Труды сотрудников ИВМ СО РАН

/ A. Shevyrnogov, G. Vysotskaya, E. Shevyrnogov // Advances in Space Research. - 2004. - Vol. 33, Is. 7. - P. 1179-1183, DOI 10.1016/S0273-1177(03)00369-7 . - ISSN 0273-1177
Аннотация: The work presents the data on the spatial distribution of temperature anomalies in the Global Ocean, based on the long-term measurements with the AVHRR satellite equipment. It is noteworthy that such results can be only obtained by using long time series of satellite images. To obtain them by ship-borne methods is actually impossible. The proposed anomaly criterion is equal to a difference between minimum/maximum and average temperature, normed for the mean square deviation. The difference is calculated from the whole time series (with regard to a season). Based on this criterion, anomalies can be distinguished on the background of usual seasonal dynamics at various absolute values of deviations of the measured parameter. Besides, rare, single, fluctuations can be also revealed. Based on the proposed criterion, connected zones have been defined. These zones occur almost in every part of the Global Ocean. The data obtained have been analyzed in association with the CZCS (1978-1986) and SeaWiFS satellite images in order to compare them with the areas of anomalous dynamics of chlorophyll concentration and the regions quasistationary in the seasonal dynamics of chlorophyll. Anomalies in the temperature dynamics are of exceptional importance for the formation of climatic deviations; they affect the ocean-atmosphere interaction and reflect variations in the hydrological structure of the surface waters. The work presents a comparison with the dynamics of chlorophyll concentration distribution determined from the SeaWiFS data for the Atlantic Ocean. В© 2003 COSPAR. Published by Elsevier Ltd. All rights reserved.

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Shevyrnogov, A.; Vysotskaya, G.; Высоцкая, Галина Степановна; Shevyrnogov, E.

/ A. Shevyrnogov [et al.] // Advances in Space Research. - 2000. - Vol. 26, Is. 7. - P. 1169-1172, DOI 10.1016/S0273-1177(99)01142-4 . - ISSN 0273-1177
Аннотация: Deep insight into types of vegetation variability provided by AVHRR space scanner images of vegetation index spatial distribution helps reveal impact of land surface changes on environment. The Institute of Computational Modeling SB RAS has developed nonparametric algorithms of automatic to classify and recognize patterns of these images which helped to reveal: (1) major variability types (generally connected); (2) areas belonging to small classes, which can be used to reveal deviations from 'normal' (e.g., forest fires, etc.); (3) deviation from a certain type of dynamics indicative of changes in condition of plants, which can be used to diagnose pathology at early stages; (4) impact of economical activities on vegetation in Norilsk area. The authors provide biological interpretation of the satellite data. Computer-animated dynamics and color maps are presented. Nonparametric algorithms of an automatic classification and pattern recognition were provided by the Institute of Computational Modeling SB RAS. (C) 2000 COSPAR. Published by Elsevier Science Ltd.

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Shevyrnogov, A.; Vysotskaya, G.; Высоцкая, Галина Степановна; Sidko, A.; Dunaev, K.

/ A. P. Shevyrnogov, M. Y. Chernetskiy, G. S. Vysotskaya // Izv. Atmos. Ocean Phys. - 2013. - Vol. 49, Is. 9. - P. 1047-1056, DOI 10.1134/S0001433813090132 . - ISSN 0001-4338
Аннотация: It is found that the nonlinear positive Normalized Difference Vegetation Index (NDVI) trend of mountain taiga in the south of Krasnoyarsk Krai has been negative since 1999-2000. A comparison with the boreal belt of northern Eurasia showed that, though still nonnegative, the positive trend has distinctly decreased to nearly a plateau. A trend analysis of radiation temperature of the surface revealed that the temperature shows a decreasing trend for the selected region of mountainous taiga and an increasing trend for northern Eurasia. We compared air-temperature data from the Yermakovskoe meteorological station to eliminate a preliminary data-processing error. Regression analysis demonstrated a fairly high degree of correlation. Also, we found a quite high degree of correlation between time series and trends of air temperature and NDVI. Trends in air temperature in northern Eurasia according to NCEP-DOE Reanalysis 2 data also confirm the trend found on the basis of satellite data. © 2013 Pleiades Publishing, Ltd.

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Shevyrnogov, A.P.; Chernetskiy, M.Y.; Vysotskaya, G.S.; Высоцкая, Галина Степановна

[Text] / M. Chernetskiy [et al.] // Adv. Space Res. - 2009. - Vol. 43, Is. 2. - P. 206-213, DOI 10.1016/j.asr.2008.04.002. - Cited References: 24 . - ISSN 0273-1177РУБ Astronomy & Astrophysics + Geosciences, Multidisciplinary + Meteorology & Atmospheric Sciences

Аннотация: In this work historical investigations and modern results of classification of the Krasnoyarsk Reservoir are presented. The paper presents results of studying the dynamics of phytopigments and other optically active components, using multispectral satellite data. Several approaches to interpreting satellite data for optically complex inland water bodies are offered. Based on results of historical investigations it is shown that the spatial distribution of phytoplankton in the reservoir stems back to the time of its formation. Color index in the red spectral region (CIR) is introduced. A relationship between the color index and chlorophyll concentration is investigated. The CIR, derived from the AVHRR data, has been found to be related to chlorophyll concentration. Based on MODIS data, the waters of the Krasnoyarsk Reservoir have been classified in accordance with their optical spectral variability, using the technique of unsupervised Iso-Data classification. An empirical relationship between multispectral MODIS data and the ground-truth measurements of chlorophyll concentration has been found. (C) 2008 COSPAR. Published by Elsevier Ltd. All rights reserved.


Доп.точки доступа:
Chernetskiy, M.; Shevyrnogov, A.; Shevnina, S.; Vysotskaya, G.; Высоцкая, Галина Степановна; Sidko, A.