Riparian vegetation classification from airborne laser scanning data with an emphasis on cottonwood trees

A. Farid, D. Rautenkranz, D. C. Goodrich, S. E. Marsh, S. Sorooshian

Research output: Contribution to journalArticle

15 Scopus citations

Abstract

The high point density of airborne laser mapping systems enables achieving a detailed description of geographic objects and the terrain. Growing experience indicates, however, that extracting useful information directly from the data can be difficult. In this study, small-footprint lidar data were used to differentiate between 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 the Optech Incorporated ALTM 1233 (Optech Incorporated, Toronto, Ont.), during flyovers conducted at an altitude of 750 m. The lidar data were preprocessed to create a two-band image of the study site: a high-accuracy canopy altitude model band, and a near-infrared intensity band. These lidar-derived images provided the basis for supervised 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 accurately.

Original languageEnglish (US)
Pages (from-to)15-18
Number of pages4
JournalCanadian Journal of Remote Sensing
Volume32
Issue number1
DOIs
StatePublished - Feb 2006

ASJC Scopus subject areas

  • Earth and Planetary Sciences(all)

Fingerprint Dive into the research topics of 'Riparian vegetation classification from airborne laser scanning data with an emphasis on cottonwood trees'. Together they form a unique fingerprint.

  • Cite this