Remote Sensing

Autor: Ross Nelson, Mark Sanford, Alicia Peduzzi, James J. Reis, Randolph H. Wynne, Valerie A. Thomas
Přispěvatelé: Forest Resources and Environmental Conservation
Jazyk: angličtina
Rok vydání: 2012
Předmět:
Zdroj: Remote Sensing, Vol 4, Iss 6, Pp 1758-1780 (2012)
Remote Sensing
Volume 4
Issue 6
Pages 1758-1780
Popis: The objective of this study was to determine whether leaf area index (LAI) in temperate mixed forests is best estimated using multiple-return airborne laser scanning (lidar) data or dual-band, single-pass interferometric synthetic aperture radar data (from GeoSAR) alone, or both in combination. In situ measurements of LAI were made using the LiCor LAI-2000 Plant Canopy Analyzer on 61 plots (21 hardwood, 36 pine, 4 mixed pine hardwood
stand age ranging from 12-164 years
mean height ranging from 0.4 to 41.2 m) in the Appomattox-Buckingham State Forest, Virginia, USA. Lidar distributional metrics were calculated for all returns and for ten one meter deep crown density slices (a new metric), five above and five below the mode of the vegetation returns for each plot. GeoSAR metrics were calculated from the X-band backscatter coefficients (four looks) as well as both X- and P-band interferometric heights and magnitudes for each plot. Lidar metrics alone explained 69% of the variability in LAI, while GeoSAR metrics alone explained 52%. However, combining the lidar and GeoSAR metrics increased the R2 to 0.77 with a CV-RMSE of 0.42. This study indicates the clear potential for X-band backscatter and interferometric height (both now available from spaceborne sensors), when combined with small-footprint lidar data, to improve LAI estimation in temperate mixed forests.
Databáze: OpenAIRE