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

[Text] / S. . Wilhelm [et al.] // Forests. - 2014. - Vol. 5, Is. 8. - P1999-2015, DOI 10.3390/f5081999. - Cited References: 50. - The authors want to thank the employees of the Sukachev Institute of Forest in Krasnoyarsk, Russia, Siberia, who were involved in the validation of the mapping results. In addition, thanks go out to Tim Robin van Doorn for proofreading this article. The maps were produced within the FP 7 EU-Russia ZAPAS (Russian: 3anac, stands for GSV or forest stock) project on the assessment and monitoring of forest resources in central Siberia. ZAPAS was funded by the European Commission, Space, Cross-cutting Activities, International Cooperation, Grant No. SPA.2010.3.2-01 EU-Russia Cooperation in Global Monitoring for Environment and Security (GMES). . - ISSN 1999-4907РУБ Forestry

Аннотация: The forests of the Russian Taiga can be described as an enormous biomass and carbon reservoir. Therefore, they are of utmost importance for the global carbon cycle. Large-area forest inventories in these mostly remote regions are associated with logistical problems and high financial efforts. Remotely-sensed data from satellite platforms may have the capability to provide such huge amounts of information. This study presents an application-oriented approach to derive aboveground growing stock volume (GSV) maps using the annual large-area L-band backscatter mosaics provided by the Japan Aerospace Exploration Agency (JAXA). Furthermore, a multi-temporal map has been created to improve GSV estimation accuracy. Based on information from Russian forest inventory data, the maps were generated using the machine learning algorithm, RandomForest. The results showed the high potential of this method for an operational, large-scale and high-resolution biomass estimation over boreal forests. An RMSE from 55.2 to 63.3 m(3)/ha could be obtained for the annual maps. Using the multi-temporal approach, the error could be slightly reduced to 54.4 m(3)/ha.

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Держатели документа:
[Wilhelm, Sebastian] Earth Observat Serv EOS Jena GmbH, D-07743 Jena, Germany
[Huettich, Christian
Schmullius, Christiane] Univ Jena, Dept Earth Observat, D-07743 Jena, Germany
[Korets, Mikhail] Russian Acad Sci, VN Sukachev Inst Forest, Siberian Branch, Krasnoyarsk 660036, Russia
ИЛ СО РАН

Доп.точки доступа:
Wilhelm, S...; Huttich, C...; Korets, M...; Schmullius, C...; European Commission, Space, Cross-cutting Activities, International Cooperation, EU-Russia Cooperation in Global Monitoring for Environment and Security (GMES) [SPA.2010.3.2-01]