Regional Applicability of Forest Height and Aboveground Biomass Models for the Geoscience Laser Altimeter System

Accurate estimates of forest aboveground biomass are needed to reduce uncertainties in global and regional terrestrial carbon fluxes. In this study we investigated the utility of the Geoscience Laser Altimeter System (GLAS) onboard the Ice, Cloud and land Elevation Satellite for large-scale biomass inventories. GLAS is the first spaceborne lidar sensor that will provide global estimates of forest height. We compared accuracy and regional variability of GLAS height estimates with data from the US Forest Service Inventory and Analysis (FIA) program and found that current GLAS algorithms provided generally accurate estimates of height. GLAS heights were on average 2-3 m lower than FIA estimates. To translate GLAS-estimated heights into forest biomass will require general allometric equations. Analysis of the regional variability of forest height-biomass relationships using FIA field data indicates that general nonspecies specific equations are applicable without a significant loss of prediction accuracy. We developed biomass models from FIA data and applied them to the GLAS-estimated heights. Regional estimates of forest biomass from GLAS differed between 39.7 and 58.2 Mg ha 1 compared with FIA. FOR .S CI. 54(6):647-657.

[1]  Michael A. Lefsky,et al.  Revised method for forest canopy height estimation from Geoscience Laser Altimeter System waveforms , 2007 .

[2]  W. Cohen,et al.  Lidar remote sensing of above‐ground biomass in three biomes , 2002 .

[3]  W. Cohen,et al.  Estimates of forest canopy height and aboveground biomass using ICESat , 2005 .

[4]  K. Lim,et al.  Estimation of above ground forest biomass from airborne discrete return laser scanner data using canopy-based quantile estimators , 2004 .

[5]  D. Lu The potential and challenge of remote sensing‐based biomass estimation , 2006 .

[6]  Irena Hajnsek,et al.  Forest biomass estimation using polarimetric SAR interferometry , 2002, IEEE International Geoscience and Remote Sensing Symposium.

[7]  William A. Bechtold,et al.  The forest inventory and analysis plot design , 2005 .

[8]  H. Zwally,et al.  Overview of ICESat's Laser Measurements of Polar Ice, Atmosphere, Ocean, and Land , 2002 .

[9]  Mark Hansen Volume and biomass estimation in FIA: national consistency vs. regional accuracy , 2002 .

[10]  Ranga B. Myneni,et al.  Remote sensing estimates of boreal and temperate forest woody biomass: carbon pools, sources, and sinks , 2003 .

[11]  D. Harding,et al.  ICESat waveform measurements of within‐footprint topographic relief and vegetation vertical structure , 2005 .

[12]  Karin S. Fassnacht,et al.  Relationships between leaf area index and Landsat TM spectral vegetation indices across three temperate zone sites , 1999 .

[13]  Guoqing Sun,et al.  Mapping of boreal forest biomass from spaceborne synthetic aperture radar , 1997 .

[14]  B. Law,et al.  Forest Attributes from Radar Interferometric Structure and Its Fusion with Optical Remote Sensing , 2004 .

[15]  R. Dubayah,et al.  Sensitivity of large-footprint lidar to canopy structure and biomass in a neotropical rainforest , 2002 .

[16]  Peter R. J. North,et al.  Vegetation height estimates for a mixed temperate forest using satellite laser altimetry , 2008 .

[17]  A Model-Based Approach to Inventory Stratification , 2006 .

[18]  Patrick Johnson,et al.  A low-frequency radar experiment for measuring vegetation biomass , 1998, IEEE Trans. Geosci. Remote. Sens..

[19]  W. Cohen,et al.  Surface lidar remote sensing of basal area and biomass in deciduous forests of eastern Maryland, USA , 1999 .

[20]  R. Birdsey,et al.  National-Scale Biomass Estimators for United States Tree Species , 2003, Forest Science.

[21]  R. Fournier,et al.  A comparison of four methods to map biomass from Landsat-TM and inventory data in western Newfoundland , 2006 .

[22]  R. Dickinson,et al.  Couplings between changes in the climate system and biogeochemistry , 2007 .

[23]  William A. Bechtold,et al.  The enhanced forest inventory and analysis program - national sampling design and estimation procedures , 2005 .

[24]  W. Walker,et al.  Mapping forest structure for wildlife habitat analysis using waveform lidar: Validation of montane ecosystems , 2005 .

[25]  J. Abshire,et al.  Geoscience Laser Altimeter System (GLAS) on the ICESat Mission: On‐orbit measurement performance , 2005 .

[26]  Mark H. Hansen,et al.  Sample-based estimators used by the forest inventory and analysis national information management system , 2005 .

[27]  Christopher B. Field,et al.  FOREST CARBON SINKS IN THE NORTHERN HEMISPHERE , 2002 .

[28]  F. H. Eyre,et al.  Forest cover types of the United States and Canada , 1980 .

[29]  Wolfgang Lucht,et al.  Global biomass mapping for an improved understanding of the CO2 balance—the Earth observation mission Carbon-3D , 2005 .

[30]  R. Houghton,et al.  Aboveground Forest Biomass and the Global Carbon Balance , 2005 .

[31]  Carbon storage and fluxes in ponderosa pine forests at different developmental stages , 2001 .

[32]  J. Blair,et al.  The Laser Vegetation Imaging Sensor: a medium-altitude, digitisation-only, airborne laser altimeter for mapping vegetation and topography , 1999 .