Труды сотрудников ИВМ СО РАН

/ 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.

[Текст] : статья / З. З. Ружичка [и др.] // Информационные технологии. - 2017. - Т. 23, № 7. - С. 529-535 . - ISSN 1684-6400
   Перевод заглавия: Information Technological Support of Tasks of Processing and Submission of Radiometric Satellite Data

УДК	004.4, 528.8

Аннотация: Рассматриваются проблемы и методы, программные средства для обработки и представления радиометрических спутниковых данных SMOS, GCOM-W1, MODIS, используемых в исследованиях различных характеристик почвы (влажность, температура). Создана база геопространственных данных, программы и прикладные сервисы для различных операций над ними. Разработанный комплекс программ обеспечивает решение всех необходимых задач автоматизации научных исследований.
These data are used in studies of different soil characteristics, such as soil moisture and temperature. The main attention is paid to SMOS satellite data and the discussion different characteristics of the software to handle them. Article presents a list of existing software toolboxes for various operations on these data. A database of geospatial data along with software and applied services for a variety of operations on them have been created. Efficient data storage structure that provides a significant increase in computational performance for a number of tasks has been proposed. A number of software functions have been implemented for downloading, storing and processing of geospatial radiometric data. The developed system provides setting of various parameters through configuration files, which simplify common user tasks, such as granting access rights for database connection, selection and visualization of information from geospatial database, conversion and export data to third party formats. Using of open international mapping standards of Open Geospatial Consortium (OGC) for geospatial data greatly simplifies access to information on the topic, expanding the audience of potential users. The software tools developed can be used for solving different problems arising in scientific investigations. It is widely used in everyday research in the Laboratory of Radiophysics of the Remote Sensing, Kirensky Institute of Physics, Siberian Branch of Russian Academy of Sciences.

РИНЦ

Держатели документа:
Институт вычислительного моделирования СО РАН, ФИЦ КНЦ СО РАН
Институт леса им. В. Н. Сукачева СО РАН, ФИЦ КНЦ СО РАН
Институт физики им. Л. В. Киренского СО РАН, ФИЦ КНЦ СО РАН
Сибирский государственный аэрокосмический университет имени академика М. Ф. Решетнева

Доп.точки доступа:
Ружичка, З.З.; Ruzicka Z.Z.; Музалевский, К.В.; Muzalevskiy K.V.; Якубайлик, О.Э.; Yakubailik O.E.; Швецов, Е.Г.; Shvetsov E.G.

[Текст] : доклад, тезисы доклада / Ю. Д. Иванова [и др.] // Сложные системы в экстремальных условиях : материалы XIX Всероссийского симпозиума с международным участием. - Красноярск, 2018. - С. 91-93 . - ISBN 978-5-6041286-8-8

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Источник статьи

Держатели документа:
Институт биофизики СО РАН ФИЦ КНЦ СО РАН
Институт вычислительного моделирования ФИЦ КНЦ СО РАН
Институт леса СО РАН ФИЦ КНЦ СО РАН
Федеральный исследовательский центр «Красноярский научный центр?Сибирского отделения Российской академии наук»

Доп.точки доступа:
Иванова, Юлия Дмитриевна; Ivanova Yu.D.; Ковалев, Антон Владимирович; Kovalev A.V.; Суховольский, Владислав Григорьевич; Sukhovolsky V.G.; Якубайлик, Олег Эдуардович; Yakubailik O.E.; Сложные системы в экстремальных условиях(2018 ; 20.08 - 23.08 ; Красноярск)
Нет сведений об экземплярах (Источник в БД не найден)

/ Y. Ivanova [et al.] // Forests. - 2019. - Vol. 10, Is. 7, DOI 10.3390/f10070561 . - ISSN 1999-4907
Аннотация: Vegetation indices derived from remote sensing measurements are commonly used to describe and monitor vegetation. However, the same plant community can have a different NDVI (normalized difference vegetation index) depending on weather conditions, and this complicates classification of plant communities. The present study develops methods of classifying the types of plant communities based on long-term NDVI data (MODIS/Aqua). The number of variables is reduced by introducing two integrated parameters of the NDVI seasonal series, facilitating classification of the meadow, steppe, and forest plant communities in Siberia using linear discriminant analysis. The quality of classification conducted by using the markers characterizing NDVI dynamics during 2003-2017 varies between 94% (forest and steppe) and 68% (meadow and forest). In addition to determining phenological markers, canonical correlations have been calculated between the time series of the proposed markers and the time series of monthly average air temperatures. Based on this, each pixel with a definite plant composition can be characterized by only four values of canonical correlation coefficients over the entire period analyzed. By using canonical correlations between NDVI and weather parameters and employing linear discriminant analysis, one can obtain a highly accurate classification of the study plant communities. © 2019 by the authors.

