Natural Afforestation of Postagrogenic Lands in the South of the Central Russian Upland
DOI:
https://doi.org/10.52575/2712-7443-2024-48-3-405-415Keywords:
abandoned agricultural lands, natural afforestation, time series, Central Russian Upland, Sentinel-2Abstract
The article explores types of postagrogenic lands in the south of the Central Russian Upland, differing in natural afforestation. Four land categories are distinguished according to this feature: with areas of closed forest; with numerous isolated trees; with rare isolated trees; without forest vegetation. The abandoned lands with isolated trees and without closed forest vegetation are characterized by the absence of a statistically significant trend in the long-term dynamics of the NDVI vegetation index. Abandoned farmlands with areas of closed forest have a trend, but its statistical significance is close to the threshold value. The distribution of forest vegetation on abandoned agricultural lands is manifested in the spectral reflectance of visible, near and short-wave infrared ranges derived from Sentinel-2 data. However, the types of abandoned agricultural lands without closed forest do not display any statistically significant difference from each other in any spectral range. Statistically significant differences start to appear simultaneously with the formation of such areas, when forest cover of individual land reaches 27–30 %. The appearance of numerous isolated trees in the absence of a continuous tree cover does not lead to the formation of statistically significant differences in the spectral reflectance measured using Sentinel-2 data from lands without tree vegetation.
Acknowledgements: This research was funded by the Ministry of Science and Higher Education of the Russian Federation within the framework of State Assignment No. FZWG-2023-0011
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Атутова Ж.В. 2020. Современное состояние залежных угодий Тункинской котловины (юго-западное Прибайкалье). География и природные ресурсы, 2(161): 51–61. https://doi.org/10.21782/GIPR0206-1619-2020-2(51-61)
Голеусов П.В., Лисецкий Ф.Н. 2009. Воспроизводство почв в антропогенных ландшафтах лесостепи. М., Белгородский государственный национальный исследовательский университет, 232 с.
Данилов Д.А., Яковлев А.А., Крылов И.А. 2023. Формирование естественных растительных ассоциаций на постагрогенных землях. Известия Санкт-Петербургской лесотехнической академии, 242: 60–82. https://doi.org/10.21266/2079-4304.2023.242.60-82
Иванов А.И., Иванова Ж.А., Соколов И.В. 2020. Вторичное освоение неиспользуемых угодий. Российская сельскохозяйственная наука, 2: 48–52. https://doi.org/10.31857/S2500-2627-2020-2-48-52
Китов М.В., Цапков А.Н. 2015. Изменения площадей залежных земель на Европейской территории России за период 1990-2013 гг. Научные ведомости Белгородского государственного университета. Серия: Естественные науки, 15(212): 163–171.
Курбанов Э.А., Воробьев О.Н., Меньшиков С.А., Смирнова Л.Н. 2018. Распознавание лесных насаждений и доминирующих древесных пород Пензенской области по данным спутника Sentinel-2. Современные проблемы дистанционного зондирования Земли из космоса, 15(5): 154–166. https://doi.org/10.21046/2070-7401-2018-15-5-154-166
Терехин Э.А. 2022. Особенности лесовозобновления на залежных землях Среднерусской лесостепи. Известия РАН. Серия географическая, 86(4): 594–604. https://doi.org/10.31857/S2587556622040112
Широких П.С., Федоров Н.И., Туктамышев И.Р., Бикбаев И.Г., Мартыненко В.Г. 2023. Закономерности лесовосстановительных сукцессий на заброшенных сельскохозяйственных землях Башкирского Предуралья. Экология, 3: 179–187. https://doi.org/10.31857/S036705972303006X
Физико-географическое районирование центральных черноземных областей. 1961. Под. ред. Ф.Н. Милькова. Воронеж, Изд-во Воронежского университета, 263 с.
Bera D., Das Chatterjee N., Bera S., Ghosh S., Dinda S. 2023. Comparative Performance of Sentinel-2 MSI and Landsat-8 OLI Data in Canopy Cover Prediction Using Random Forest Model: Comparing Model Performance and Tuning Parameters. Advances in Space Research, 71(11): 4691–4709. https://doi.org/10.1016/j.asr.2023.01.027
Bowen M.E., McAlpine C.A., House A.P.N., Smith G.C. 2007. Regrowth Forests on Abandoned Agricultural Land: A Review of Their Habitat Values for Recovering Forest Fauna, Biological Conservation, 140(3–4): 273–296. https://doi.org/10.1016/j.biocon.2007.08.012
Estel S., Kuemmerle T., Alcántara C., Levers C., Prishchepov A., Hostert P. 2015. Mapping Farmland Abandonment and Recultivation Across Europe Using MODIS NDVI Time Series. Remote Sensing of Environment, 163: 312–325. https://doi.org/10.1016/j.rse.2015.03.028
Fayet C.M.J., Reilly K.H., Van Ham C., Verburg P.H. 2022. What is the Future of Abandoned Agricultural Lands? A Systematic Review of Alternative Trajectories in Europe. Land Use Policy, 112: 105833. https://doi.org/10.1016/j.landusepol.2021.105833
Koroleva N.V., Tikhonova E.V., Ershov D.V., Saltykov A.N., Gavrilyuk E.A., Pugachevskii A.V. 2018. Twenty-Five Years of Reforestation on Nonforest Lands in Smolenskoe Poozerye National Park According to Landsat Imagery Assessment. Contemporary Problems of Ecology, 11(7): 719–728. https://doi.org/10.1134/S1995425518070077
Velázquez E., Martínez-Jaraíz C., Wheeler C., Mitchard E.T.A., Bravo F. 2022. Forest Expansion in Abandoned Agricultural Lands has Limited Effect to Offset Carbon Emissions from Central-North Spain. Regional Environmental Change, 22(4): 132. https://doi.org/10.1007/s10113-022-01978-0
Wu J., Jin S., Zhu G., Guo J. 2023. Monitoring of Cropland Abandonment Based on Long Time Series Remote Sensing Data: a Case Study of Fujian Province, China. Agronomy, 13(6): 1585. https://doi.org/10.3390/agronomy13061585
Yang X., Qiu S., Zhu Z., Rittenhouse C., Riordan D., Cullerton M. 2023. Mapping Understory Plant Communities in Deciduous Forests from Sentinel-2 Time Series. Remote Sensing of Environment, 293: 113601. https://doi.org/10.1016/j.rse.2023.113601
Zhao X., Wu T., Wang S., Liu K., Yang J. 2023. Cropland Abandonment Mapping at Sub-Pixel Scales Using Crop Phenological Information and MODIS Time-Series Images. Computers and Electronics in Agriculture, 208: 107763. https://doi.org/10.1016/j.compag.2023.107763
Zhu X., Xiao G., Zhang D., Guo L. 2021. Mapping Abandoned Farmland in China Using Time Series MODIS NDVI. Science of the Total Environment, 755: 142651. https://doi.org/10.1016/j.scitotenv.2020.142651
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