Title
Estimation of tropical forest structural characteristics using large-footprint lidar
Abbreviated Journal Title
Remote Sens. Environ.
Keywords
aboveground biomasss; carbon; forest structure; tropical forests; lidar; remote sensing; laser altimeter; Costa Rica; LASER SCANNER DATA; LANDSAT TM DATA; RADAR BACKSCATTER; RAIN-FOREST; LANDSCAPE-SCALE; SPATIAL HETEROGENEITY; STAND CHARACTERISTICS; CANOPY; STRUCTURE; AIRBORNE LIDAR; COSTA-RICA; Environmental Sciences; Remote Sensing; Imaging Science & Photographic; Technology
Abstract
Quantification of forest structure is important for developing a better understanding of how forest ecosystems function. Additionally, estimation of forest structural attributes, such as aboveground biomass (AGBM), is an important step in identifying the amount of carbon in terrestrial vegetation pools and is central to global carbon cycle studies. Although current remote sensing techniques recover such tropical forest structure poorly, new large-footprint lidar instruments show great promise. As part of a prelaunch validation plan for the Vegetation Canopy Lidar (VCL) mission, the Laser Vegetation Imaging Sensor (LVIS), a large-footprint airborne scanning lidar, was flown over the La Selva Biological Station, a tropical wet forest site in Costa Rica. The primary objective of this study was to test the ability of large-footprint lidar instruments to recover forest structural characteristics across a spectrum of land cover types from pasture to secondary and primary tropical forests. LVIS metrics were able to predict field-derived quadratic mean stem diameter (QMSD), basal area, and AGBM with R 2 values of up to .93,.72, and .93, respectively. These relationships were significant and nonasymptotic through the entire range of conditions sampled at the La Selva. Our results confirm the ability of large-footprint lidar instruments. to estimate. important structural attributes, including biomass in dense tropical forests, and when taken along with similar results from studies in temperate forests, strongly validate the VCL mission framework. (C) 2002 Elsevier Science Inc. All rights reserved.
Journal Title
Remote Sensing of Environment
Volume
79
Issue/Number
2-3
Publication Date
1-1-2002
Document Type
Article
Language
English
First Page
305
Last Page
319
WOS Identifier
ISSN
0034-4257
Recommended Citation
"Estimation of tropical forest structural characteristics using large-footprint lidar" (2002). Faculty Bibliography 2000s. 3165.
https://stars.library.ucf.edu/facultybib2000/3165