Труды сотрудников ИЛ им. В.Н. Сукачева СО РАН

[Текст] = Software for optimizing fire management objects disposition in the forest management area : материалы временных коллективов / К. С. Першин // Исследование компонентов лесных экосистем Сибири: Материалы конференции молодых ученых, 5-6 апреля 2012 г. , Красноярск. - Красноярск : Институт леса им. В.Н. Сукачева СО РАН , 2012. - Вып.13. - С. 30-32. - Библиогр.: 4 назв.
Аннотация: This paper presents software developed for optimizing fire management objects distribution in the forest area. New programs based on expert data allow determining the best object location from the suggested ones.

Держатели документа:
Институт леса им. В.Н. Сукачева Сибирского отделения Российской академии наук : 660036, Красноярск, Академгородок, 50/28

Доп.точки доступа:
Pershin K.S.

/ M. Korets, A. Onuchin // IAHS-AISH Publication. - 2009. - Vol. 331: Symposium JS.4 at the Joint Convention of the International Association of Hydrological Sciences, IAHS and the International Association of Hydrogeologists, IAH (6 September 2009 through 12 September 2009, Hyderabad) Conference code: 83573. - P510-513 . -
Аннотация: Forest areas can intercept surface runoff from upslope bare areas and transfer it to interflow. Therefore, planting protective forests along the banks of rivers, reservoirs, and lakes preserves natural water sources from pollution. Depending on the particular landscape conditions, the streamside forest shelterbelt (SFS) width is often either wider or narrower than the ecologically substantiated width. As a result, either water quality worsens or the ecologically unjustified prohibition of forest use leads to economic losses. The assessment of SFS width using GIS technologies allows considerable simplification of evaluation procedures and their application in practice. DEM processing is integrated into most modern GIS software packages. For example, the popular ESRI ArcGIS package with its Spatial Analyst module provides extra options for calculating a series of relief-based hydrological features, which include calculation procedures for surface flow direction, length of flow-producing slopes and surface flow accumulations. Two algorithms for GIS-based SFS construction were tested for several rivers of the Yenisei basin and Krasnoyarsk Reservoir, Siberia. The first algorithm is technically simple and based on empirical equations of runoff slope length, slope steepness and soil infiltration. The second one includes a three-dimensional flow accumulation procedure and thus it is more sensitive to real surface structure. Both algorithms are ready to be used in practice. The results obtained indicate that, on average, the SFS width along banks of large rivers might be reduced, while in some cases it should be widened along the banks of small streams. Copyright В© 2009 IAHS Press.

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Держатели документа:
V. N. Sukachev Institute of Forest, Siberian Branch, Russian Academy of Sciences, 50/28, Akademgorodok, 660036, Krasnoyarsk, Russian Federation

Доп.точки доступа:
Korets, M.; Onuchin, A.

[Text] / S. Im // INFORMATICS, GEOINFORMATICS AND REMOTE SENSING, VOL I (SGEM 2015) : STEF92 TECHNOLOGY LTD, 2015. - 15th International Multidisciplinary Scientific Geoconference (SGEM) (JUN 18-24, 2015, Albena, BULGARIA). - P433-440. - (International Multidisciplinary Scientific GeoConference-SGEM). - Cited References:13 . - РУБ Computer Science, Interdisciplinary Applications + Geosciences,

Аннотация: The goal of this research was to develop a cost-effective technique to analyze spatio-temporal dynamics of darkneedle stands desiccation. The developed technique allows estimating of spatio-temporal dynamics of darkneedle stands desiccation based on remote sensing data from Landsat satellites regarding orography and climate trends. Advantages of the technique are (1) using of freely available Landsat data, digital elevation model and climate data; and (2) it is based on the maximum likelihood supervised classification method realized in the most of software products. There are six main steps in the technique: (1) preliminary data preparation and analysis; (2) generation of classification map of darkneedle stands for the period prior to decline of trees; (3) masking of time series of Landsat data based on the classification map of darkneedle stands for the period prior to decline of trees; (4) generation of classification maps of desiccated stands; (5) GIS-analysis of relationships between spatio-temporal dynamics of desiccation of trees and orography; (6) statistical analysis of relationships between spatio-temporal dynamics of desiccation of trees and climate trends. The technique was successfully tested at two sites located in Siberia. Forest decline occurred after consecutive droughts during the last decades. Mortality began at hilltops and steep south-facing slopes, shifting with time to lower elevations. Maximum of the desiccated forest area was within steep (18 degrees-25 degrees) south-facing slopes.

