Mapping of vegetation communities of the subzone of dark coniferous forests of the South Sakhalin based on space surveys

Verkhoturov, Alexey A.; Melkiy, Vyacheslav A.

doi:10.35595/2414-9179-2020-4-26-60-72

Cited by 3 publications

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References 12 publications

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“…Использование географических информационных систем в качестве методологической основы позволит осуществить картирование ареалов лекарственных растений [7][8][9], провести анализ растительных сообществ не только для территории Среднего Урала на высоком научном уровне, но и других регионов при наличии соответствующих топооснов [1][2][3][4].…”

Section: Introductionunclassified

Development of a Predictive Model for Estimating Stocks of Medicinal Plants Using GIS Tools on the Example of the Middle Urals

Turyshev

Белоногова

Лужанин

2022

Razrabotka i registraciâ lekarstvennyh sredstv

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Introduction. Intensive anthropogenic impact leads to a sharp reduction in natural reserves of many valuable plants. In this regard, previously obtained data on stocks quickly become obsolete. Therefore, the inventory of stocks of medicinal plants in the Russian Federation as a whole and the Middle Urals, in particular, remains an urgent problem. Unfortunately, modern technologies are not being implemented intensively enough in the domestic pharmacy. In our opinion, the reasons for this are expensive software, insufficient theoretical and practical skills to work on personal computers, as well as the specifics of the industry. Despite this, the use of geographic information systems (GIS) in pharmacy is quite promising [7–9]. The use of geographical information systems as a methodological basis will make it possible to map the areas of medicinal plants, to analyze plant communities not only for the territory of the Middle Urals at a high scientific level [1, 4].Aim. Development of predictive models for the distribution of medicinal plants based on a comprehensive assessment of the state of populations of wild medicinal plants of the Middle Urals.Materials and methods. The determination of raw material reserves of the studied species of medicinal plants was carried out on specific thickets according to the generally accepted methodology. The authenticity of raw materials was established by the macroscopic method when collecting samples of raw materials. In the course of the study, stocks of 4652 populations of 27 species of medicinal plants growing in the Middle Urals were studied. The collection of the material was carried out in the period from 2006 to 2019 during the survey of the administrative districts of the Perm Krai and the Sverdlovsk region. A comparative comprehensive assessment of resource and phytochemical indicators was studied using the example of 6 species of wild medicinal plants: Origanum vulgare L., Lamiaceae, Hypericum perforatum L., Hypericaceae and Hypericum maculatum Crantz, Hypericaceae, Tanacetum vulgare L., Asteraceae, Artemisia absinthium L., Asteraceae, Leonurus quinquelobatus Gilib., Lamiaceae, Achillea millefolium L., Asteraceae.Results and discussion. In the course of resource and phytochemical studies of representatives of the medicinal flora of the Middle Urals, a comprehensive assessment of the state of populations of wild medicinal plants – sources of medicinal plant raw materials (herba Origani vulgaris, herba Hyperici, flores Tanaceti vulgaris, herba Artemisiae absinthii, herba Achilleae millefolii and herba Leonuri) was carried out. A geospatial analysis of the distribution of medicinal plant populations by soil types within the regions of the Middle Urals was carried out. An algorithm for constructing predictive models of the distribution of populations of wild medicinal plants of the Middle Urals has been worked out. A set of maps of the "occurrence" of medicinal plants in the study area has been developed.Conclusion. The conducted complex of studies will allow updating information about the medicinal flora of the Middle Urals. Developed on the example of a number of representatives of the medicinal flora of the Middle Urals, the algorithm for constructing forecast maps can be used for any regions in the presence of appropriate topos.

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Section: Introductionunclassified

Development of a Predictive Model for Estimating Stocks of Medicinal Plants Using GIS Tools on the Example of the Middle Urals

Turyshev

Белоногова

Лужанин

2022

Razrabotka i registraciâ lekarstvennyh sredstv

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Geoinformation analysis of variability state of the natural environment after eruption of the Chikurachki volcano by remote sensing data

