Труды сотрудников ИВМ СО РАН

/ T. N. Ivanilova // Annual Review in Automatic Programming. - 1985. - Vol. 12, Is. PART 2. - P185-188 . - ISSN 0066-4138
Аннотация: Average measure simulation of forest fire spread is one of the applications of set probability theory. Probability spread calculations are carried out using set identification methods of a model of random spread, taking into account initial data of fire condition in a present moment of time we get prognosis - average measure fire contour - in any post coming moment of time. В© 1985.

Scopus

Держатели документа:
Computer Center, SB AS USSR, Krasnoyarsk, 660036, USSR
ИВМ СО РАН

Доп.точки доступа:
Ivanilova, T.N.

[Text] / O. Y. Vorobev // FIRE IN ECOSYSTEMS OF BOREAL EURASIA. Ser. FORESTRY SCIENCES : KLUWER ACADEMIC PUBL, 1996. - Vol. 48: International Scientific Conference on Fire in Ecosystems of Boreal Eurasia (JUN-JUL -, 1993, KRASNOYARSK, RUSSIA). - P271-276. - Cited References: 0 . - ISBN 0-7923-4137-6РУБ Ecology + Forestry


WOS

Держатели документа:
RUSSIAN ACAD SCI,CTR COMP,SIBERIAN BRANCH,KRASNOYARSK 660036,RUSSIA
ИВМ СО РАН
Доп.точки доступа:
Vorobev, O.Y.; Воробьев, Олег Юрьевич

/ I. V. Zenkov, I. M. Baradulin // Gorn. Zh. - 2016. - Vol. 2016, Is. 3. - С. 85-88, DOI 10.17580/gzh.2016.03.18 . - ISSN 0017-2278
Аннотация: Slow-rate development of mineral resources in Siberia is connected with remoteness of mineral fields and deficiency in hard-surface roads. The approval of the government transport system program in Siberia requires boosting road metal production and quarrying expansion. Mined-out voids of depleted quarries disturb lands and remain bare for a long time. The situation in the Krasnoyarsk Territory is of particular concern. It is urgently required to find planting methods for mined-out ballast quarries. The obstacle is the traditional geometry of mined-out open pits, with steep walls and vast bottom flooded with atmospheric precipitations. Ecological monitoring of mined-out surface mines in the Krasnoyarsk Territory and most effective vegetation of mined-out voids shows that, given the local climate (long cold winter and short hot summer), population of trees is higher on the southern and eastern pit walls, where moisture content is higher and trees are less dehumidified under the sun in simmer; of no less significance is flatness of slopes and weak inclination (3-5°) of roads towards pit walls, as well as presence of fertile soil layer in the walls. On special purpose plots of land 0.2 ha in area, trees have been counted per each element of a quarry, which makes the basis to develop recommendations on environmentally optimal shape of quarries: maximum area of the southern and eastern pitwalls to be slightly sloping (15-24°), minimum technologically reasoned area of bottom is shifted northwestward. The study is in accordance with the Fundamental Research Program of the National Academies of Sciences for 2013-2020 and the research plan of the Nauka Design and Engineering Center, ICT SB RAS for 2013-2017, under the project "Information Support Models and Technologies for Evaluation, Forecasting and Management of Regional Eco-Systems, Territorial Infrastructure and Natural and Industrial Safety".

Scopus,
Смотреть статью

Держатели документа:
Institute of Computational Technologies, Siberian Branch, Russian Academy of Sciences, Krasnoyarsk, Russian Federation
Siberian Federal University, Krasnoyarsk, Russian Federation
Nauka Design and Engineering Center, Krasnoyarsk Division

Доп.точки доступа:
Zenkov, I. V.; Baradulin, I. M.

/ A. V. Lapko, V. A. Lapko // Optoelectron. Instrum. Data Proces. - 2018. - Vol. 54, Is. 5. - P451-456, DOI 10.3103/S8756699018050047 . - ISSN 8756-6990
Аннотация: Modifications of a nonparametric pattern recognition algorithm corresponding to the maximum likelihood criterion with additional decision functions are considered. The synthesis of the proposed algorithms is based on the analysis of the ratios of the estimates of the probability density distributions of random variables in classes and their functionals with input thresholds. The choice of the thresholds is determined by specific features of the classification problem. The results obtained are applied for assessing the states of forest tracts on the basis of remote sensing data. © 2018, Allerton Press, Inc.

