Abstract

The article deals with the problem of overgrowing trees and shrubs of abandoned agricultural land in the Perm Region. The widespread occurrence of overgrowth processes in the non-chernozem zone is associated with the close proximity of agricultural land and forested areas. Also, a significant reason for widespread occurrence of this process is the non-use of land by agricultural producers in the region, due to financial problems and lack of funds to carry out work to return agricultural land to use. The method is based on the use of Landsat satellite imagery data. Analysis has been performed over a 30-year period, from the time of a maximum use of agricultural land to the present day. The processes of overgrowing of agricultural land on the territory of the Perm Region are used quite actively, this is due to the close proximity of agricultural land, as well as, often, with the non-use of the region’s land by agricultural producers due to financial difficulties and the lack of work to return agricultural land into circulation. The results are presented for the municipal districts of the Perm Region. The total area of overgrown agricultural land in 2020 is 138,610 km2 (58.8 % of the total area of agricultural land in the Perm Region). Early stages of forest regeneration are not identified on satellite images due to their low spatial resolution. Approximately 68,950 km2 of agricultural land are covered by closed forest vegetation, its return to agricultural use has extremely low economic efficiency for agricultural manufacturers of the region. Young unclosed forest vegetation covers 69,660 km2. Accuracy assessment is performed based on reference sites with ground survey and high-resolution satellite images from public services (Google Earth and ESRI Imagery).

Highlights

  • The article deals with the problem of overgrowing trees and shrubs of abandoned agricultural land in the Perm Region

  • Карты и ГИС в cельском хозяйстве и землепользовании non-chernozem zone is associated with the close proximity of agricultural land and forested areas

  • A significant reason for widespread occurrence of this process is the non-use of land by agricultural producers in the region, due to financial problems and lack of funds to carry out work to return agricultural land to use

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Summary

Исходные данные

Классификация территорий на три класса, выявляющая зарастание на 2018–2020 гг. Лесопокрытые территории были выделены на основе снимков Landsat (TM), полученных в зимний период времени на 1986–1988 гг.[1] Снимки зимнего сезона позволяют довольно четко определить территории зарастания. Определение двух классов (лесопокрытые и безлесные территории) происходит с помощью управляемой классификации по методу максимального правдоподобия (рис.[1]). Для классификации использованы композитные снимки, созданные на основе комбинации «Искусственные цвета» (ближний инфракрасный, красный и зеленый спектральные каналы) [Белоусова, 2018]. Далее проведена классификация территорий на три класса в границах маски сельскохозяйственных угодий, выявляющая процессы зарастания Исходными данными выступают данные программы Landsat (OLI) за 2018–2020 гг., полученные в период с устойчивым снежным покровом. Применен метод максимального правдоподобия для композитных снимков, созданных на основе комбинации «Искусственные цвета»

Карты и ГИС в cельском хозяйстве и землепользовании
Процент обеспеченности сельскохозяйственными угодьями
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