Abstract
In this paper the concept of integrated modeling and simulation processes of the Complex Natural and Technological Object (CNTO) is presented. The main goal of the investigations consists in the practice of the predetermined modeling. The practice direction as the remote sensing forest monitoring is proposed by the authors. Here the methodical foundations of the integrated modeling and simulation, the process of CNTO operation, the technology of the remote sensing forest monitoring are considered. Principal concern is attended to the continuity of the model and object solving practical issues. More over results of CNTO remote sensing forest monitoring make it possible to adapt models of this system to changing environment conformably to the forest management.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Ohtilev, M.Y., Sokolov, B.V., Yusupov, R.M.: Intellectual technologies for monitoring and control of structure-dynamics of complex technical objects. Nauka, Moscow (2006)
Skurihin, V.I., Zabrodsky, V.A., Kopeychenko, Y.V.: Adaptive control systems in machine-building industry. Mashinostroenie, Moscow (1989)
Rastrigin, L.A.: Adaptation of Complex Systems. Zinatne, Riga (1981)
Ivanov, D., Sokolov, B., Kaeschel, J.: A multi-structural framework for adaptive supply chain planning and operations with structure dynamics considerations. Eur. J. Oper. Res. 200(2), 409–420 (2010)
Sokolov, B., Zelentsov, V., Yusupov, R., Merkuryev, Y.: Information fusion multiple-models quality definition and estimation. In: Proceedings of the International Conference on Harbor Maritime and Multimodal Logistics M&S, pp. 102–111. Vienna, Austria, 19–21 September 2012
Ivanov, D., Sokolov, B.: Control and system-theoretic identification of the supply chain dynamics domain for planning, analysis and adaptation of performance under uncertainty. Eur. J. Oper. Res. 224(2), 313–323 (2012) (Elsevier, London)
Acknowledgments
The research described in this paper is supported by the Russian Foundation for Basic Research (grants 12-07-00302, 13-07-00279, 13-08-00702, 13-08-01250, 13-07-12120-ofi-m, 12-07-13119-ofi-m-RGD), Department of Nanotechnologies and Information Technologies of the RAS (project 2.11), by Postdoc project in technical and economic disciplines at the Mendel University in Brno (reg. number CZ.1.07/2.3.00/30.0031), by ESTLATRUS projects 1.2./ELRI-121/2011/13 «Baltic ICT Platform» and 2.1/ELRI-184/2011/14 «Integrated Intelligent Platform for Monitoring the Cross-Border Natural-Technological Systems» as a part of the Estonia–Latvia–Russia cross border cooperation Program within European Neighborhood and Partnership instrument 2007–2013. This work was partially financially supported by Government of Russian Federation, Grant 074-U01.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Sokolov, B.V., Zelentsov, V.A., Brovkina, O., Mochalov, V.F., Potryasaev, S.A. (2014). Complex Objects Remote Sensing Forest Monitoring and Modeling. In: Silhavy, R., Senkerik, R., Oplatkova, Z., Silhavy, P., Prokopova, Z. (eds) Modern Trends and Techniques in Computer Science. Advances in Intelligent Systems and Computing, vol 285. Springer, Cham. https://doi.org/10.1007/978-3-319-06740-7_37
Download citation
DOI: https://doi.org/10.1007/978-3-319-06740-7_37
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-06739-1
Online ISBN: 978-3-319-06740-7
eBook Packages: EngineeringEngineering (R0)