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Держатели документа:
VN Sukachev Inst Forest SB RAS, Krasnoyarsk, Russia.
MF Reshetnev Siberian State Aerosp Univ, Krasnoyarsk, Russia.
Siberian Fed Univ, Krasnoyarsk, Russia.

Доп.точки доступа:
Im, Sergei

/ S. Im // INFORMATICS, GEOINFORMATICS AND REMOTE SENSING CONFERENCE PROCEEDINGS, : STEF92 TECHNOLOGY LTD, 2016. - 16th International Multidisciplinary Scientific Geoconference (SGEM (JUN 30-JUL 06, 2016, Albena, BULGARIA). - P859-866. - (International Multidisciplinary Scientific GeoConference-SGEM). - Cited References:8. - This research was partly supported by the Ministry of Education and Science of the Russian Federation (grant no. 2.914.2014/K) and the Russian Science Foundation (grant no. 14-24-00112). . - РУБ Geosciences, Multidisciplinary

Аннотация: Nowadays, an accuracy of digital elevation models (DEM) is increasing and it can be used to investigate relationships between land-cover dynamics and orography. Relief elements, such as slopes, aspects, and curvature can be easily calculated using GIS-tools. However, it is known that existing DEMs have errors. Some investigators assessed accuracy of the existing high-resolution DEMs obtained by remote sensing techniques. In addition, it is crucial to know an accuracy of the calculated relief features (slope, aspect, and curvature) for proper interpretation of results, for example, vegetation distribution relative to azimuthal directions of slopes. In this research, equations to estimate errors for terrain features extracted from DEM were determined based on the equations realized in Erdas Imagine and ESRI ArcGIS software, and using error assessment theory. Equations to estimate root mean square error (RMSE) were realized using Erdas Imagine modeler. The analysis of SRTM DEM showed that RMSE of aspects depends on the average changes in elevation by x and y directions and relative elevation error of DEM. RMSE of aspects decreases with increasing of the average changes in elevation by x and y directions. RMSE for aspects was less than 13 degrees for 90% of the area within test site. RMSE of slopes depends on spatial resolution and relative elevation error of DEM, and the average changes in elevation by x and y directions. With increasing of slope steepness, its RMSE decreases. RMSE for slope was less than 4.5 for 90% of the area within test site.

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Держатели документа:
VN Sukachev Inst Forest SB RAS, Krasnoyarsk, Russia.
Siberian Fed Univ, Krasnoyarsk, Russia.
MF Reshetnev Siberian State Aerosp Univ, Krasnoyarsk, Russia.

Доп.точки доступа:
Im, Sergei; Ministry of Education and Science of the Russian Federation [2.914.2014/K]; Russian Science Foundation [14-24-00112]

/ 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.

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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
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.

/ P. Dyachuk, A. Arzac, P. Peresunko [et al.] // Dendrochronologia. - 2020. - Vol. 60. - Ст. 125687, DOI 10.1016/j.dendro.2020.125687 . - ISSN 1125-7865
Аннотация: Quantitative wood anatomy (QWA) is a growing field of dendrochronology that allows obtaining a large number of parameters as the number, size and spatial arrangement of cellular elements, elements that highlight the adjustments of trees to their environment. In this work, we presented the free/libre open-source software AutoCellRow (ACR), a ready-to-use tool for automatic QWA in conifers. The ACR analyzes radial files of cells on cross-sections views of tree rings and provides automatic measurements of different cell parameters (e.g., lumen radial diameter, double cell wall thickness and cell radial diameter) for each cell along the selected radial file. The ACR measurements are based on high performed image analysis of xylem cells. The accuracy of the software measurements was tested in cross-sections of five conifer species from a semi-arid area of southern Siberia, and compared with measurements obtained by a semiautomatic tool. Our results suggested high accuracy in the ACR cell traits measurements, facilitating and speeding the analysis of quantitative wood anatomy in conifers over radial files of cells. © 2020 Elsevier GmbH

