ON THE PREDICTION QUALITY IMPROVEMENT OF VEGETATION IN RUSSIA ACCORDING TO SPACE PROBES
(ON THE EXAMPLE OF SEVER MODEL)

Chumachenko Evgeny Nikolaevich, Doctor of engineering sciences, professor, head of sub-department of mathematical modeling, Moscow State Institute of Electronics and Mathematics (technical university), mmkaf@miem.edu.ru
Kulagin Vladimir Petrovich, Doctor of engineering sciences, professor, rector of Moscow State Institute of Electronics and Mathematics (technical university), kvp@miem.edu.ru
Khvostikov Sergey Antonovich, Postgraduate student, Moscow State Institute of Electronics and Mathematics (technical university), mmkaf@miem.edu.ru 

629.7.05

The authors propose a method of quality estimation for Dynamic Global Vegetation Model, based on comparison with remote sensing products, and methods to improve the quality. In order to improve the model quality for the territory of Russia, the researchers have changed the algorithm and optimized the model parameters. The final model more precisely reproduces distribution of vegetation types for the territory of Russia. 

modeling, vegetation, DGVM, SEVER, optimization.