МОНИТОРИНГ СЕЛЬСКОХОЗЯЙСТВЕННЫХ ТЕРРИТОРИЙ КЫЗЫЛОРДИНСКОЙ ОБЛАСТИ С ПРИМЕНЕНИЕМ СОВРЕМЕННЫХ ТЕХНОЛОГИЙ

Асель Алтаева; Асель Даркенбаева; Батырхан Садықов

doi:10.37884/3-2025/43

Abstract

In the context of global climate change and water resource scarcity, the need to implement modern monitoring technologies to improve agricultural efficiency is increasing. This article is dedicated to analyzing the potential of Earth remote sensing (ERS) and geographic information systems (GIS) for monitoring the condition of agricultural lands in the Kyzylorda region. The key tool used is the NDVI (Normalized Difference Vegetation Index), which allows for the operational assessment of vegetation condition and agroecosystem productivity. Based on satellite data from recent years' vegetation periods, spatial and temporal changes in the state of agricultural lands were identified, which made it possible to determine areas with sustainable development and problematic zones requiring additional attention. The paper presents thematic maps of NDVI distribution, analyzes factors affecting the decrease in vegetation activity, including weather conditions, irrigation levels, and soil degradation. The results confirm the high informational value and practical significance of using NDVI in agro-monitoring, and highlight the need for integrating remote sensing methods into the regional agricultural management system. The proposed approach can be useful for government bodies, farming enterprises, and research institutions in making decisions on adapting agriculture to modern climate challenges.

NDVI Earth remote sensing Sentinel-2 ArcGIS Pro agriculture Kyzylorda region agro-monitoring vegetation index geospatial technologies vegetation

01 Introduction

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02 References

1. Segarra, J., Buchaillot, M. L., Araus, J. L., Kefauver, S. C. Remote sensing for precision agriculture: Sentinel-2 improved features and applications. Agronomy, 10(5), Article 641, 2020. P. 2-18. https://doi.org/10.3390/agronomy10050641.
2. Huang, S. A commentary review on the use of normalized difference vegetation index (NDVI). Journal of Forest Research, 32(4), 2021. P. 683–698. https://doi.org/10.1007/s11676-020-01155-1.
3. Liepa, A. et al. Harmonized NDVI time-series from Landsat and Sentinel-2: Capturing phenological patterns. Remote Sensing Applications: Society and Environment, 29, 2024. P. 100—115. https://doi.org/10.1016/j.rsase.2024.1000946.
4. Rafikov, T., Zhumatayeva, Z., Mukaliyev, Z., & Zhildikbayeva, A. Evaluating land degradation in East Kazakhstan using NDVI and Landsat data. International Journal of Design Nature and Ecodynamics, 19(5), 2024. P. 1677–1686. https://doi.org/10.18280/ijdne.190521.
5. Кенжегалиев Е.М. Система спутникового мониторинга состояния посевов сельскохозяйственных культур. Международный научный журнал «Вестник науки», № 4 (25), том 4, 2020. С. 87–90.
6. Рафиков Т., Ерболқызы М., Жилдикбаева А. Применение данных дистанционного зондирования земли и анализа NDVI в Восточно-Казахстанской области. Izdenister Natigeler, (1 (101), 2024. С.183–191. https://doi.org/10.37884/1-2024/18.
7. Айтхожаева , Г., Жилдикбаева , А., Пентаев, Т., Баухан , А., Жумагалиева , Н., Гурскиене В. Современное состояние использования земель сельхозяйственного назначения в контексте устойчивого развития. Izdenister Natigeler, (3(103), 2024. С. 380–387. https://doi.org/10.37884/3-2024/42.
8. Rafikov, T., Erbolkyzy, M., Zhildikbayeva, A. Применение данных дистанционного зондирования Земли и анализа NDVI в Восточно-Казахстанской области. Ізденістер, нәтижелер – Исследования, результаты, (1)101, 2024. P. 183–192. https://doi.org/10.37884/1-2024/18.
9. Alpysbay, M. A., & Gapparov, A. Z. Agricultural land monitoring using Sentinel-2 satellite data. Engineering Journal of Satbayev University, 143(2), 2021. P. 14–21. https://doi.org/10.51301/vest.su.2021.i2.02.
10. Arystanov, A. Use of indices applied to remote sensing for establishing winter wheat crops in South Kazakhstan. Sustainability, 16(17), 2024. P. 7548. https://doi.org/10.3390/su16177548
11. Nugmanov, A. Quantitative assessment of soil condition based on Sentinel-2 for flax productivity in the steppe zone of Kazakhstan. Journal of Agricultural Science and Technology, 15(3), 2023. P. 55–67. https://pubmed.ncbi.nlm.nih.gov/37971089/.
12. Farmonov, N., Amankulova, K., Szatmari, J., Urinov, J., Narmanov, Z., Nosirov, J., Mucsi, L. Combining PlanetScope and Sentinel-2 images with environmental data for improved wheat yield estimation. International Journal of Digital Earth, 16(1), 2023. P. 847–867. https://doi.org/10.1080/17538947.2023.2186505
13. Löw, F. Mapping abandoned agricultural land in Kyzyl-Orda, southern Kazakhstan. Land Use Policy, 48, 2015. P. 76–86. https://doi.org/10.1016/j.landusepol.2015.04.024
14. Kabzhanova, G. Remote sensing applications for pasture assessment in Kazakhstan. Agronomy, 15(3), 2025. P. 526-529. https://doi.org/10.3390/agronomy15030526.

