Provider: Ingenta Connect
Database: Ingenta Connect
Content: application/x-research-info-systems
TY - ABST
AU - Magnussen, Steen
AU - Eggermont, Paul
AU - LaRiccia, Vincent N.
TI - Recovering Tree Heights from Airborne Laser Scanner Data
JO - Forest Science
PY - 1999-08-01T00:00:00///
VL - 45
IS - 3
SP - 407
EP - 422
KW - Weibull distribution
KW - Canopy height
KW - crown area
KW - deconvolution
KW - extreme value distribution
KW - error function
KW - PPS sampling
KW - EM algorithm
N2 - Airborne laser scanner data collected over forests provide a canopy height. To obtain tree heights from airborne laser scanner data one needs a recovery model. Two such models, one (A) assuming that observations are sampled with probability proportional to displayed crown area, and the other (B) derived from the probability that a laser beam penetrates to a given canopy depth, were developed and applied to laser scanner data obtained over stands of Douglas-fir. Model estimates of recovered arithmetic mean tree heights and quantiles (75%, 85%, and 95%) were not significantly (P> 0.24) different from ground-based equivalents. An overall mean bias of-3 m in the laser canopy heights was eliminated by both methods. The median absolute difference between observed and predicted plot means and quantiles were reduced by 40 to 60%. Three alternative recovery procedures are presented for model B. For a single plot, the predictions varied significantly among the models and estimation procedures with no consistent pattern. Predictions of arithmetic mean heights were best for plots with no understory, while predictions of upper quantiles were consistent in all plots. For. Sci. 45(3):407-422.
UR - http://www.ingentaconnect.com/content/saf/fs/1999/00000045/00000003/art00012
ER -