Scopus,
Смотреть статью

Держатели документа:
Institute of Computational Modeling, Siberian Branch, Russian Academy of Sciences, Academgorodok-50, 44, Krasnoyarsk, 660036, Russian Federation
Reshetnev Siberian State University of Science and Technology, pr. Krasnoyarskii rabochii 31, Krasnoyarsk, 660037, Russian Federation

Доп.точки доступа:
Lapko, A. V.; Lapko, V. A.

/ A. V. Lapko, V. A. Lapko // Comput. Opt. - 2019. - Vol. 43, Is. 2. - С. 238-244, DOI 10.18287/2412-6179-2019-43-2-238-244. - Cited References:21 . - ISSN 0134-2452. - ISSN 2412-6179РУБ Optics

Аннотация: The paper deals with a new method of testing hypotheses for the distribution of multidimensional remote sensing spectral data. The proposed technique is based on the use of nonparametric algorithms for pattern recognition. Testing the hypothesis of the identity of two laws of distributions of multidimensional random variables is replaced by testing a hypothesis stating that the pattern recognition error equals 0.5. The application of this technique allows doing without the decomposition of the random variable domain into multidimensional intervals, which is typical for the Pearson criterion. Its effectiveness is confirmed by the results of testing the hypotheses of the distribution of spectral data of remote sensing in forestry. The analysis of the distribution laws for the following types of forestry is carried out: dark coniferous forest, damaged and dry forest stands. The initial information was obtained from the southern Siberia remote sensing data using six spectral channels of Landsat. The results of the research form a basis for a set of significant spectral features when dealing with forest condition monitoring.

WOS,
Смотреть статью,
Scopus,
РИНЦ

Держатели документа:
Russian Acad Sci, Siberian Branch, Inst Computat Modeling, Krasnoyarsk, Russia.
Reshetnev Siberian State Univ Sci & Technol, Space Facil & Technol Dept, Krasnoyarsk, Russia.

Доп.точки доступа:
Lapko, A. V.; Lapko, V. A.

/ A. A. Kadochnikov // Geod. Kartogr. - 2019. - Vol. 80, Is. 1. - С. 110-118, DOI 10.22389/0016-7126-2019-943-1-110-118 . - ISSN 0016-7126
Аннотация: Today, remote sensing data are an important source of operational information about the environment for thematic GIS, this data can be used for the development of water, forestry and agriculture management, in the ecology and nature management, with territorial planning, etc. To solve the problem of ensuring the effective use of the space activities 'results in the Krasnoyarsk Territory a United Regional Remote Sensing Center was created. On the basis of the Center, a new satellite receiving complex of FRC KSC SB RAS was put into operation. It is currently receiving satellite data from TERRA, AQUA, Suomi NPP and FENG-YUN satellites. Within the framework in cooperation with the Siberian Regional Center for Remote Sensing the Earth, an archive of satellite data from domestic Resource-P and Meteor-M2 satellites was created. The work considers some features of softwaredevelopment and technological support tools for loading, processing and publishing remote sensing data. The product is created in the service-oriented paradigm based on geoportal technologies and interactive web-cartography The focus in this article is paid to the peculiarities of implementing the software components of the web GIS, the efficient processing and presentation ofgeospatial data. © 2019 Center of Geodesy, Cartography and SDI, FSBI. All rights reserved.

Scopus,
Смотреть статью,
РИНЦ

Держатели документа:
Institute of Computational Modelling, Siberian Branch, Russian Academy of Sciences, Building 44, Akademgorodok, 50, Krasnoyarsk, 660036, Russian Federation

Доп.точки доступа:
Kadochnikov, A. A.

/ A. V. Dergunov, 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/537/6/062084 . -
Аннотация: Siberian silk moth is one of the most dangerous pests of coniferous forests of Krasnoyarsk region, which are the most important natural resource of the region. Climate change is considered to be one of the essential criteria for the growth of the silk moth population. In 2014, there was another outbreak of the number of silk moth in the Yenisei district of Krasnoyarsk region. It is known that the forest area of the Yenisei river left bank is subject to severe damage by the silk moth, and the right bank is characterized by a weak forest damage. The task of this work is to analyze the situation with the heterogeneous lesion of the forest by the Siberian silkworm on both banks of the Yenisei river of the territory under consideration according to most detailed available meteorological data for the period from 2009 to 2018. The results of the study showed that the left bank of the river has an increased surface temperature compared to the right bank by an average of 1-1.5C during the period under review. This effect may be the reason for the spatial distribution of the Siberian silk moth population. © 2019 IOP Publishing Ltd. All rights reserved.