Citation Links

[1]2025. MONITORING OF AGRICULTURAL AREAS IN KYZYLORDA REGION USING MODERN TECHNOLOGIES. Izdenister natigeler. 3 (107) (Sep. 2025), 454–464. DOI:https://doi.org/10.37884/3-2025/43.

(1)MONITORING OF AGRICULTURAL AREAS IN KYZYLORDA REGION USING MODERN TECHNOLOGIES. Izdenister natigeler 2025, No. 3 (107), 454-464. https://doi.org/10.37884/3-2025/43.

MONITORING OF AGRICULTURAL AREAS IN KYZYLORDA REGION USING MODERN TECHNOLOGIES. (2025). Izdenister Natigeler, 3 (107), 454-464. https://doi.org/10.37884/3-2025/43

MONITORING OF AGRICULTURAL AREAS IN KYZYLORDA REGION USING MODERN TECHNOLOGIES. Izdenister natigeler, [S. l.], n. 3 (107), p. 454–464, 2025. DOI: 10.37884/3-2025/43. Disponível em: https://agrosoil.kaznaru.edu.kz/index.php/research/article/view/980. Acesso em: 15 sep. 2026.

“MONITORING OF AGRICULTURAL AREAS IN KYZYLORDA REGION USING MODERN TECHNOLOGIES”. 2025. Izdenister Natigeler, no. 3 (107) (September): 454-64. https://doi.org/10.37884/3-2025/43.

“MONITORING OF AGRICULTURAL AREAS IN KYZYLORDA REGION USING MODERN TECHNOLOGIES” (2025) Izdenister natigeler, (3 (107), pp. 454–464. doi:10.37884/3-2025/43.

[1]“MONITORING OF AGRICULTURAL AREAS IN KYZYLORDA REGION USING MODERN TECHNOLOGIES”, Izdenister natigeler, no. 3 (107), pp. 454–464, Sep. 2025, doi: 10.37884/3-2025/43.

“MONITORING OF AGRICULTURAL AREAS IN KYZYLORDA REGION USING MODERN TECHNOLOGIES”. Izdenister Natigeler, no. 3 (107), Sept. 2025, pp. 454-6, https://doi.org/10.37884/3-2025/43.

“MONITORING OF AGRICULTURAL AREAS IN KYZYLORDA REGION USING MODERN TECHNOLOGIES”. Izdenister natigeler, no. 3 (107) (September 30, 2025): 454–464. Accessed September 15, 2026. https://agrosoil.kaznaru.edu.kz/index.php/research/article/view/980.