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Держатели документа:
Siberian Federal University, 79 Svobodny pr, Krasnoyarsk, 660041, Russian Federation
V. N. Sukachev Institute of Forest, Siberian Branch of the Russian Academy of Sciences, Krasnoyarsk, Russian Federation
Khakass Technical Institute, Siberian Federal University, 27 Shchetinkina St, Abakan, 655017, Russian Federation
Le Studium Loire Valley Institute for Advanced Studies, Orleans, France

Доп.точки доступа:
Dyachuk, P.; Arzac, A.; Peresunko, P.; Videnin, S.; Ilyin, V.; Assaulianov, R.; Babushkina, E. A.; Zhirnova, D.; Belokopytova, L.; Vaganov, E. A.; Shishov, V. V.

/ P. Dyachuk, A. Arzac, P. Peresunko [et al.] // Dendrochronologia. - 2020. - Vol. 60. - Ст. 125687, DOI 10.1016/j.dendro.2020.125687. - Cited References:22. - This work was carried out on the basis of the Laboratory for integral studies of forest dynamics of Eurasia"of the Siberian Federal University [FSRZ-2020-0014], with financial support from the Ministry of Education and Science of the Russian Federation [Project 5.3508.2017/4.6, software development] and the Russian Science Foundation [Grant18-74-10048, software testing and upgrade, experiment design and paper writing]. VS appreciates the support of the Russian Science Foundation [Grant 18-14-00072, data analysis] and LE STUDIUM/Marie Skladowska-Curie Research Fellowship. . - ISSN 1125-7865. - ISSN 1612-0051РУБ Forestry + Geography, Physical

Аннотация: Quantitative wood anatomy (QWA) is a growing field of dendrochronology that allows obtaining a large number of parameters as the number, size and spatial arrangement of cellular elements, elements that highlight the adjustments of trees to their environment. In this work, we presented the free/libre open-source software AutoCellRow (ACR), a ready-to-use tool for automatic QWA in conifers. The ACR analyzes radial files of cells on cross-sections views of tree rings and provides automatic measurements of different cell parameters (e.g., lumen radial diameter, double cell wall thickness and cell radial diameter) for each cell along the selected radial file. The ACR measurements are based on high performed image analysis of xylem cells. The accuracy of the software measurements was tested in cross-sections of five conifer species from a semi-arid area of southern Siberia, and compared with measurements obtained by a semiautomatic tool. Our results suggested high accuracy in the ACR cell traits measurements, facilitating and speeding the analysis of quantitative wood anatomy in conifers over radial files of cells.

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Держатели документа:
Siberian Fed Univ, 79 Svobodny Pr, Krasnoyarsk 660041, Russia.
Russian Acad Sci, Siberian Branch, VN Sukachev Inst Forest, Krasnoyarsk, Russia.
Siberian Fed Univ, Khakass Tech Inst, 27 Shchetinkina St, Abakan 655017, Russia.
Le Studium Loire Valley Inst Adv Studies, Orleans, France.

Доп.точки доступа:
Dyachuk, Petr; Arzac, Alberto; Peresunko, Pavel; Videnin, Sergey; Ilyin, Victor; Assaulianov, Roman; Babushkina, Elena A.; Zhirnova, Dina; Belokopytova, Liliana; Vaganov, Eugene A.; Shishov, Vladimir V.; Ministry of Education and Science of the Russian FederationMinistry of Education and Science, Russian Federation [5.3508.2017/4.6]; Russian Science FoundationRussian Science Foundation (RSF) [18-74-10048, 18-14-00072]; LE STUDIUM/Marie Skladowska-Curie Research Fellowship

/ A. V. Volokitina, T. M. Sofronova, M. A. Korets // Lesnoy Zh. - 2020. - Is. 1. - С. 9-25, DOI 10.37482/0536-1036-2020-1-9-25. - Cited References:64 . - ISSN 0536-1036РУБ Forestry

