GIS-BASED FOREST COVER CLASSIFICATION AND MAPPING (PRINCIPLES AND TECHNIQUE)
Vera Ryzhkova, Irina Danilova, Michael Korets
Pages: 177-189
Published: 28 May 2015
Views: 3,074
Downloads: 803
Abstract: Automated classification and mapping of forest cover can be accomplished only through interdisciplinary research efforts. A technique of automated classification and mapping of potential forest growing conditions and forest regeneration dynamics was developed and applied to south central Siberia. This technique is based on GIS-technology involving spatial analysis of a digital elevation model (Shuttle Radar Topography Mission (SRTM)), Landsat 5-TM images and ground observation data. In this way, an algorithm of conjugate analysis of dissimilar data in a stepwise manner was developed. The vector maps obtained reflect forest growing condition types, forest types, and regeneration age stages. Although the obtained maps show current vegetation cover state, the map legend is based on the classification, which takes into account site-specific forest regeneration development. Therefore, these maps enable to predict forest regeneration dynamics in different growing condition.
Keywords: central siberia, digital elevation model (dem), geographical information system (gis), potential forest growing conditions, forest regeneration dynami
Cite this article: Vera Ryzhkova, Irina Danilova, Michael Korets. GIS-BASED FOREST COVER CLASSIFICATION AND MAPPING (PRINCIPLES AND TECHNIQUE). Journal of International Scientific Publications: Ecology & Safety 9, 177-189 (2015). https://www.scientific-publications.net/en/article/1000709/
Back to the contents of the volume
© 2025 The Author(s). This is an open access article distributed under the terms of the
Creative Commons Attribution License https://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. This permission does not cover any third party copyrighted material which may appear in the work requested.
Disclaimer: The Publisher and/or the editor(s) are not responsible for the statements, opinions, and data contained in any published works. These are solely the views of the individual author(s) and contributor(s). The Publisher and/or the editor(s) disclaim any liability for injury to individuals or property arising from the ideas, methods, instructions, or products mentioned in the content.