Operational Capability Assessment for the NA-GS Hyperspectral Sensor Using Simulation and Statistical Modeling
- Autores: Zotov S.1, Dmitriev E.2, Shibanov S.1, Kozoderov V.3, Donskoy S.4
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Afiliações:
- Moscow Institute of Physics and Technology
- Institute of Numerical Mathematics, Russian Academy of Sciences
- Moscow State University
- Roslesinforg
- Edição: Volume 55, Nº 9 (2019)
- Páginas: 1457-1464
- Seção: Space Vehicles and Systems of Programs of the Institute of Earth Crust
- URL: https://journals.rcsi.science/0001-4338/article/view/148835
- DOI: https://doi.org/10.1134/S0001433819090597
- ID: 148835
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Resumo
The NA-GS hyperspectral camera (Hyperspectrometer scientific instrument) produced by NPO Lepton (Zelenograd, Moscow) will be installed on the Russian segment of the International Space Station within a program for Earth remote sensing from space for experimentally testing the ground–space system for monitoring and forecasting the development of natural and manmade disasters. The practical application of this system is associated with performing tasks of thematic processing of hyperspectral images that should satisfy certain quality criteria. In this article, we propose a technique for assessing the operational capabilities of the NA-GS based on simulation and statistical modeling data. The concept of the proposed simulation and statistical model (SSM) includes modeling a test polygon of complex shape and simulating the observation of selected parts of the test polygon with a given accuracy using a hyperspectral sensor and taking into account cloud cover and the zenith angle of the Sun. The effect of external observation conditions on the quality of hyperspectral images is considered. Numerical experiments are conducted for the selected test areas. The analysis of the calculation results confirms the reliability of the proposed technique.
Sobre autores
S. Zotov
Moscow Institute of Physics and Technology
Autor responsável pela correspondência
Email: zotov.sa@mipt.ru
Rússia, Dolgoprudny
E. Dmitriev
Institute of Numerical Mathematics, Russian Academy of Sciences
Email: zotov.sa@mipt.ru
Rússia, Moscow
S. Shibanov
Moscow Institute of Physics and Technology
Email: zotov.sa@mipt.ru
Rússia, Dolgoprudny
V. Kozoderov
Moscow State University
Email: zotov.sa@mipt.ru
Rússia, Moscow
S. Donskoy
Roslesinforg
Email: zotov.sa@mipt.ru
Rússia, Moscow