Please use this identifier to cite or link to this item:https://hdl.handle.net/20.500.12259/84202
Type of publication: Straipsnis konferencijos medžiagoje Clarivate Analytics Web of Science ar/ir Scopus / Article in Clarivate Analytics Web of Science or Scopus DB conference proceedings (P1a)
Field of Science: Miškotyra / Forestry (A004)
Author(s): Jonikavičius, Donatas;Mozgeris, Gintautas
Title: Estimation of forest parameters using the non-parametric techniques and satellite images at compartment level
Is part of: Research for rural development 2010 : annual 16th international scientific conference proceedings, Jelgava, Latvia, 19-21 May, 2010. Jelgava: Latvia University of Agriculture, 2010, vol. 1
Extent: p. 194-200
Date: 2010
Keywords: Forest inventory;Satellite images;K-nearest neighbor;Most similar neighbor
Abstract: This paper discusses the use of medium resolution Landsat TM satellite images to support conventional approaches of Lithuanian forest inventory practices. Estimation accuracies achieved using just field measured sample plots, Landsat TM satellite images and two non-parametric k-nearest neighbor and most similar neighbor estimators were studied at a level of compartments. 19 mature forest areas, prepared for final felling with GPS measured borders and all trees callipered, were used for validation. Notably higher estimation accuracies were achieved using field sample plots distributed through the whole forest area studied than just ones located on mature forest stands. The root mean square deviations in estimating compartment-wise volume of growing stock per 1 ha was around 27-28% if the best variant of estimation approach was used. Possible influence of the accuracy in locating the borders of validation areas on the estimations is discussed in the paper, too
Internet: http://www.llu.lv/getfile.php?id=27929
Affiliation(s): Vytauto Didžiojo universitetas
Žemės ūkio akademija
Appears in Collections:Universiteto mokslo publikacijos / University Research Publications

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