Аннотация: The necessity for predicting the behavior of vegetation fires, including forest fires, is keenly felt in a time of severe droughts, which periodically recur in this or that area, and their precise prediction is still hampered. It is unfeasible to maintain sufficient forces and means in each region for suppressing all emerging fires. Merely the increase of technical power won't solve the problem, as evidenced by the experience of developed countries, where much attention, along with fire danger rating, has long been given to the development of a fire behavior prediction system. Such system in Russia isn't available yet, and the use of international practices seems to be impossible, since it is complicated by several factors and, above all, different historically developed approaches to the pyrological classification of vegetation and its inventory. Currently, there are all opportunities for creating the Russian system for vegetation fire behavior prediction (including forest fires): fundamental pyrological developments based on the research results of the nature of fires; a fire monitoring system has been created and is being developed; and fire danger (both natural and due to the weather conditions) rating is being improved. The article presents a principle diagram of the vegetation fire behavior prediction and considers its main components. A practical model was chosen for prediction the burning spread rate. The necessary data base for the model is available in the GIS system. Software for creation vegetation fuel (VF) maps and prediction the behavior of surface forest fires, which are up to 97 % of all occurring fires has been developed, retrospectively verified and registered. Examples of the VF maps for the Chunskoye Forest District (Krasnoyarsk Krai) for different periods of the fire season are given. They are created based on the use of forest management information and a type identifier of primary fire carriers (i.e. the first VF group), which is directly shown in the maps. Information on the other groups of VF supporting, delaying burning or not participating in the process of burning spread, is attached to the map in the form of a pyrological description. A list of the data included in the pyrological description is given, as well as the reasons, which hold back on practical application of pyrological developments available in Russia for predicting the behavior of vegetation fires into the forest fire protection service.

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Держатели документа:
RAS, SB, Sukachev Inst Forest, Akademgorodok 50-28, Krasnoyarsk 660036, Russia.
Krasnoyarsk State Pedag Univ, Ul Ady Lebedevoy 89, Krasnoyarsk 660049, Russia.

Доп.точки доступа:
Volokitina, A. V.; Sofronova, T. M.; Korets, M. A.; Korets, Mikhail

/ V. P. Vetrova, A. P. Barchenkov, N. V. Sinelnikova // Vestn. Tomsk. Gos. Univ. Biol. - 2021. - Is. 53. - С. 47-67, DOI 10.17223/19988591/53/3. - Cited References:38 . - ISSN 1998-8591. - ISSN 2311-2077РУБ Biology + Ecology