1.MONITORING OF AGRICULTURAL AREAS IN KYZYLORDA REGION USING MODERN TECHNOLOGIES. Izdenister natigeler [Internet]. 2025 Sep. 30 [cited 2026 Sep. 15];(3 (107):454-6. Available from: https://agrosoil.kaznaru.edu.kz/index.php/research/article/view/980

1.MONITORING OF AGRICULTURAL AREAS IN KYZYLORDA REGION USING MODERN TECHNOLOGIES. Izdenister natigeler. 2025;(3 (107):454-464. doi:10.37884/3-2025/43

[1] 1. Segarra, J., Buchaillot, M. L., Araus, J. L., Kefauver, S. C. Remote sensing for precision agriculture: Sentinel-2 improved features and applications. Agronomy, 10(5), Article 641, 2020. P. 2-18. https://doi.org/10.3390/agronomy10050641.

[2] 2. Huang, S. A commentary review on the use of normalized difference vegetation index (NDVI). Journal of Forest Research, 32(4), 2021. P. 683–698. https://doi.org/10.1007/s11676-020-01155-1.

[3] 3. Liepa, A. et al. Harmonized NDVI time-series from Landsat and Sentinel-2: Capturing phenological patterns. Remote Sensing Applications: Society and Environment, 29, 2024. P. 100—115. https://doi.org/10.1016/j.rsase.2024.1000946.

[4] 4. Rafikov, T., Zhumatayeva, Z., Mukaliyev, Z., & Zhildikbayeva, A. Evaluating land degradation in East Kazakhstan using NDVI and Landsat data. International Journal of Design Nature and Ecodynamics, 19(5), 2024. P. 1677–1686. https://doi.org/10.18280/ijdne.190521.

[5] 5. Кенжегалиев Е.М. Система спутникового мониторинга состояния посевов сельскохозяйственных культур. Международный научный журнал «Вестник науки», № 4 (25), том 4, 2020. С. 87–90.

[6] 6. Рафиков Т., Ерболқызы М., Жилдикбаева А. Применение данных дистанционного зондирования земли и анализа NDVI в Восточно-Казахстанской области. Izdenister Natigeler, (1 (101), 2024. С.183–191. https://doi.org/10.37884/1-2024/18.

[7] 7. Айтхожаева , Г., Жилдикбаева , А., Пентаев, Т., Баухан , А., Жумагалиева , Н., Гурскиене В. Современное состояние использования земель сельхозяйственного назначения в контексте устойчивого развития. Izdenister Natigeler, (3(103), 2024. С. 380–387. https://doi.org/10.37884/3-2024/42.

[8] 8. Rafikov, T., Erbolkyzy, M., Zhildikbayeva, A. Применение данных дистанционного зондирования Земли и анализа NDVI в Восточно-Казахстанской области. Ізденістер, нәтижелер – Исследования, результаты, (1)101, 2024. P. 183–192. https://doi.org/10.37884/1-2024/18.

[9] 9. Alpysbay, M. A., & Gapparov, A. Z. Agricultural land monitoring using Sentinel-2 satellite data. Engineering Journal of Satbayev University, 143(2), 2021. P. 14–21. https://doi.org/10.51301/vest.su.2021.i2.02.

[10] 10. Arystanov, A. Use of indices applied to remote sensing for establishing winter wheat crops in South Kazakhstan. Sustainability, 16(17), 2024. P. 7548. https://doi.org/10.3390/su16177548

[11] 11. Nugmanov, A. Quantitative assessment of soil condition based on Sentinel-2 for flax productivity in the steppe zone of Kazakhstan. Journal of Agricultural Science and Technology, 15(3), 2023. P. 55–67. https://pubmed.ncbi.nlm.nih.gov/37971089/.

[12] 12. Farmonov, N., Amankulova, K., Szatmari, J., Urinov, J., Narmanov, Z., Nosirov, J., Mucsi, L. Combining PlanetScope and Sentinel-2 images with environmental data for improved wheat yield estimation. International Journal of Digital Earth, 16(1), 2023. P. 847–867. https://doi.org/10.1080/17538947.2023.2186505

[13] 13. Löw, F. Mapping abandoned agricultural land in Kyzyl-Orda, southern Kazakhstan. Land Use Policy, 48, 2015. P. 76–86. https://doi.org/10.1016/j.landusepol.2015.04.024

[14] 14. Kabzhanova, G. Remote sensing applications for pasture assessment in Kazakhstan. Agronomy, 15(3), 2025. P. 526-529. https://doi.org/10.3390/agronomy15030526.