Verkhoturov

Melkiy

2021

ICIGIS

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Explosive volcanic eruptions pose certain danger for natural environment, transport communications and other objects of human economic activity due to the fact that during such eruptions, up to several cubic kilometers of volcanic ash and aerosols can enter to atmosphere in long time. The research of extent of the impact of volcanic eruptions on surrounding area and the determination of their consequences contributes to reasonable assessment of volcanic hazard and possible risks in time conduct of economic activities and ensuring for safe location of settlements, enterprises, sea way and air lines. Chikurachki volcano is one from most active on territory of the Kuril Island Arc. In articles of volcanologists is information about eruptions in 1853–1859, 1958, 1961, 1964, 1973, 1986, 2002, 2003, 2005, 2007, 2008, 2015, 2016. The vegetation index (NDVI) used as means of assessing state of the natural environment. The boundary dividing areas with disturbed and healthy vegetation cover taken along isoline with NDVI value of 0.4. Schematic maps of the dynamics of boundary isolines according for the vegetation index from 1972 to 2020 has been compiled. The dynamics of vegetation cover in the north-eastern, south-eastern and southern sectors relative to Chikurachki volcano is revealed. The north-eastern sector experienced strong negative impact of eruption of the Chikurachki volcano in 1853, at later (2007 and 2015) only ash falls were observed in this direction. The vegetation cover outside the isoline NDVI = 0.4 has almost completely recovered to 2020. The south-eastern sector damaged during eruption of 1986, and was also subject for periodic tephra precipitation and ash falls during 2002–2016. Vegetation was completely destroyed at distance of 9 km from the crater of the volcano, and also valley forests on Tukharka River were destroyed. In southern sector in upper part of the Vernadsky Ridge, harsh growing conditions do not allow vegetation to recover for decades. At the same time, on eastern and western slopes of the ridge, after eruptions with deposition of tephra by layer of small thickness, alder elfin restoration few years. The results of the recearch can be used in forecasting volcanic hazards and rapid assessment of impact on natural environment of territories adjacent to volcanoes of this type as a result of volcanic eruptions.

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Analysis of the dynamics of condition forest plant communities in the “Makarovsky” nature sanctuary (Sakhalin Island) by remote sensing data

Melkiy,

Verkhoturov

2023

ICIGIS

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The results of the analysis of changes in the state of forest plant communities in the “Makarovsky” Nature Sanctuary in the period from 1980 to 2020 are presented in the article. In the process of our work there was created a model of the vegetation cover of the “Makarovsky” Sanctuary, which made it possible to determine the difference between plant communities and their condition. The data for the construction of the cartographic model were formalized spectral characteristics of the surface of plant communities recorded on Landsat-1–7 and Sentinel-2 images. In a specially protected natural area, 7 classes of objects have been identified when conducting uncontrolled classification using ArcGIS according by their spectral characteristics. The division of dark coniferous and deciduous forests, the identification of the boundaries of plots with different species composition of forest stands and the allocation of felling sites was performed on the basis of the normalized vegetation index (NDVI). The accuracy of determining the composition of forest stands based on the results of interpretation was checked by data of geobotanical research data on the territory of the “Makarovsky” Nature Sanctuary. As part of the vegetation cover of the “Makarovsky” Nature Sanctuary, 8 forest communities were identified—spruce-fir, stone-birch forests, cedar elfin formation, valley deciduous, birch, birch-spruce forests, woodlands, sometimes larch forests, and 2 non-forest communities—Kuril bamboo formation and meadow vegetation. Forest communities occupy 95 % of the territory of the “Makarovsky” Sanctuary. The landscape and climatic conditions of the area are optimal for the growth of spruce-fir forests, which cover 44 % of the total area of the “Makarovsky” Nature Sanctuary. Birch and stone-birch forests (39 %) are widespread on logged land in Sanctuary. There is a wide distribution of secondary succession in the territory of the “Makarovsky” Nature Sanctuary. The composition of forest stands in Sanctuary has changed significantly over the research period in favor of young coniferous trees. Vegetation in the “Makarovsky” Nature Sanctuary has preserved its natural pristine appearance and reflects both altitude differentiation and landscape-zonal features of the middle taiga subzone of Sakhalin. The use of satellite images of medium spatial resolution made it possible to accurately analyze the state of forests of the “Makarovsky” Sanctuary. More detailed researches require the use of unmanned aerial vehicles.

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Mapping of vegetation communities of the subzone of dark coniferous forests of the South Sakhalin based on space surveys

Cited by 3 publications

References 12 publications

Development of a Predictive Model for Estimating Stocks of Medicinal Plants Using GIS Tools on the Example of the Middle Urals

Development of a Predictive Model for Estimating Stocks of Medicinal Plants Using GIS Tools on the Example of the Middle Urals

Geoinformation analysis of variability state of the natural environment after eruption of the Chikurachki volcano by remote sensing data

Analysis of the dynamics of condition forest plant communities in the “Makarovsky” nature sanctuary (Sakhalin Island) by remote sensing data

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