Scopus,
Смотреть статью

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:
Dergunov, A. V.; Yakubailik, O. E.

/ 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.

Scopus,
Смотреть статью,
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.

/ M. Saltykov, O. Yakubailik, S. Bartsev // 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/537/6/062001 . -
Аннотация: The applicability of artificial neural networks (ANN) for the identification of vegetation types using satellite multispectral imagery was studied. The study was focused on the three main vegetation types found in the south of the Krasnoyarsk Region: mixed forest, boreal forest and grassland. Sentinel-2 satellite images were used as a data source for the neural networks. It was shown that vegetation type can be identified pixel-by-pixel using 12 spectral channels and simple feed forward ANN with good quality and reliability. Analysis of the input layer of the trained neural networks allowed several spectral bands to be selected that were the most valuable for the ANN decision and not used in the classic NDVI vegetation index. © 2019 IOP Publishing Ltd. All rights reserved.

Scopus,
Смотреть статью

Держатели документа:
Institute of Biophysics, FRC KSC SB RAS, Akademgorodok 50/50, Krasnoyarsk, 660036, Russian Federation
Institute of Computation Modeling, FRC KSC SB RAS, Akademgorodok 50/44, Krasnoyarsk, 660036, Russian Federation

Доп.точки доступа:
Saltykov, M.; Yakubailik, O.; Bartsev, S.

/ A. V. Dergunov [et al.] // International Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM : International Multidisciplinary Scientific Geoconference, 2019. - Vol. 19: 19th International Multidisciplinary Scientific Geoconference, SGEM 2019 (30 June 2019 through 6 July 2019, ) Conference code: 150486, Is. 2.2. - P517-524, DOI 10.5593/sgem2019/2.2/S10.063 . -
Аннотация: Response to anthropogenic disturbances, recorded according to remote sensing of the Earth, has a long-term manifestation not only in the spectral characteristics of the channels of visible and near infrared ranges of satellite imagery, but also in the study of the temperature field. The paper deals with the local excess temperature of the underlying surface in the areas of cutting the territory of the Angara region, compared with the background values identified by satellite data Landsat 5 and 8 for the seventeen-year period. Estimates of the relative difference in the temperature of the underlying surface of the cutting area in comparison with the average background values are obtained. To this end, a number of software products to automate the archiving and conversion of satellite information has been developed. These software products are designed for calculation of the radio-brightness temperature of the underlying surface of disturbed and undisturbed areas of forest vegetation in the pre-selected areas of the territory. They are also used to average the obtained data of radio-brightness temperature and to calculate the difference between the average values of the radio-brightness temperature of the underlying surface of the disturbed areas relative to the undisturbed, that is, the background. This approach can significantly reduce the processing time of a large amount of information and optimize the amount of data storage. Separately, the study area was analyzed according to the NDVI vegetation index. The data obtained demonstrate a high rate of recovery of grass cover and grass-shrub layer immediately after damage to forest vegetation. It is shown that during the considered period of time (17 years) the value of excess temperature decreases, which is determined by the processes of vegetation restoration, including stand on felling. It is established that the increased temperatures of the underlying surface in the place of cuttings are remained for at least 15 years, and the temperature increase over the background values in the conditions of the observed successional processes is not less than 10%. As a limiting factor in the restoration of the temperature background of the underlying surface, fires can act. © SGEM2019. All Rights Reserved.

Scopus,
Смотреть статью

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

Доп.точки доступа:
Dergunov, A. V.; Krasnoshchokov, K. V.; Ponomarev, E. I.; Yakubailik, O. E.

/ A. V. Dergunov, 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. - P349-353 . -
Аннотация: Siberian silkworm is one of the main pests of coniferous forests. In 2014, there was an outbreak of its number in the Yeniseisk district of the Krasnoyarsk Territory. The forest of the left bank of the Yenisei River, unlike the right bank, suffers more from its impact. The purpose of the work is to analyze the heterogeneous forest damage by the silkworm on both banks of the Yenisei River according to meteorological data from 2009 to 2018. The results showed that the left bank is warmer than the right bank by an average of 1-1.5 ° C during the period under consideration. Also recorded a significant decrease in rainfall in 2012. Copyright © 2019 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

Scopus

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:
Dergunov, A. V.; Yakubailik, O. E.