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The aim of the work is to develop a method of landscape dynamics under anthropogenic impact. The developed methodology is tested on the territory of Kostanay region, which is one of the main regions of mining industry development, with a focus on iron ore mining and crop production. Space images and field survey results are used as input materials. In general, the work consists of the following six stages: the first stage includes the selection and processing of space images, the second stage includes the calculation of indices based on data from different channels of space images, the third stage includes field work aimed at collecting information for verification of the obtained results on the basis of RS data, the fourth stage includes the calculation of range values, the fifth stage comprises verification of the obtained indices, and the final sixth stage deals with calculation of the integral index of landscape degradation degree and analysis of landscape dynamics under anthropogenic impacts. The calculation of the integral indicator of the degree of degradation of the natural environment of the Kostanay region, based on the degradation of each indicator in the conditions of anthropogenic impact, allowed for identification of landscapes with different degrees of degradation (from weak to very strong). The research confirmed that landscapes with a high degree of degradation under anthropogenic impact are confined to semi-desert landscapes in the south of the study region. The degradation of these landscapes is associated not only with anthropogenic impacts but also with natural and climatic features that influence the development of landscape pollution processes. On the contrary, landscapes with a weak degree of degradation correspond to the forest-steppe and steppe zones, characterized by a high level of economic development and resistance to anthropogenic impacts. The verification of the obtained indicators by the values of the remaining 25% of field points determines the reliability of the obtained results, ranging from 87% to 92%, confirming the correct choice of methods and techniques for obtaining the results, especially the choice of field methods and vegetation and non-vegetation indices for assessing the selected indicators. Subsequently, based on the verified map of degradation of the natural environment, created through space monitoring for a certain period, it is possible to forecast the functioning of the natural environment in the conditions of anthropogenic impact.
Słowa kluczowe
Czasopismo
Rocznik
Tom
Strony
80--94
Opis fizyczny
Bibliogr. 27 poz., rys., tab., wykr.
Twórcy
autor
- L.N.Gumilyov Eurasian National University, Kazakhstan
autor
- Shakarim University of Semey, Kazakhstan
autor
- L.N.Gumilyov Eurasian National University, Kazakhstan
autor
- L.N.Gumilyov Eurasian National University, Kazakhstan
autor
- L.N.Gumilyov Eurasian National University, Kazakhstan
Bibliografia
- [1]. Alam A., Mahmood A., Chaudhry M. N., Ahmad Sajid R., Ul Safa N., Alghamdi Huda A., Alhamdi H. W. & Ullah R. (2022). Baseline study in environmental risk assessment: site-specific model development and application. Archives of Environmental Protection, 48, 3, 80-88. DOI:10.24425/aep.2022.142692
- [2]. Belov A.V. & Sokolova L. P. (2014). Ecological potential of vegetation as a factor of nature management in Baikal Siberia. Geography and natural resources, 3, pp. 53-60.
- [3]. El Garouani, A., Mulla, D. J., El Garouani, S. & Knight, J. (2017). Analysis of urban growth and sprawl from remote sensing data: Case of Fez, Morocco. International Journal of Sustainable Built Environment, 6, 1, pp.160–169. DOI:10.1016/j.ijsbe.2017.02.003.
- [4]. Fadhil A.M. (2009). Land Degradation Detection Using Geo-Information Technology for Some Sites in Iraq. Journal of Al-Nahrain University, 12, 3, pp. 94-108.
- [5]. Govaerts, B. & Verhulst, N. (2010). The Normalized Difference Vegetation Index (NDVI) Greenseeker (TM) Handheld Sensor: Toward the Integrated Evaluation of Crop Management Part A: Concepts and Case Studies; CIMMYT: Mexico City, Mexico.
- [6]. Gusev A.P., Kozulev I.I. & Shavrin I. A. (2020). The use of spectral indices for assessing soil erosion in natural and anthropogenic landscapes of Belarus. Russian Journal of Applied Ecology. 2, pp.48-52. (in Russian).
