Description Usage Arguments Details Value Note Author(s) References Examples
This vectorized function uses models and parameter estimates from Wykoff et al. (1982) to predict tree heights given over-bark diameter measurements (cm) taken at 1.37 m (4'6”). The function ht.fvs.ni.ft performs the computation in imperial units, and ht.fvs.ni.m is a wrapper for convenience.
1 2 | ht.fvs.ni.ft(spp, dbh.in)
ht.fvs.ni.m(spp, dbh.cm)
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spp |
Tree species. Must be one of: WP, WL, DF, GF, WH, WC, LP, ES, SF, PP, MH |
dbh.cm |
Tree diameter, cm, measured at 1.37 m. from the ground. |
dbh.in |
Tree diameter, in., measured at 1.37 m. from the ground. |
The species are: WP = white pine, WL = western larch, DF = Douglas-fir, GF = grand fir, WH = western hemlock, WC = western red cedar, LP = lodgepole pine, ES = Engelmann spruce, SF = subalpine fir, PP = ponderosa pine, and MH = mountain hemlock.
The function was fitted using least squares regression; the resposne variable was log of height and the predictor variable 1 / (DBH + 1).
The function returns a vector of tree heights, in metres.
The function doesn't perform any input checks. Caveat computator.
Andrew Robinson <apro@unimelb.edu.au>
Robinson, A.P., and J.D. Hamann. 2010. Forest Analytics with R: an Introduction. Springer.
Wykoff, W. R., Crookston, N. L., Stage, A. R., 1982. User's Guide to the Stand Prognosis Model. GTR-INT 133, USDA Forest Service, Ogden, UT.
1 | ht.fvs.ni.m(c("DF, WH"), c(25, 27))
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