Аннотация: Geometric morphometric analysis of shape variation in the cone scales of two closely related larch species, Larix dahurica Laws. (=Larix gmelinii (Rupr.) Rupr) and L. cajanderi Mayr, was carried out. The data on the taxonomy and distribution of L. dahurica and L. cajanderi are contradictory. The taxonomic status of L. cajanderi has been confirmed by the genetic and morphological studies performed in Russia and based on considerable evidence, but the species has not been recognized internationally, being considered as a synonym of Larix gmelinii var. gmelinii. In the systematics of larch, morphological characters of the generative organs are mainly used as diagnostic markers, among the most important being the shape variation of the cone scales. The aim of this study was to test geometric morphometrics as a tool for analyzing differentiation of L. dahurica and L. cajanderi in the shape of their cone scales. Characterization of shape variations in cone scales using geometric morphometric methods consists in digitizing points along an outline of scales followed by analysis of partial warps, describing individual differences in coordinates of the outline points. We studied the populations of L. dahurica from Evenkia and the Trans-Baikal region and six L. cajanderi populations from Yakutia and Magadan Oblast. In each population, we analyzed samples of 100-150 cones collected from 20-30 trees. Scales taken from the middle part of the cones were scanned using an Epson Perfection V500 Photo. On the scanned images, outline points were placed with a TPSDig program (Rolf, 2010), using angular algorithm (Oreshkova et al., 2015). The data were processed and analyzed using Integrated Morphometrics Programs (IMP) software (http://www.canisius.edu/similar to sheets/morphsoft.html, Sheets, 2001), following the guidelines on geometric morphometrics in biology (Pavlinov, Mikeshina, 2002; Zelditch et al., 2004). Initial coordinates of the scale landmarks were aligned with the mean structure for L. dahurica and L. cajanderi cone scales using Procrustes superimposition in the CoordGen6 program. PCA based on covariances of partial warp scores was applied to reveal directions of variation in the shape of the cone scales. The relative deformations of the cone scales (PCA scores) were used as shape variables for statistical comparisons of these two larch species with canonical discriminant analysis. Morphotypes of the cone scales were distinguished in L. dahurica populations by pairwise comparison of samples from trees in the TwoGroup6h program using Bootstrap resampling-based Goodall's F-test (Sheets, 2001). Samples from the trees in which the cone scales differed significantly (p 0.01) were considered to belong to different morphotypes. Morphotypes distinguished in L. dahurica populations were compared with the morphotypes that we had previously determined in L. cajanderi populations. The composition and the frequency of occurrence of morphotypes were used to determine phenotypic distances between populations (Zhivotovskii, 1991). Multidimensional scaling matrix of the phenotypic distances was applied for ordination of larch populations. In this research, we revealed differentiation of L. dahurica and L. cajanderi using geometric morphometric analysis of the shape variation of cone scales. The results of PCA of partial warp scores exposed four principal components, which account for 90% of total explained variance in the shape of the cone scales in the two larch species. Graphical representations of these shape transformations in the vector form characterized directions of shape variability in scales corresponding to the maximum and minimum values of four principal components (See Fig. 2). PCA-ordination of the larch populations revealed some difference in the shape variation of the cone scales in L. dahurica and L. cajanderi (See Fig. 3). The results of canonical discriminant analysis of relative deformations of scales showed differentiation of the populations of the two larch species (See Fig. 4). Eleven morphotypes were identified in L. dahurica cones from Evenkia and nine morphotypes in the Ingoda population, three of the morphotypes being common for both populations (See Fig. 5). The shape of L. dahurica cone scales varied from spatulate to oval and their apical margins from weakly sinuate to distinctly sinuate. The Trans-Baikal population was dominated by scales with obtuse (truncate) and rounded apexes. The obtained morphotypes were compared with 25 cone scale morphotypes previously distinguished in the Yakut and the Magadan L. cajanderi populations (See Fig. 3). Four similar morphotypes of cone scales were revealed in the North-Yeniseisk population of L. dahurica and the Yakut populations of L. cajanderi. The differences between them in the populations of the two larch species were nonsignificant (p 0.01). All morphotypes of cone scales from the Ingoda population of L. dahurica differed significantly from L. cajanderi cone scale morphotypes. The results of multidimensional scaling phenotypic distance matrix calculated based on the similarity of morphotypes of L. dahurica and L. cajanderi populations were consistent with the results of their differentiation based on relative deformations of scales obtained using canonical discriminant analysis (See Fig. 4 and Fig. 7). In spite of the differences in the shape of the cone scales between the North-Yeniseisk and the Trans-Baikal populations of L. dahurica, they both differed from L. cajanderi populations. Thus, phenotypic analysis confirmed differentiation of these two larch species. Despite the similarities between a number of morphotypes, the Yakut L. cajanderi populations were differentiated from L. dahurica populations. Significant differences were noted between intraspecific groups: between L. cajanderi populations from Okhotsk-Kolyma Upland and Yakutia and between L. dahurica populations from Evenkia and the Trans-Baikal region (See Fig. 4). The similarities between species and intraspecific differences may be attributed to the ongoing processes of hybridization and species formation in the region where the ranges of the larches overlap with the ranges of L. czekanowskii Szafer and L. dahuricax L. cajanderi hybrids. Geometric morphometrics can be used as an effective tool for analyzing differentiation of L. dahurica and L. cajanderi in the shape of their cone scales. The paper contains 7 Figures, 1 Table and 38 References.

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Держатели документа:
Russian Acad Sci, Lab Plant Ecol, Kamchatka Branch Pacific Geog Inst, Far Eastern Branch, 19-A Rybakov Ave, Petropavlovsk Kamchatski 683024, Russia.
Russian Acad Sci, Lab Forest Genet & Breeding, VN Sukachev Inst Forest, Siberian Branch, 50-28 Academgorodok, Krasnoyarsk 660036, Russia.
Siberian Fed Univ, Lab Biogeochem Ecosyst, 79 Svobodny Ave, Krasnoyarsk 660041, Russia.
Russian Acad Sci, Inst Biol Problems North, Lab Bot, Far Eastern Branch, 18 Portovaya Str, Magadan 685000, Russia.

