Труды сотрудников ИЛ им. В.Н. Сукачева СО РАН

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    Role of an Altitudinal Zonal Basis and Remote Sensing Data in the Sustainable Management of Mountain Forests
/ D. I. Nazimova, E. I. Ponomarev, M. E. Konovalova // Contemp. Probl. Ecol. - 2020. - Vol. 13, Is. 7. - P742-753, DOI 10.1134/S1995425520070070 . - ISSN 1995-4255
Аннотация: Abstract: This paper substantiates the necessity of improving the principles of using natural basis for ecosystem-focused forest management in mountain conditions using all the collected knowledge, regional databases, and new remote sensing facilities. The results of applying the spectral features of vegetation using the thermal range for studying the altitudinal differentiation of forest cover are given based on the example of the mountains of the Altai-Sayan region. Thus, forest-steppe, subtaiga light-coniferous small-leaved deciduous, mountain dark coniferous chern, mountain dark coniferous taiga, and subalpine classes of altitudinal belt complexes (ABC) can be defined in the Yenisei part of the Sayans. Particular forest-management systems should be used for each of them, taking into account the natural features of forests and their management purpose. One important task for mountain forestry and whole multipurpose forest use is to improve the ecological and geographical basis and present it in the form of medium-scale maps, which reflect not only the formational composition of forest cover, but also the altitudinal classes of ecosystems. Modern satellite remote sensing systems coupled with GIS technologies open up new possibilities for forest cover inventory, monitoring, and study methods. This makes it possible to introduce a high-quality natural basis into forest management, which is currently highly relevant at all levels of forest planning: from exploitation projects for separate forest plots to forest plans of federal subjects of the Russian Federation. © 2020, Pleiades Publishing, Ltd.

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Держатели документа:
Sukachev Institute of Forest, Siberian Branch, Russian Academy of Sciences, Krasnoyarsk, 660036, Russian Federation
Siberian Federal University, Krasnoyarsk, 660041, Russian Federation

Доп.точки доступа:
Nazimova, D. I.; Ponomarev, E. I.; Konovalova, M. E.