Analysis of Multiple Lidar Device's Ability to Estimate Tree Diameter and Height Compared to Field Measurements

Student: Seth Machado

Faculty Mentor: Matthew Clark

Geography, Environment & Planning

College of Humanities, Social Sciences, and the Arts

Light Detection and Ranging, or lidar, is a powerful remote sensing technology that is used for measuring the 3-dimensional properties of the Earth’s surface. In forestry applications, lidar is able to measure the Diameter Breast Height (DBH) and tree height, which can be used to predict aboveground biomass or carbon stocks. In this experiment, we performed a comparative analysis of four different lidar devices (Riegl, Ligrip, Geoslam, Resepi) to estimate DBH and tree height as measured by field measurements. Three of these devices (Ligrip, Geoslam, and Resepi) are handheld, mobile, and capable of flying on a drone, whereas the Riegl is a stationary device that needs to be set up on a tripod. All the data were acquired from the ground, except for one dataset, which was merged ground- and drone-based lidar data. When analyzing the data, we used a linear model R-squared value to assess accuracy. The lidar device that had the greatest R-squared value in estimating field-based DBH was the Riegl device at 0.608, and the second greatest R-squared value was from Resepi with 0.476. However, when comparing the tree height, only Resepi without the drone data being merged had a significant R-squared value of 0.114 when being compared to field measurements. Our results indicate that the Resepi device is the most accurate when looking at DBH measurements relative to the other handheld lidar devices. However, it is hard to determine which is the best lidar for measuring height due to possible limitations of these devices when compared to field measurements. Handheld lidar can be used for other forestry applications, like mapping vegetation density, ladder fuel loads, and pre- and post-treatment vegetation change.