- [7]. Huang, S., Tang, L., Hupy, J.P., Yang, W. & Shao, G. (2021). A commentary review on the use of normalized difference vegetation index (NDVI) in the era of popular remote sensing. Journal of Forestry Research. 32, pp.1-6. DOI:10.1007/s11676-020-01155- 1.
- [8]. https://eos.com/make-an-analysis/ndmi.
- [9]. Krauklis A. A. (1979). Problems of experimental landscape studies. Novosibirsk: Nauka, 233 p. (in Russian).
- [10]. Myachina K.V. & Malakhov D.V. (2013). The experience of using remote sensing data of medium spatial resolution for the identification of oilfield objects in a technogenically modified landscape (on the example of the Orenburg region). Izvestiya Samara Scientific Center of the Russian Academy of Sciences.. 15, 3, p.7. (in Russian). 11. National Atlas of the Republic of Kazakhstan / edited by A.R. Medeu et al. – Almaty, 2010. – Vol. 1. – 150 p. (in Russian).
- [12]. Nachtergaele F., Biancalani R. & Petri M. (2011). Land degradation. Food and Agriculture Organization of the United Nations, 14 p.
- [13]. Official website of the All-Russian Research Institute of Vegetable Growing — branch of the Federal State Budgetary Scientific Institution «Federal Scientific Center of Vegetable Growing».(in Russian).
- [14]. Petrov K. M. (2001). Biogeography with the basics of biosphere protection. St. Petersburg: Publishing House of St. Petersburg University, 476 p.(in Russian)
- [15]. Resolution of the Government of the Republic of Kazakhstan. (2013). The main provisions of the General Scheme of organization of the territory of the Republic of Kazakhstan, № 1434. (in Russian).
- [16]. Samokhvalov Yu.Ya. & Naumenko E.M. (2007). Expert evaluation. Methodological aspect.
- [17]. Kiev, 262 p. (in Russian).
- [18]. Saaty, T.L. (2008). Decision Making with the Analytic Hierarchy Process. Int. J. Serv. Sci., 1, pp. 83–98.
- [19]. Shcheglov D.I. & Gorbunova N.S. (2011). Erosion and soil protection. Publishing and Printing Center of Voronezh State University. p. 33. (in Russian).
- [20]. Sówka I., Badura M., Pawnuk M., Szymański P., Batog P. (2020). The use of the GIS tools in the analysis of air quality on the selected University campus in Poland, Archives of Environmental Protection, 46, 1, 100-106. DOI: 10.24425/aep.2020.132531
- [21]. Sochava V. B. (1980). Geographical aspects of the Siberian taiga. Novosibirsk. Nauka, 256 p. (in Russian)
- [22]. The official website of EOS Data Analytics.
- [23]. Vian, A.L., Bredemeier, C., Turra, M.A., Giordano, C.P.S., Fochesatto, E., Silva, J.A. & Drum, M.A. (2018). Nitrogen management in wheat based on the normalized difference vegetation index (NDVI). Ciência Rural, 48. DOI:10.1590/0103-8478cr20170743 24. Vladimirov I. N., Sofronov A. P., Sorokov A. A., Kobylkin D. V. & Frolov A. A. (2014).
- [25]. Structure of vegetation cover of the Western part of the Upper Angara basin. Geography and natural resources, 2, pp. 44-53.
- [26]. Wilson, E.H. & Sader, S.A. (2002). Detection of forest harvest type using multiple dates of Landsat TM imagery. Remote Sensing of Environment, 80, pp.385-396.
- [27]. Yengoh G.T., Dent D., Olsson L., Tengberg A.E. & Tucker C.J. (2014). The use of the Normalized Difference Vegetation Index (NDVI) to assess land degradation at multiple scales: a review of the current status, future trends, and practical considerations. Lund University Centre for sustainability studies–LUCSUS,. P.80
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-e14503e3-fbce-4a70-9aff-8fe31660f35c