HR: 0800h
AN: H31E-1345    [Abstracts]
TI: Using Airborne Lidar to Differentiate Cottonwood Trees in a Riparian Area and Refine Riparian Water Use Estimates
AU: * Farid, A
EM: farid@hwr.arizona.edu
AF: Department of Hydrology and Water Resources, University of Arizona, Tucson, AZ 85721
AU: Goodrich, D
EM: dgoodrich@tucson.ars.ag.gov
AF: USDA-ARS-SWRC, SW Watershed Research Center, 2000 E. Allen Road, Tucson, AZ 85719
AU: Sorooshian, S
EM: soroosh@uci.edu
AF: Department of Civil and Environmental Engineering, University of California - Irvine, Irvine, CA 92697
AB: 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, USA. The lidar data were acquired in June 2003, using Optech's 1233 ALTM (Optech Incorporated, Toronto, Canada), during flyovers conducted at an altitude of 750 m. Canopy height, crown diameter, stem diameter at breast height (dbh), canopy cover, and mean intensity of return laser pulses from the canopy surface are estimated for the cottonwood trees from lidar data. The lidar estimates show a good degree of correlation with ground-based measurements. This study also demonstrates 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). These lidar-derived canopy metrics provided the basis for a supervised image classification of cottonwood age categories, using a maximum likelihood algorithm. The results of classification illustrate the potential of airborne lidar data to differentiate age classes of cottonwood trees for riparian areas quickly and quantitatively. In addition, four metrics (canopy height, height of median energy, ground return ratio, and canopy return ratio) were derived by synthetically constructing a large footprint lidar waveform from the airborne small-footprint lidar data. These four metrics were incorporated into a stepwise regression procedure to predict field-derived Leaf Area Index (LAI) for different age classes of cottonwoods. Additionally, this study applied the well-known Penman-Monteith model to estimate age classes of cottonwood transpiration using lidar-derived canopy metrics, such as height and LAI, so improved riparian water use estimates could be made.
DE: 1209 Tectonic deformation (6924)
DE: 1294 Instruments and techniques
DE: 1625 Geomorphology and weathering (0790, 1824, 1825, 1826, 1886)
DE: 1824 Geomorphology: general (1625)
DE: 1886 Weathering (0790, 1625)
SC: Hydrology [H]
MN: Fall Meeting 2005