title: Airborne lidar-based estimates of tropical forest structure in complex terrain: opportunities and trade-offs for REDD+
abstract: BACKGROUND
  Carbon stocks and fluxes in tropical forests remain large sources of uncertainty in the global carbon budget. Airborne lidar remote sensing is a powerful tool for estimating aboveground biomass, provided that lidar measurements penetrate dense forest vegetation to generate accurate estimates of surface topography and canopy heights. Tropical forest areas with complex topography present a challenge for lidar remote sensing.
  
  
  RESULTS
  We compared digital terrain models (DTM) derived from airborne lidar data from a mountainous region of the Atlantic Forest in Brazil to 35 ground control points measured with survey grade GNSS receivers. The terrain model generated from full-density (~20 returns m-2) data was highly accurate (mean signed error of 0.19 ± 0.97 m), while those derived from reduced-density datasets (8 m-2, 4 m-2, 2 m-2and 1 m-2) were increasingly less accurate. Canopy heights calculated from reduced-density lidar data declined as data density decreased due to the inability to accurately model the terrain surface. For lidar return densities below 4 m-2, the bias in height estimates translated into errors of 80-125 Mg ha-1in predicted aboveground biomass.
  
  
  CONCLUSIONS
  Given the growing emphasis on the use of airborne lidar for forest management, carbon monitoring, and conservation efforts, the results of this study highlight the importance of careful survey planning and consistent sampling for accurate quantification of aboveground biomass stocks and dynamics. Approaches that rely primarily on canopy height to estimate aboveground biomass are sensitive to DTM errors from variability in lidar sampling density.
authors: Remote Sensing Division, National Institute for Space Research (INPE), São José dos Campos, SP CEP 12201-970 Brazil ; Biospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD 20771 USA.
authors: Veronika
authors: V
authors: Leitold
authors: International Institute of Tropical Forestry, USDA Forest Service, San Juan, 00926 Puerto Rico ; EMBRAPA Satellite Monitoring, Campinas, SP CEP 13070-115 Brazil.
authors: Michael
authors: M
authors: Keller
authors: Biospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD 20771 USA.
authors: Douglas C
authors: DC
authors: Morton
authors: Biospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD 20771 USA.
authors: Bruce D
authors: BD
authors: Cook
authors: Remote Sensing Division, National Institute for Space Research (INPE), São José dos Campos, SP CEP 12201-970 Brazil.
authors: Yosio E
authors: YE
authors: Shimabukuro
keywords: Airborne lidar; Biomass estimation; Canopy height; Data thinning; Digital Terrain Model; Elevation accuracy; REDD+; Tropical montane forest