Доп.точки доступа:
Vetrova, Valentina P.; Barchenkov, Alexey P.; Sinelnikova, Nadezhda, V

/ A. Volokitina, A. Kalachev, M. Korets, T. Sofronova // Symmetry. - 2021. - Vol. 13, Is. 4. - Ст. 578, DOI 10.3390/sym13040578 . - ISSN 2073-8994
Аннотация: This paper considers automated fire behavior prediction in larch forests of the Kazakhstan Altai based on large-scale vegetation fuel maps (VF maps). First-time pyrological description of the Kazakhstan Altai larch forests was performed, thus facilitating VF maps’ creation using forest inventory information in a geographical information system (GIS). Based on the methodological developments of the Sukachev Institute of Forest, types of primary fire carriers were identified for larch forests and other categories of sites. On the example of the Markakol Forestry area (Kazakhstan Altai), our fire growth simulation modeling system was adapted for predicting fire behavior in the mountain terrain. The developed fire simulation software helped not only identify inventory plots ready to burn, but also assess spread rate for fire parts dependent upon weather conditions, predict fire intensity and fire development, and calculate the required manpower and resources for fire suppression. The effects of each specific fire were predicted in terms of percentage of tree mortality dependent upon fire intensity, tree species, and average tree diameter. Examples of VF maps were made for different periods of a fire season and analysis was given to behavior of a simulated surface fire in the Markakol Forestry area. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

Scopus

Держатели документа:
V.N. Sukachev Institute of Forest, Russian Academy of Sciences, Siberian Branch, Krasnoyarsk, 660036, Russian Federation
A.N. Bukeykhan Kazakh Scientific Research Institute of Forestry and Agroforestmelioration, Altai Branch, Shchuchinsk, 010000, Kazakhstan
Department of English Philology and Department of Physical Geography, V.P. Astafiev Krasnoyarsk State Pedagogical University, Krasnoyarsk, 660049, Russian Federation

Доп.точки доступа:
Volokitina, A.; Kalachev, A.; Korets, M.; Sofronova, T.

/ A. Volokitina, A. Kalachev, M. Korets, T. Sofronova // Symmetry-Basel. - 2021. - Vol. 13, Is. 4. - Ст. 578, DOI 10.3390/sym13040578. - Cited References:27. - This research was funded within the framework of the Agreement No. 10/1 (dated 25 April 2019) between the A.N. Bukeykhan Kazakh Scientific Research Institute of Forestry and Agroforestmelioration (Republic of Kazakhstan) and the V.N. Sukachev Institute of Forest SB RAS (Russia). Partial financial support was provided by the Russian Foundation for Basic Research (grant No. 18-05-00781A). . - ISSN 2073-8994РУБ Multidisciplinary Sciences

Аннотация: This paper considers automated fire behavior prediction in larch forests of the Kazakhstan Altai based on large-scale vegetation fuel maps (VF maps). First-time pyrological description of the Kazakhstan Altai larch forests was performed, thus facilitating VF maps' creation using forest inventory information in a geographical information system (GIS). Based on the methodological developments of the Sukachev Institute of Forest, types of primary fire carriers were identified for larch forests and other categories of sites. On the example of the Markakol Forestry area (Kazakhstan Altai), our fire growth simulation modeling system was adapted for predicting fire behavior in the mountain terrain. The developed fire simulation software helped not only identify inventory plots ready to burn, but also assess spread rate for fire parts dependent upon weather conditions, predict fire intensity and fire development, and calculate the required manpower and resources for fire suppression. The effects of each specific fire were predicted in terms of percentage of tree mortality dependent upon fire intensity, tree species, and average tree diameter. Examples of VF maps were made for different periods of a fire season and analysis was given to behavior of a simulated surface fire in the Markakol Forestry area.

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Держатели документа:
Russian Acad Sci, VN Sukachev Inst Forest, Siberian Branch, Krasnoyarsk 660036, Russia.
AN Bukeykhan Kazakh Sci Res Inst Forestry & Agrof, Altai Branch, Shchuchinsk 010000, Kazakhstan.
VP Astafiev Krasnoyarsk State Pedag Univ, Dept English Philol, Krasnoyarsk 660049, Russia.
VP Astafiev Krasnoyarsk State Pedag Univ, Dept Phys Geog, Krasnoyarsk 660049, Russia.

