Abstract

The weighted k-nearest neighbour (kNN) method was used for estimating stem volume (m(3) ha(-1)) and basal area (m(2) ha(-1)) on a compartment level (average 19 ha) by combining satellite image data with measurements from Swedish National Forest (NFI) inventory plots. In the kNN method each estimation location (target plot) is assigned a value that is an average, which is weighted, of the attribute data from the k closest reference plots (NFI plots). The distance between target and reference plot was measured on different scales, which were transforms of spectral values and/or ancillary data. The standard error (assuming bias with no trend) of stem volume estimates in the compartments was 36% using only spectral data. This estimation accuracy improved to 17% if site index, age of the forest and mean tree height (ancillary data) were known for the compartments. Low volumes were overestimated and high volumes underestimated. This bias was reduced if ancillary data were added but was also dependent on the transform of the original scales

Published in

Scandinavian Journal of Forest Research
2000, volume: 15, number: 1, pages: 103-111
Publisher: SCANDINAVIAN UNIVERSITY PRESS

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