MONITORING OF AGRICULTURAL AND PASTURE LANDS IN BUKHARA REGION USING INNOVATIVE TECHNOLOGIES
Abstract
Agricultural and pasture lands in Uzbekistan, particularly in the Bukhara region, are increasingly affected by climate variability, soil degradation, salinity, and inefficient water management. These challenges require advanced and innovative monitoring technologies to ensure sustainable land use and maximize productivity. Modern tools such as Geographic Information Systems (GIS), satellite-based remote sensing, UAV (drone) surveying, and automated NDVI (Normalized Difference Vegetation Index) have become essential components of land monitoring worldwide.
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References
Xudoyberdiyev X. Yer monitoringi asoslari [Fundamentals of Land Monitoring]. Toshkent.
Jo‘rayev B. Qishloq xo‘jaligi yerlari tahlili bo‘yicha ilmiy izlanishlar [Scientific Research on Agricultural Land Analysis].
Yo‘ldoshev O. GIS texnologiyalarining amaliy qo‘llanilishi [Practical Application of GIS Technologies].
Karimov S. NDVI ko‘rsatkichlari orqali yer degradatsiyasini baholash [Land Degradation Assessment via NDVI Indicators].
Abduvaliyev A. Masofaviy zondlash va geodeziya asoslari [Basics of Remote Sensing and Geodesy].
Thenkabail, P. S. (Ed.). (2015). Remote Sensing Handbook (Three Volume Set). CRC Press. (Highly cited global reference on remote sensing applications).
Lillesand, T., Kiefer, R. W., & Chipman, J. (2015). Remote Sensing and Image Interpretation (7th ed.). Wiley. (Foundational textbook, high h-index authors).
Huete, A., Didan, K., Miura, T., Rodriguez, E. P., Gao, X., & Ferreira, L. G. (2002). Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote Sensing of Environment, 83(1-2), 195-213. (Seminal paper on vegetation indices, highly cited).
Gómez, C., White, J. C., & Wulder, M. A. (2016). Optical remotely sensed time series data for land cover classification: A review. ISPRS Journal of Photogrammetry and Remote Sensing, 116, 55-72. (Key review on time-series analysis for monitoring).
Pervez, M. S., & Brown, J. F. (2010). Mapping irrigated lands at 250-m scale by merging MODIS data and national agricultural statistics. Remote Sensing, 2(10), 2388-2412. (Relevant study for irrigation monitoring in agricultural regions).