Abstract

Information about the state of the forest is of vital importance in forest management planning. To enable high-precision modelling. many forest planning systems demand input data at the single-tree level, The conventional strategy for collecting such data is a plot-wise field inventory. This is expensive and, thus, cost-efficient alternatives are of interest. During recent years, the focus has been on remote sensing techniques. The k nearest neighbour (kNN) estimation method is a way to assign plot-wise data to all stands in a forest area, using remotely sensed data in connection with a sparse sample of field reference plots. Plot-wise aerial photograph interpretations combined with information from a stand register were used in this study. Nearness to a reference plot was decided upon using a regression transform distance. Standing stem volume was estimated with a relative root mean square error (RMSE) equal to 20% at the stand level, while age could be estimated with a RMSE equal to 15%. A cost-efficient data-capturing strategy could be to assign plot data with the presented k-NN method to some types of forest, while using traditional field inventories in other, more valuable, stands.

Keywords

carrier phase GPS; forest inventory; prediction difference distance; reference sample plot method; remote sensing

Published in

Scandinavian Journal of Forest Research
2001, Volume: 16, number: 1, pages: 67-78
Publisher: TAYLOR & FRANCIS AS

SLU Authors

• Holmström, Hampus

  • Department of Forest Resource Management and Geomatics, Swedish University of Agricultural Sciences
    

• Nilsson, Mats

  • Department of Forest Resource Management and Geomatics, Swedish University of Agricultural Sciences
    

• Ståhl, Göran

  • Department of Forest Resource Management and Geomatics, Swedish University of Agricultural Sciences
    

UKÄ Subject classification

Forest Science


Publication identifier

DOI: https://doi.org/10.1080/028275801300004424

Permanent link to this page (URI)

https://res.slu.se/id/publ/41910