ESTIMATION OF TIMBER VOLUME IN A CONIFEROUS PLANTATION FOREST USING LANDSAT TM

Optimisation of economic return from forests requires that comprehensi ve forest inventory data be available to support the design of harvest ing strategies. Such inventory data can potentially be obtained by rem ote sensing. This study investigates the accuracy with which wood volu me (m(3) ha(-1)) in a plantation forest can be calculated from Landsat TM data at the pixel and forest-stand spatial scales. Wood volumes we re estimated from regression analysis, nonparametric line-fitting, and an N-dimensional K-nearest-neighbour classification scheme. At the pi xel scale, relations between Landsat data and measured wood volume wer e found to be significant but weak, with r(2) values of less than or e qual to 0.3, and with correspondingly poor estimates of wood volume (r oot-mean-square errors-rmses-of > 100 m(3) ha(-1)). By averaging the p ixel-scale estimates, wood volume estimates of acceptable accuracy wer e obtained for forest-stand areas of about 40 ha (rmses of less than o r equal to 46 m(3) ha(-1)). Parametric regression performed slightly b etter overall than non-parametric line fitting techniques for estimati ng wood volume. Estimates of similar accuracy to those obtained by reg ression were also given by NK-classification at the pixel-scale, provi ded K was large (greater than or equal to 15), although the classifier produced biased results at the forest-stand scale. It is concluded th at Landsat TM only provides an acceptable data source for estimating w ood volumes in plantation forests for areas of about 40 ha and larger. The very low dynamic range in the Landsat data is probably a signific ant factor limiting its use for inventory at more detailed scales.