@Article{LeitoldKelMorCooShi:2015:OpTrRE,
author = "Leitold, Veronika and Keller, Michael and Morton, Douglas C. and
Cook, Bruce D. and Shimabukuro, Yosio Edemir",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {} and NASA
and NASA and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
title = "Airborne lidar-based estimates of tropical forest structure in
complex terrain: opportunities and trade-offs for REDD+",
journal = "Carbon Balance and Management",
year = "2015",
volume = "10",
number = "3",
keywords = "Tropical montane forest, Airborne lidar, Digital Terrain Model,
Elevation accuracy, Data thinning, Canopy height, Biomass
estimation, 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\−2,4m\−2,2m\−2 and 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 80125 Mg ha\−1 in
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.",
doi = "10.1186/s13021-015-0013-x",
url = "http://dx.doi.org/10.1186/s13021-015-0013-x",
issn = "1750-0680",
language = "en",
targetfile = "leitold_airborne.pdf",
urlaccessdate = "27 abr. 2024"
}