ISSN 1995-4301
(Print)

ISSN 2618-8406
(Online)

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2 issue of the journal in 2024

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Monitoring the distribution of Heracleum sosnowskyi in urban areas based on Earth remote sensing data

T.Ya. Ashikhmina, V.V. Rutman, T.A. Adamovich, E.V. Tovstik
Section: Monitoring of natural and anthropogenically disturbed areas
The article deals with the problem of distribution and the possibility of monitoring Sosnowsky’s hogweed (Heracleum sosnowskyi Manden.) in certain areas of the urban environment using Earth remote sensing data. The Sentinel-2 images with a resolution of 10 m were used as the initial satellite information. Identifying, tracking, analysis and mapping the distribution areas of Sosnowsky’s hogweed were carried out using satellite data. The choice of mass growing areas of Sosnovsky’s hogweed for monitoring was carried out during the preliminary field studies of the urban territory of Kirov. The monitoring studies were based on differences in the reflectivity between the hogweed and other environmental objects. Satellite data processing was carried out using the QGIS-3.26 program. Based on the results of the work, maps were obtained, on which areas of mass growth of Sosnowsky’s hogweed were visualized. The built-in tools of the program allowed calculating the area of distribution of the studied invasive species in certain areas of Kirov. The identified areas were represented by plots of continuous overgrowth and its distribution in small groups. The paper describes a technique that makes it possible to calculate changes in the areas of plots of continuous overgrowth of Sosnowsky’s hogweed in the study area. The technique enables to identify periods of maximum growth of hogweed, to determine the trends in the area of its continuous overgrowth.
The results of the work demonstrate the effectiveness of a combination of Earth remote sensing methods and satellite image processing algorithms in monitoring the distribution of Sosnowsky’s hogweed.
Keywords: Heracleum sosnowskyi, invasive species, monitoring, Earth remote sensing, Sentinel-2, processing algorithm, overgrowth area

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Article published in number 3 for 2023
DOI: 10.25750/1995-4301-2023-3-073-080
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