Доп.точки доступа:
Volokitina, Aleksandra; Kalachev, Andrey; Korets, Mikhail; Sofronova, Tatiana; A.N. Bukeykhan Kazakh Scientific Research Institute of Forestry and Agroforestmelioration (Republic of Kazakhstan) [10/1]; V.N. Sukachev Institute of Forest SB RAS (Russia); Russian Foundation for Basic ResearchRussian Foundation for Basic Research (RFBR) [18-05-00781A]

/ I. V. Zenkov, A. V. Lapko, V. A. Lapko [и др.] // Comput. Opt. - 2021. - Vol. 45, Is. 2. - С. 253-+, DOI 10.18287/2412-6179-CO-801. - Cited References:13. - The research was funded by RFBR, Krasnoyarsk Territory and Krasnoyarsk Regional Fund of Science, project number 20-41-240001. . - ISSN 0134-2452. - ISSN 2412-6179РУБ Optics

Аннотация: A nonparametric algorithm for automatic classification of large statistical data sets is proposed. The algorithm is based on a procedure for optimal discretization of the range of values of a random variable. A class is a compact group of observations of a random variable corresponding to a unimodal fragment of the probability density. The considered algorithm of automatic classification is based on the "compression" of the initial information based on the decomposition of a multidimensional space of attributes. As a result, a large statistical sample is transformed into a data array composed of the centers of multidimensional sampling intervals and the corresponding frequencies of random variables. To substantiate the optimal discretization procedure, we use the results of a study of the asymptotic properties of a kernel-type regression estimate of the probability density. An optimal number of sampling intervals for the range of values of one- and two-dimensional random variables is determined from the condition of the minimum root-mean square deviation of the regression probability density estimate. The results obtained are generalized to the discretization of the range of values of a multidimensional random variable. The optimal discretization formula contains a component that is characterized by a nonlinear functional of the probability density. An analytical dependence of the detected component on the antikurtosis coefficient of a one-dimensional random variable is established. For independent components of a multidimensional random variable, a methodology is developed for calculating estimates of the optimal number of sampling intervals for random variables and their lengths. On this basis, a nonparametric algorithm for the automatic classification is developed. It is based on a sequential procedure for checking the proximity of the centers of multidimensional sampling intervals and relationships between frequencies of the membership of the random variables from the original sample of these intervals. To further increase the computational efficiency of the proposed automatic classification algorithm, a multithreaded method of its software implementation is used. The practical significance of the developed algorithms is confirmed by the results of their application in processing remote sensing data.

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Держатели документа:
Siberian Fed Univ, Svobodny Av 79, Krasnoyarsk 660041, Russia.
Inst Computat Modelling SB RAS, Akademgorodok 50, Krasnoyarsk 660036, Russia.
Sukachev Inst Forest SB RAS, Akademgorodok 50, Krasnoyarsk 660036, Russia.
Reshetnev Siberian State Univ Sci & Technol, Krasnoyarsky Rabochy Av 31, Krasnoyarsk 660037, Russia.
Fed Res Ctr Informat & Computat Technol, Krasnoyarsk Branch, Mira Av 53, Krasnoyarsk 660049, Russia.

Доп.точки доступа:
Zenkov, I., V; Lapko, A., V; Lapko, V. A.; Im, S. T.; Tuboltsev, V. P.; Avdeenok, V. L.; RFBRRussian Foundation for Basic Research (RFBR); Krasnoyarsk Regional Fund of Science [20-41-240001]; Krasnoyarsk Territory

/ I. V. Zenkov, A. V. Lapko, V. А. Lapko [и др.] // Comput. Opt. - 2021. - Vol. 45, Is. 2. - С. 253-260, DOI 10.18287/2412-6179-CO-801 . - ISSN 0134-2452
Аннотация: A nonparametric algorithm for automatic classification of large statistical data sets is proposed. The algorithm is based on a procedure for optimal discretization of the range of values of a random variable. A class is a compact group of observations of a random variable corresponding to a unimodal fragment of the probability density. The considered algorithm of automatic classification is based on the «compression» of the initial information based on the decomposition of a multidimensional space of attributes. As a result, a large statistical sample is transformed into a data array composed of the centers of multidimensional sampling intervals and the corresponding frequencies of random variables. To substantiate the optimal discretization procedure, we use the results of a study of the asymptotic properties of a kernel-type regression estimate of the probability density. An optimal number of sampling intervals for the range of values of one-and twodimensional random variables is determined from the condition of the minimum root-mean square deviation of the regression probability density estimate. The results obtained are generalized to the discretization of the range of values of a multidimensional random variable. The optimal discretization formula contains a component that is characterized by a nonlinear functional of the probability density. An analytical dependence of the detected component on the antikurtosis coefficient of a one-dimensional random variable is established. For independent components of a multidimensional random variable, a methodology is developed for calculating estimates of the optimal number of sampling intervals for random variables and their lengths. On this basis, a nonparametric algorithm for the automatic classification is developed. It is based on a sequential procedure for checking the proximity of the centers of multidimensional sampling intervals and relationships between frequencies of the membership of the random variables from the original sample of these intervals. To further increase the computational efficiency of the proposed automatic classification algorithm, a multithreaded method of its software implementation is used. The practical significance of the developed algorithms is confirmed by the results of their application in processing remote sensing data. © 2021, Institution of Russian Academy of Sciences. All rights reserved.

