Using Airborne Lidar to Discern Age Classes of Cottonwood Trees in a Riparian Area.
Authors:
Farid, A. Goodrich, D.C. Sorooshian, S. USDA, ARS
Source:
Western journal of applied forestry. 2006 July, v. 21, no. 3, p. 149-158.
NALT Subjects:
riparian forests forest trees remote sensing Populus fremontii tree age tree classes spatial distribution overstory canopy forest mensuration methodology regression analysis equations spatial data Arizona
Issue Date:
Jul-2006
Abstract:
Airborne lidar (light detecting and ranging) is a useful tool for probing the structure of forest canopies. Such information is not readily available from other remote sensing methods and is essential for modern forest inventories. In this study, small-footprint lidar data were used to estimate biophysical properties of young, mature, and old cottonwood trees in the San Pedro River basin near Benson, Arizona. The lidar data were acquired in June 2004, using Optech's 1233 ALTM during flyovers conducted at an altitude of 600 m. Canopy height, crown diameter, stem dbh, canopy cover, and mean intensity of return laser pulses from the canopy surface were estimated for the cottonwood trees from the data. Linear regression models were used to develop equations relating lidar-derived tree characteristics with corresponding field acquired data for each age class of cottonwoods. The lidar estimates show a good degree of correlation with ground-based measurements. This study also shows that other parameters of young, mature, and old cottonwood trees such as height and canopy cover, when derived from lidar, are significantly different (P < 0.05). Additionally, mean crown diameters of mature and young trees are not statistically different at the study site (P = 0.31). The results illustrate the potential of airborne lidar data to differentiate different age classes of cottonwood trees for riparian areas quickly and quantitatively.
