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Article

Spatiotemporal Assessment of Climate Change Impacts on Pasture Ecosystems in Central Kazakhstan Using Remote Sensing and Spatial Analysis

1
Department of Geography, Land Management and Cadastre, Al-Farabi Kazakh National University, 71 Al-Farabi Ave., Almaty 050040, Kazakhstan
2
Department of Cartography and Geoinformatics, Al-Farabi Kazakh National University, 71 Al-Farabi Ave., Almaty 050040, Kazakhstan
3
Space Technology and Remote Sensing Center, Al-Farabi Kazakh National University, 71 Al-Farabi Ave., Almaty 050040, Kazakhstan
4
Department of Biodiversity and Bioresources, Al-Farabi Kazakh National University, 71 Al-Farabi Ave., Almaty 050040, Kazakhstan
*
Author to whom correspondence should be addressed.
Sustainability 2025, 17(22), 10331; https://doi.org/10.3390/su172210331
Submission received: 8 October 2025 / Revised: 7 November 2025 / Accepted: 14 November 2025 / Published: 18 November 2025

Abstract

The study aims to evaluate the impact of climate change on pasture ecosystems in Central Kazakhstan, particularly within the Karaganda and Ulytau regions. The assessment combines remote sensing indicators (NDVI, LST) with long-term climatic datasets (CRU TS v4.09 and national meteorological records) for the period 2000–2024. Non-parametric statistical methods, including the Mann–Kendall trend test, Sen’s slope estimator, and Pettitt’s test, were applied to identify the direction, intensity, and structural shifts in temperature and precipitation trends. The results indicate significant regional warming, especially during summer and spring, alongside spatially inconsistent precipitation changes. The southern and southwestern areas (Zhezkazgan and Satpayev) show intensified aridization, manifested in rising land surface temperatures, decreasing rainfall, and declining vegetation productivity and exacerbated by anthropogenic pressures. Conversely, the eastern and northeastern regions exhibit stable or increasing NDVI values and moderate precipitation growth, suggesting potential for natural recovery. The study concludes that pasture degradation in Central Kazakhstan is driven by combined climatic and human factors, with pronounced spatial heterogeneity. The integrated approach enhances the reliability of climate impact assessments and provides a scientific basis for developing adaptive and region-specific strategies for sustainable pasture management under ongoing climate change.
Keywords: climate change; pasture ecosystems; Central Kazakhstan; degradation; NDVI; remote sensing climate change; pasture ecosystems; Central Kazakhstan; degradation; NDVI; remote sensing

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MDPI and ACS Style

Tokbergenova, A.; Kaliyeva, D.; Zulpykharov, K.; Taukebayev, O.; Salmurzauly, R.; Assanbayeva, A.; Mukhtarov, U.; Bilalov, B.; Tokkozhayev, D. Spatiotemporal Assessment of Climate Change Impacts on Pasture Ecosystems in Central Kazakhstan Using Remote Sensing and Spatial Analysis. Sustainability 2025, 17, 10331. https://doi.org/10.3390/su172210331

AMA Style

Tokbergenova A, Kaliyeva D, Zulpykharov K, Taukebayev O, Salmurzauly R, Assanbayeva A, Mukhtarov U, Bilalov B, Tokkozhayev D. Spatiotemporal Assessment of Climate Change Impacts on Pasture Ecosystems in Central Kazakhstan Using Remote Sensing and Spatial Analysis. Sustainability. 2025; 17(22):10331. https://doi.org/10.3390/su172210331

Chicago/Turabian Style

Tokbergenova, Aigul, Damira Kaliyeva, Kanat Zulpykharov, Omirzhan Taukebayev, Ruslan Salmurzauly, Aisara Assanbayeva, Ulan Mukhtarov, Bekzat Bilalov, and Dias Tokkozhayev. 2025. "Spatiotemporal Assessment of Climate Change Impacts on Pasture Ecosystems in Central Kazakhstan Using Remote Sensing and Spatial Analysis" Sustainability 17, no. 22: 10331. https://doi.org/10.3390/su172210331

APA Style

Tokbergenova, A., Kaliyeva, D., Zulpykharov, K., Taukebayev, O., Salmurzauly, R., Assanbayeva, A., Mukhtarov, U., Bilalov, B., & Tokkozhayev, D. (2025). Spatiotemporal Assessment of Climate Change Impacts on Pasture Ecosystems in Central Kazakhstan Using Remote Sensing and Spatial Analysis. Sustainability, 17(22), 10331. https://doi.org/10.3390/su172210331

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