Scopus

Держатели документа:
Siberian Federal University, Svobodny Av. 79, Krasnoyarsk, 660041, Russian Federation
Institute of Computational Modelling SB RAS, Akademgorodok 50, Krasnoyarsk, 660036, Russian Federation
Sukachev Institute of Forest SB RAS, Akademgorodok 50, Krasnoyarsk, 660036, Russian Federation
Reshetnev Siberian State University of Science and Technology, Krasnoyarsky Rabochy Av. 31, Krasnoyarsk, 660037, Russian Federation
Krasnoyarsk Branch of the Federal Research Center for Information and Computational Technologies, Mira Av. 53, Krasnoyarsk, 660049, Russian Federation

Доп.точки доступа:
Zenkov, I. V.; Lapko, A. V.; Lapko, V. А.; Im, S. T.; Tuboltsev, V. P.; Аvdeenok, V. L.

/ A. K. Ekart, A. Y. Larionova, A. N. Kravchenko [et al.] // Russ. J. Genet. - 2021. - Vol. 57, Is. 8. - P920-927, DOI 10.1134/S1022795421070073. - Cited References:36. - This study was supported by the Russian Foundation for Basic Research, the Government of Krasnoyarsk krai, and the Krasnoyarsk Regional Fund of Science (project no. 1944-240006 r_a), as well as by the Russian Foundation for Basic Research (project no. 18-04-01061a). . - ISSN 1022-7954. - ISSN 1608-3369РУБ Genetics & Heredity

Аннотация: The genetic diversity, structure, and differentiation of relict lime plantations in Krasnoyarsk krai (considered as a separate species Tilia nasczokinii Stepanov) were for the first time studied on the basis of the analysis of variability of 12 microsatellite markers of the nuclear genome. In addition, six T. cordata Mill. populations from the European and West Siberian parts of its range and the T. sibirica Bayer population from Kemerovo oblast were included in the study. It was found that lime plantations in the vicinity of Krasnoyarsk (Manskoye Zaymishche and Kashtak) have a similar genetic structure and are in a state close to equilibrium. The level of genetic variability of T. nasczokinii populations is comparable to the level of variability of the T. sibirica population, but was significantly lower than in T. cordata populations. Estimation of the degree of genetic differentiation of lime populations according to interpopulation paired F-st values and Nei's genetic distances (D-N72) detected significant differences of the T. nasczokinii populations from the T. cordata and T. sibirica populations. The analysis of genetic differentiation (by the PCoA method) of paired F-st values and individual genetic distances (D), as well as clustering in STRUCTURE, demonstrated the separation of the studied populations into three groups according to their species affiliation. Moreover, the T. nasczokinii populations are genetically removed from the T. sibirica population to a greater extent than from T. cordata populations.

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Держатели документа:
Russian Acad Sci, Sukachev Inst Forest, Siberian Branch, Krasnoyarsk 660036, Russia.
Russian Acad Sci, Inst Plant & Anim Ecol, Ural Branch, Ekaterinburg 620144, Russia.

Доп.точки доступа:
Ekart, A. K.; Larionova, A. Ya; Kravchenko, A. N.; Semerikova, S. A.; Sedaeva, M., I; Russian Foundation for Basic ResearchRussian Foundation for Basic Research (RFBR) [18-04-01061a]; Government of Krasnoyarsk krai; Krasnoyarsk Regional Fund of Science [1944-240006 r_a]