Dubovik D. S., Tarakanov V. V. Monitoring of the Archive and Forest Seed Orchards' Condition Using High Resolution Pleiades Satellite Data
1 West-Siberian Department of V. N. Sukachev Institute of Forest, Russian Academy of Sciences,
Siberian Branch, Federal Research Center Krasnoyarsk Scientific Center,
Russian Academy of Sciences, Siberian Branch
Zukovsky str., 100/1, Novosibirsk, 630082 Russian Federation
2 Siberian State University of Geosystems and Technologies
Plakhotny str., 10, Novosibirsk, 630018 Russian Federation
3 Novosibirsk State Agrarian University
Dobrolyubov str., 160, Novosibirsk, 630039 Russian Federation
E-mail: d.d@ngs.ru, tarh012@mail.ru
Abstract
UDC 528.8+630
How to cite: Dubovik D. S.1, 2, Tarakanov V. V.1, 3 Monitoring of the archive and forest seed orchards' condition using high resolution Pleiades satellite data // Sibirskij Lesnoj Zurnal (Sib. J. For. Sci.). 2020. N. 4. P. 97–105 (in Russian with English abstract and references).
DOI: 10.15372/SJFS20200411
© Dubovik D. S., Tarakanov V. V., 2020
Thousands of hectares of forest seed orchards and archival uterine plantations of plus trees have been created in the Russian Federation. Their inventory and monitoring can be carried out using ultra-high resolution satellite imagery. The purpose of the work was to test this approach based on Pleiades 1A data, optimal in terms of price / quality ratio, for inventory and assessment of the state of archival plantations and forest seed orchards of conifers, concentrated on an area of about 200 hectares of the joint stock comp. Berdskiy forestry enterprise breeding nursery (Iskitimskiy district of the Novosibirsk Oblast). The inventory was carried out on the basis of visual interpretation of the synthesized multispectral images with increased resolution due to the panchromatic channel, taking into account passport and other data on the territory of the nursery. To control the results of visual decoding, a selective field inventory was carried out. The brightness of the pixels of the initial multispectral image in the central parts of the crowns of various trees and plantation areas not covered by crowns is compared. The results obtained illustrate the possibility of identifying healthy trees of cultivated species, as well as fallen and replaced by deciduous self-seeding trees. The described approach can be used for operational remote monitoring of archival plantations and forest seed orchards of conifers.
Article
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