On the analysis of cubic smoothing spline-based stem curve prediction for forest harvesters

In the cut-to-length (CTL) harvesting system the felling, delimbing, and bucking processes take place at the harvesting site. The optimal cutting points along the stem can be determined if the whole stem curve is known. In practice, however, it is not economically feasible to measure the whole stem first before crosscutting, and hence the first cutting decisions are usually made when only a short part of the stem is known. Predictions are used to determine the cutting pattern to compensate for the unknown part of the stem. In this paper our interest focuses on stem curve prediction in a harvesting situation and we study a modified version of a cubic smoothing spline-based prediction method devised by Nummi and Mottonen (T. Nummi and J. Mottonen. 2004. J. Appl. Stat. 31: 105–114). The method's performance was assessed in five different final felling stands of spruce and pine, collected by harvesters in southern Finland. The results for the spline approach are very promising and show the superiority of the ...

[1]  Laura Koskela,et al.  STATISTICAL PROPERTIES OF THE APPORTIONMENT DEGREE AND ALTERNATIVE MEASURES IN BUCKING , 2005 .

[2]  On the construction of monotony preserving taper curves. , 1988 .

[3]  Tapio Nummi,et al.  Prediction of Stem Measurements of Scots Pine , 2004 .

[4]  Hannu Konttinen,et al.  Tracks in the Forest: The Evolution of Logging Machinery , 1997 .

[5]  J. P. Demaerschalk,et al.  The whole-bole system: a conditioned dual-equation system for precise prediction of tree profiles , 1977 .

[6]  J. C. Rennie,et al.  Merchantable height in lieu of total height in stem profile equations , 1988 .

[7]  Tapio Nummi,et al.  Estimation and prediction for low degree polynomial models under measurement errors with an application to forest harvesters , 2004 .

[8]  B. Silverman,et al.  Nonparametric regression and generalized linear models , 1994 .

[9]  K. Nordhausen,et al.  Estimation of the diameter distribution of a stand marked for cutting using finite mixtures , 2007 .

[10]  Subhabrata Chakraborti,et al.  Nonparametric Statistical Inference , 2011, International Encyclopedia of Statistical Science.

[11]  K. Gadow,et al.  Comparison of three stem profile equations for Quercus robur L. , 1996 .

[12]  M. Kenward,et al.  The Analysis of Designed Experiments and Longitudinal Data by Using Smoothing Splines , 1999 .

[13]  M. Stone Cross‐Validatory Choice and Assessment of Statistical Predictions , 1976 .

[14]  K. Eerikäinen Stem volume models with random coefficients for Pinus kesiya in Tanzania, Zambia, and Zimbabwe , 2001 .

[15]  Douglas A. Maguire,et al.  Modeling stem taper of three central Oregon species using nonlinear mixed effects models and autoregressive error structures , 2003 .

[16]  G. Reinsel Elements of Multivariate Time Series Analysis , 1995 .

[17]  Bruce E. Borders,et al.  Number of diameters required to represent stem profiles using interpolated cubic splines , 1996 .

[18]  Steven G. Gilmour,et al.  The analysis of designed experiments and longitudinal data by using smoothing splines - Discussion , 1999 .

[19]  J. Lappi Mixed linear models for analyzing and predicting stem form variation of Scots pine , 1986 .

[20]  A. Kozak,et al.  A variable-exponent taper equation , 1988 .

[21]  Jouko Laasasenaho Taper curve and volume functions for pine, spruce and birch [Pinus sylvestris, Picea abies, Betula pendula, Betula pubescens] , 1982 .

[22]  Jouko Laasasenaho,et al.  On the construction of taper curves using spline functions. , 1979 .

[23]  R. M. Newnham Variable-form taper functions for four Alberta tree species , 1992 .

[24]  Erkki P. Liski,et al.  Prediction of tree stems to improve efficiency in automatized harvesting of forests , 1995 .

[25]  M. Naesberg,et al.  Mathematical programming models for optimal log bucking , 1985 .

[26]  Jori Uusitalo,et al.  Comparison of four measures designed for assessing the fit between the demand and output distributions of logs , 2005 .