm, Height: RMSE 1.48 m, bias—1.23 m) compared to the results from the typical inventory method. A range of 115–162.5 min/ha was required to process the data using the LiDAR, while 322.5–567.5 min was required for the typical inventory method. Thus, the application of a backpack personal LiDAR can lead to higher efficiency when conducting a forest resource inventory in a coniferous plantation with understory vegetation. Further research in various stands is necessary to confirm the efficiency of using backpack personal laser scanning.
Highlights
Forest resource surveys are conducted to gather data for forest management decisionmaking by understanding the current state of forest resources
To evaluate the applicability of a sample point forest survey using backpack personal laser scanning (BPLS), this study was performed at Saryeoni Forest, a Cryptomeria japonica plantation located in Jeju-do, South was performed at Saryeoni Forest, a Cryptomeria japonica plantation located in Jeju-do, Korea
A total of 157 trees were present in the sample plots
Summary
Forest resource surveys are conducted to gather data for forest management decisionmaking by understanding the current state of forest resources. In forest management, an accurate estimation of the key forest variables is essential, namely, the diameter at breast height (DBH) and height. Forest resource surveys conducted in a wide range of regions are time-consuming and labor-intensive, making traditional field survey methods that manually measure each stand property inefficient [1]. Technology is drawing much attention lately as an alternative method to improve the efficiency. Traditional methods to measure forest resources tend to produce a larger error margin, depending on the observer, causing a decrease in the overall accuracy. LS technology, is capable of producing high accuracy output consistently and is an environmentally friendly alternative to monitoring forests due to its non-invasive nature
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