Estimation of tropical forest structural characteristics using large-footprint lidar

    Authors

    J. B. Drake; R. O. Dubayah; D. B. Clark; R. G. Knox; J. B. Blair; M. A. Hofton; R. L. Chazdon; J. F. Weishampel;S. D. Prince

    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

    WOS:000173230400014

    ISSN

    0034-4257

    Share

    COinS