stumplift: Productivity of stump lifting machines.

stumpliftR Documentation

Productivity of stump lifting machines.

Description

The productivity of stump lifting machines on three Norway Spruce (Picea Abies) clearcut areas (sites). Stumps are lifted for use as bioenergy. The data were collected from three sites in Central Finland.

Usage

data(stumplift)

Format

A data frame with 485 observations on the following 5 variables.

Stump

A unique stump id based on the order of processing. The successive numbers are usually close to each other in the clearcut area, but nearby trees do not necessarily have small difference in stump id.

Machine

The machine/clearcut/dirver combination. A factor with three levels.

Diameter

Stump diameter, cm.

Time

Processing time, seconds.

Productivity

Productivity, m^3/effective working hour

Details

Each site was operated with different machine and driver so that the effect of site, machine and driver cannot be separated. The volume of each stump was estimated using the function of Laitila (2008), based on the stump diameter. A work system study was conducted to measure the processing time (seconds) and productivity (m^3/hour) for each stump.

References

Teijo Palander, Kalle Karha, Lauri Mehtatalo 2016. Applying polynomial regression modeling to productivity analysis of sustainable stump harvesting. Scandinavian Journal of Forest Reseach. doi: 10.1080/02827581.2016.1238957

Teijo Palander, Janne Smolander, Kalle Karha, 2015. Work system study of three stump-lifting devices in Finland. Scandinavian Journal of Forest Research 30(6) 558-567, doi: 10.1080/02827581.2015.1027731

Mehtatalo, Lauri and Lappi, Juha 2020. Biometry for Forestry and Environmental Data: with examples in R. New York: Chapman and Hall/CRC. 426 p. doi: 10.1201/9780429173462

Examples

data(stumplift)
library(nlme)

modConstPow<-gls(Productivity~Machine+Machine*I((Diameter-70)^2),
                 data=stumplift,
                 weights=varPower(),
                 corr=corAR1(form=~Stump|Machine))
           

lmfor documentation built on April 30, 2022, 1:08 a.m.