Forest change detection using knn (k-nearest neighbour)-based estimations of point-wise forest characteristics
2008
Jonikavicius, D., Lithuanian Univ. of Agriculture, Akademija, Kauno reg. (Lithuania)
This paper discusses the usability of non-parametric knn (k-nearest neighbour) method to detect changes in forest areas from satellite images. Spot Xi images acquired 1999, main forest characteristics from field measured sample plots and data of conventional stand-wise forest inventory from the year 1988 were used to estimate the grids of following forest characteristics: mean age of main forest storey, diameter, basal area, height, volume per 1 ha, as well as the percentages of coniferous, soft and hard deciduous tree species. The differences of grids, created using stand-wise forest attributes from the 1988 inventory and estimated using the k-nearest neighbour methods were experimented to detect changes in the forest. 68.7-75.5% of areas, classified as the potential felling areas, were detected to be clear cut areas or young stands less than 15 years according to the data of stand-wise inventory of year 2003. Different settings for the methods investigated are evaluated, too.
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