Optimal bucking of stems from terrestrial laser scanning data to maximize forest value

ABSTRACT

An optimal bucking strategy that allocates cutting patterns to forest stands based on the individual characteristics of each stem is critical for maximizing value recovery. However, cutting patterns are usually excluded from bucking algorithms due to the difficulties associated with capturing tree quality features when collecting forest inventory data (e.g. branchiness and tree shape). This paper presents a non-destructive and fully automated methodology for the optimal bucking of stems based on terrestrial laser scanning (TLS) point clouds that aims to maximize the economic value of trees in a forest stand. It is based on the three-dimensional modelling of stems and includes the diameter and curvature of each log. The bucking algorithm also considers several timber products and calculates the most valuable log combination for each tree. The methodology was tested in a Pinus radiata plot with 120 trees, and the results were compared with those obtained with input data that do not take curvature into account: i.e. only diameters from TLS and taper equations. The analysis of the results suggests that not including curvature in the algorithm for optimal bucking results in an overestimation of the commercial value of timber products.

KEYWORDS:

• Optimal bucking
• dynamic programming
• taper equation
• stem curvature
• timber products
• Pinus radiata

Acknowledgments

The authors wish to thank CETEMAS field workers (Manuel Alonso-Graña López and Ernesto Menéndez Álvarez) for carrying out the scanning of the plot together with some of the authors. Thanks also to Ronnie Lendrum, scientific editor and proof-reader, for correcting the English of the manuscript.

Disclosure statement

No potential conflict of interest was reported by the author(s).

List of abbreviations
ALS:	=	Aerial Laser Scanning
BVAL:	=	current best value
dbh:	=	diameter at breast height
DP:	=	Dynamic Programming
GNSS:	=	Global Navigation Satellite Systems
h:	=	total height
LED:	=	Large End Diameter
PDF:	=	Probability Density Function
PLS:	=	Portable Laser Scanning
RMSE:	=	Root Mean Square Error
SED:	=	Small End Diameter
TLS:	=	Terrestrial Laser Scanning
TS:	=	Temporary Stage
VAL:	=	Value of the log being assessed by the optimal bucking algorithm
ZLED:	=	Position of the LED in the stem in relation to the ground
ZSED:	=	Position of the SED in the stem in relation to the ground

Notes

1 A product is also referred to as a log type, so both terms are used interchangeably throughout the text.

Additional information

Funding

Carlos Cabo received funding from the UK Natural Environment Research Council (NE/T001194/1), and from the Spanish Government (Ministry of Universities) and the European Union (NextGenerationEU), within the project MU-21-UP2021-030