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WOS

Держатели документа:
Institute of Biophysics SB RAS, Federal Research Center 'Krasnoyarsk Science Center SB RAS', Academgorodok 50-50, Krasnoyarsk, 660036, Russian Federation
Federal Research Center 'Krasnoyarsk Science Center SB RAS', Academgorodok 50, Krasnoyarsk, 660036, Russian Federation
Institute of Computational Modeling SB RAS, Federal Research Center 'Krasnoyarsk Science Center SB RAS', Academgorodok 50-44, Krasnoyarsk, 660036, Russian Federation
Sukachev Institute of Forest SB RAS, Federal Research Center 'Krasnoyarsk Science Center SB RAS', Academgorodok 50-28, Krasnoyarsk, 660036, Russian Federation

Доп.точки доступа:
Ivanova, Y.; Kovalev, A.; Yakubailik, O.; Soukhovolsky, V.

/ K. V. Krasnoshchekov, O. E. Yakubailik // IOP Conference Series: Materials Science and Engineering : Institute of Physics Publishing, 2019. - Vol. 537: International Workshop on Advanced Technologies in Material Science, Mechanical and Automation Engineering - MIP: Engineering-2019 (4 April 2019 through 6 April 2019, ) Conference code: 149243, Is. 6, DOI 10.1088/1757-899X/537/6/062083 . -
Аннотация: Spectrometer MODIS, installed on TERRA and AQUA satellites, provides daily global coverage of the Earth. Based on its measurements, data on aerosol optical depth (AOD) with different spatial resolution are formed: 10, 3, 1 km. The classical algorithm with a coarse spatial resolution of 10 km is not suitable for studying the variability of aerosols at the city scale. Introduced in 2018, a new algorithm for multi-angle implementation of atmospheric correction (MAIAC) provides AOD data with spatial resolution of 1 km. This information can already be used to analyze the spatial distribution of aerosols in the city. The relationship between MAIAC AOD and PM2.5 concentrations of particulate matter was investigated, which is measured at automated posts of city environmental services. Our analysis showed that the data with a spatial resolution of 1 km allow us to see the areas of dust pollution inside the city. This information, together with measurements at the posts, can be used as an objective assessment of the environmental situation. © 2019 IOP Publishing Ltd. All rights reserved.

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Держатели документа:
Federal Research Center, Krasnoyarsk Science Center, SB RAS, Krasnoyarsk, Russian Federation
Institute of Computational Modelling, SB RAS, Krasnoyarsk, Russian Federation
Siberian Federal University, Krasnoyarsk, Russian Federation

Доп.точки доступа:
Krasnoshchekov, K. V.; Yakubailik, O. E.

/ K. V. Krasnoshchekov, O. E. Yakubailik // CEUR Workshop Proceedings : CEUR-WS, 2019. - Vol. 2534: 2019 All-Russian Conference ""Spatial Data Processing for Monitoring of Natural and Anthropogenic Processes"", SDM 2019 (26 August 2019 through 30 August 2019, ) Conference code: 156641. - P288-292 . -
Аннотация: Based on its measurements of the MODIS spectrometer installed on the TERRA and AQUA satellites, data on aerosol optical depth (AOD) with different spatial resolution are formed: 10, 3, 1 km. The relationship between AOT values measured using remote sensing and PM2.5 measured at automated observation posts (APS) was investigated. It is shown that the data with a spatial resolution of 1 km make it possible to see dusty zones inside the city. Aerosol Index was used to take into account the contribution of external factors, such as smoke from fires, to the ecological situation of the city. This information can be used as an objective assessment of the environmental situation. Copyright © 2019 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

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Держатели документа:
Federal Research Center Krasnoyarsk Science Center of the SB RAS, Krasnoyarsk, Russian Federation
Institute of Computational Modelling SB RAS, Krasnoyarsk, Russian Federation
Siberian Federal University, Krasnoyarsk, Russian Federation

Доп.точки доступа:
Krasnoshchekov, K. V.; Yakubailik, O. E.