View source: R/ManagementProb.R
management.prob | R Documentation |
Estimates de probability of a stand to be harvested or thinning following Anton-Fernandez et al. (20012).
management.prob(tr, fl, fun.final.felling = "harv.prob", fun.thinning = "thin.prob", common.vars, this.period, next.period, ...) harv.prob(region, skidding.distance.100m, AgeTo5, vuprha.m3.ha, slope.per, SI.m, SI.spp) thin.prob(region, skidding.distance.100m, AgeTo5, vuprha.m3.ha, slope.per, SI.m, SI.spp)
tr |
A trList class object. |
fl |
A list describing the plot data. |
fun.final.felling |
Function to use to calculate final felling. |
fun.thinning |
Function to use to calculate thinning. |
common.vars |
A list with at least variables dev.class and vuprha.m3.ha. |
this.period |
The period for which to calculate final felling and thinning probability. |
next.period |
The next period to the one for which final felling and thinning probability are to be calculated. |
... |
|
region |
A vector containing the region in Norway where every plot is situated. |
skidding.distance.100m |
A vector containing skidding for each plot. |
AgeTo5 |
A vector containing number of years to development class 5 for each plot. |
vuprha.m3.ha |
Volume per ha in cubic meters per ha for each plot. |
slope.per |
Slope, in percentatge, for each plot. |
SI.m |
Site index (SI) in m. |
SI.spp |
Species for which the SI is calculated (1 = spruce, 2 = pine, 3 = deciduous). |
It returns a list with one element:
mng |
a vector with the management to apply to each plot. |
Clara Anton Fernandez caf@nibio.no
Antón-Fernández, C. and Astrup, R. 2012 Empirical harvest models and their use in regional business-as-usual scenarios of timber supply and carbon stock development. Scandinavian Journal of Forest Research, 27, 4, 379–392.
foo.matrix <- matrix(0, nrow = length(tr$dbh), ncol = (5 +1)) colnames(foo.matrix) <- paste("t", 0:5, sep = "") foo.dbh <- foo.height <- foo.matrix foo.dbh[,1] <- tr$dbh foo.height[,1] <- tr$height trl <- list( plot.id = tr$plot.id, treeid = tr$treeid, dbh.mm = foo.dbh, height.dm = foo.height, yrs.sim = rep(0, nrow(tr)), tree.sp = factor(tr$tree.sp) ) tr.i <- trList$new(data = trl, nperiods = as.integer(5)) common.vars <- prep.common.vars.fun( tr = tr.i, fl = fl, i.period = 0, this.period = "t0", common.vars = "NULL", vars.required = c("spp", "SBA.m2.ha", "QMD.cm", "vuprha.m3.ha", "AgeTo5"), period.length = 5 ) fl$management <- data.frame(matrix(NA, ncol = tr.i$nperiods, nrow = nrow(tr.i$data$dbh.mm))) names(fl$management) <- paste0("t", 1:tr.i$nperiods) management.prob(tr.i, fl, fun.final.felling = "harv.prob", fun.thinning = "thin.prob", common.vars = common.vars$res, this.period = "t0", next.period = "t1") harv.prob(region = fl$region[1:3], skidding.distance.100m = fl$skidding.distance.100[1:3], AgeTo5 = c(50, 20, 15), vuprha.m3.ha = common.vars$res$vuprha.m3.ha[1:3], slope.per = fl$slope.per[1:3], SI.m = fl$SI.m[1:3], SI.spp = fl$SI.spp[1:3]) thin.prob(region = fl$region[1:3], skidding.distance.100m = fl$skidding.distance.100[1:3], AgeTo5 = c(50, 20, 15), vuprha.m3.ha = common.vars$res$vuprha.m3.ha[1:3], slope.per = fl$slope.per[1:3], SI.m = fl$SI.m[1:3], SI.spp = fl$SI.spp[1:3] )
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