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Titolo: Recovering tree heights from airborne laser scanner data
Autore: Magnussen, S; Eggermont, P; LaRiccia, VN;
 Indirizzi:
 Canadian Forestry Serv, Victoria, BC V8Z 1M5, Canada Canadian Forestry Serv Victoria BC Canada V8Z 1M5 ria, BC V8Z 1M5, Canada Univ Delaware, Dept Math Sci, Newark, DE 19716 USA Univ Delaware Newark DE USA 19716 re, Dept Math Sci, Newark, DE 19716 USA
 Titolo Testata:
 FOREST SCIENCE
fascicolo: 3,
volume: 45,
anno: 1999,
pagine: 407  422
 SICI:
 0015749X(199908)45:3<407:RTHFAL>2.0.ZU;23
 Fonte:
 ISI
 Lingua:
 ENG
 Soggetto:
 DENSITYESTIMATION; NONPARAMETRIC DECONVOLUTION; FOREST CANOPY; DIAMETER; SYSTEM; DISTRIBUTIONS; REGRESSION; MODELS; STANDS;
 Keywords:
 canopy height; crown area; PPS sampling; deconvolution; error function; Weibull distribution; extreme value distribution; EM algorithm;
 Tipo documento:
 Article
 Natura:
 Periodico
 Settore Disciplinare:
 Agriculture,Biology & Environmental Sciences
 Citazioni:
 57
 Recensione:
 Indirizzi per estratti:
 Indirizzo: Magnussen, S Canadian Forestry Serv, 506 W Burnside Rd, Victoria, BC V8Z 1M5, Canada Canadian Forestry Serv 506 W Burnside Rd Victoria BC Canada V8Z 1M5



 Citazione:
 S. Magnussen et al., "Recovering tree heights from airborne laser scanner data", FOREST SCI, 45(3), 1999, pp. 407422
Abstract
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 standsof Douglasfir. Model estimates of recovered arithmetic mean tree heights and quantiles (75%, 85%, and 95%) were not significantly (P > 0.24) different from groundbased equivalents. An overall mean bias of 3 m in the lasercanopy heights was eliminated by both methods, The median absolute difference between observed and predicted plot means and quantiles we re reduced by 40 to 60%. Three alternative recovery procedures are presented for model B. For a single plot, the predictions varied significantly among the modelsand 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.
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Documento generato il 26/11/20 alle ore 11:09:43