Please use this identifier to cite or link to this item:https://hdl.handle.net/20.500.12259/84299
Type of publication: research article
Type of publication (PDB): Straipsnis konferencijos medžiagoje kitose duomenų bazėse / Article in conference proceedings in other databases (P1c)
Field of Science: Miškotyra / Forestry (A004)
Author(s): Jonikavičius, Donatas
Title: Forest change detection using knn (k-nearest neighbour) - based estimations of point-wise forest characteristics
Is part of: Research for rural development 2008: international scientific conference proceedings, Jelgava, Latvia. Jelgava : Latvia University of Agriculture, 2008
Extent: p. 122-127
Date: 2008
Keywords: Forest inventory;Satellite images;Knn (k-nearest neighbour) method;Point-wise forest characteristics;Change detection
Abstract: 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 neighbor 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 under 15 years according to the data of stand-wise inventory of year 2003. Different setting for the methods investigated are evaluated, too
Internet: https://hdl.handle.net/20.500.12259/84299
Affiliation(s): Vytauto Didžiojo universitetas
Žemės ūkio akademija
Appears in Collections:Universiteto mokslo publikacijos / University Research Publications

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