Торайгыров университет

Литература

  1. Разновидности и применение инфракрасных ламп [Электронный ресурс]. – URL: https://www.svetstk.ru/post/raznovidnosti-i-primenenie-infrakrasnyh-lamp.
  2. 10 различий мультиспектральной и гиперспектральной съемки [Электронный ресурс]. – URL: https://gisproxima.ru/10_razlichiy_multispektralnoy_i_giperspektralnoy_syemki.
  3. Спектральная сигнатура растительности [Электронный ресурс]. – URL: https://gisproxima.ru/spektralnaya_signatura_rastitelnosti.
  4. NDVI: Что Нужно Знать Фермеру для Анализа Вегетации [Электронный ресурс]. – URL: https://eos.com/ru/blog/ndvi-voprosy-i-otvety/.
  5. Что такое индекс NDVI и как он делает жизнь фермера проще [Электронный ресурс]. – URL: https://blog.onesoil.ai/ru/what-is-ndvi.
  6. Использование вегетационных индексов для анализа растительности [Электронный ресурс]. – URL: https://gisproxima.ru/ispolzovanie_vegetatsionnyh_indeksov.
  7. Stop Calling Them “False Color” Images! [Электронный ресурс]. – URL: https://christianready.com/2013/07/25/stop-calling-them-false-color-images/.
  8. Multispectral camera FS-50 series [Электронный ресурс]. – URL: https://www.figspec.com/en/h-col-365.html.
  9. Дрон DJI Mavic 3 Multispectral [Электронный ресурс]. – URL: https://www.drone.com.kz/products/drony/mavic_3_multispectral/.
  10. DJI Mavic 3M – User Manual v1.8 2024.08 [Электронный ресурс]. – URL: https://ag.dji.com/mavic-3-m/downloads
  11. Finger R., Swinton S. M., El Benni N., Walter A. Precision Farming at the Nexus of Agricultural Production and the Environment // Annual Review of Resource Economics. – 2019. – Vol. 11. – P. 313–335. – https://doi.org/10.1146/annurev-resource-100518-093929.
  12. Ali A., Hassan M., Kaul H.-P. Broad Scope of Site-Specific Crop Management and Specific Role of Remote Sensing Technologies Within It—A Review // Journal of Agronomy and Crop Science. – 2024. – Vol. 210. – e12732. – https://doi.org/10.1111/jac.12732.
  13. Zhang S., Wang X., Lin H., Dong Y., Qiang Z. A review of the application of UAV multispectral remote sensing technology in precision agriculture // Smart Agricultural Technology. – 2025. – Vol. 12. – 101406. – https://doi.org/10.1016/j.atech.2025.101406.
  14. Wang S., Jiang K., Li Y., Li T., An Z., Wang M., Zhang J., Liu C., Gao H., Yu L., Xu L., Cai W. From Field Sensing to Smart Spreading: A Comprehensive Review of Variable Rate Fertilization Technologies in Precision Agriculture // Sustainability. – 2026. – Vol. 18. – № 14. – 7095 p. – https://doi.org/10.3390/su18147095.
  15. Jensen H. G., Jacobsen L. B., Pedersen S. M. et al. Socioeconomic impact of widespread adoption of precision farming and controlled traffic systems in Denmark // Precision Agriculture. – 2012. – Vol. 13. – P. 661–677. – https://doi.org/10.1007/s11119-012-9276-3.
  16. Mohidem N. A., Che’Ya N. N., Juraimi A. S., Fazlil Ilahi W. F., Mohd Roslim M. H., Sulaiman N., Saberioon M., Mohd Noor N. How Can Unmanned Aerial Vehicles Be Used for Detecting Weeds in Agricultural Fields? // Agriculture. – 2021. – Vol. 11. – № 10. – 1004 p. – https://doi.org/10.3390/agriculture11101004 .
  17. Neupane K., Baysal-Gurel F. Automatic Identification and Monitoring of Plant Diseases Using Unmanned Aerial Vehicles: A Review // Remote Sensing. – 2021. – Vol. 13. – № 19. – 3841 p. – https://doi.org/10.3390/rs13193841 .
  18. Nguyen C., Sagan V., Skobalski J., Severo J. I. Early Detection of Wheat Yellow Rust Disease and Its Impact on Terminal Yield with Multi-Spectral UAV-Imagery // Remote Sensing. – 2023. – Vol. 15. – № 13. – 3301 p. – https://doi.org/10.3390/rs15133301.
  19. Portela F., Sousa J. J., Araújo-Paredes C., Peres E., Morais R., Pádua L. Monitoring the Progression of Downy Mildew on Vineyards Using Multi-Temporal Unmanned Aerial Vehicle Multispectral Data // Agronomy. – 2025. – Vol. 15. – № 4. – 934 p. – https://doi.org/10.3390/agronomy15040934.
  20. Liu Y., Fan Y., Yue J., Ma Y., Yang F., Fan J., Chen R., Bian M., Feng H. UAV-based remote sensing estimation of above-ground biomass in different crops: A review // International Journal of Applied Earth Observation and Geoinformation. – 2025. – Vol. 144. – 104938. – https://doi.org/10.1016/j.jag.2025.104938.
  21. Gade S. A., Madolli M. J., García-Caparrós P., Ullah H., Cha-um S., Datta A., Himanshu S. K. Advancements in UAV remote sensing for agricultural yield estimation: a systematic comprehensive review of platforms, sensors, and data analytics // Remote Sensing Applications: Society and Environment. – 2025. – Vol. 37. – 101418. – https://doi.org/10.1016/j.rsase.2024.101418.
  22. Lan J., Ban Q. The Farm-Level Economic and Environmental Benefits of Precision Agriculture Technology Adoption: A Meta-Analysis of Global Evidence // Sustainability. – 2025. – Vol. 17. – № 24. – 11223 p. – https://doi.org/10.3390/su172411223.
  23. Cai B., Shi F., Geremew B. A., Addis A. K., Abate M. C., Dessie W., Bayu T. Precision agriculture techniques for optimizing chemical fertilizer use and environmental sustainability: a systematic review // Frontiers in Agronomy. – 2025. – Vol. 7. – 1665444. – https://doi.org/10.3389/fagro.2025.1665444.