MODIS olingan indekslar yordamida qurg'oqchilik monitoring va Google Earth Engine platformasi
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Keywords

Qurg'oqchilik monitoringi, Qurg'oqchilik indekslari, masofaviy Sensing, MODIS, Google Earth Engine, Turkiya

How to Cite

R.S.Ibragimov, & Xаsаnоvа Shohsаnаm Аxаd qizi. (2023). MODIS olingan indekslar yordamida qurg’oqchilik monitoring va Google Earth Engine platformasi. Journal of Universal Science Research, 1(5), 1071–1078. Retrieved from https://universalpublishings.com/index.php/jusr/article/view/868

Abstract

Qurg'oqchilik tez-tez kuzatiladigan tabiiy hodisalardan biridir yog'ingarchilik tanqisligidan kelib chiqadigan va ortib borayotgan xavf yuqori harorat ta'sirida evapotranspiratsiya. Masofadan fazoviy-vaqt taqsimotini tahlil qilish uchun sezuvchi indekslardan foydalaniladi qurg'oqchilik sharoitlarini aniqlash va qurg'oqchilikning og'irligini aniqlash. Bunda tadqiqot, biz qurg'oqchilikning fazoviy-vaqt taqsimotini tahlil qildik 2000 yil fevralidan 2019 yil yanvarigacha Turkiyadagi sharoit MODIS sun'iy yo'ldoshidan ishlab chiqarilgan turli xil qurg'oqchilik indekslari yordamida Google Earth Engine (GEE) platformasidagi ma'lumotlar. O'simliklar salomatligi Indeks (VHI), Normallashtirilgan ko'p tarmoqli qurg'oqchilik indeksi (NMDI) va Normallashtirilgan Qurg'oqchilik Indeksi (NDDI) xaritalarida tegishli yillarning turli yillari va oylari uchun mamlakat darajasi qurg'oqchilik sharoitlarini baholash uchun foydalanilgan. Vaqt seriyalari edi chuqur tahlil qilish uchun ba'zi aniq joylar uchun ham yaratilgan 20 yillik davrda qurg'oqchilik sharoitlari. Bizning natijalar shuni ko'rsatadi MODISdan olingan qurg'oqchilik indekslari foydali geofazoni ta'minlaydi mamlakat darajasidagi qurg'oqchilik sharoitlarini baholash uchun ma'lumot. Bundan tashqari, GEE platformasi erishish uchun juda qulay va tezkor vositadir tegishli sun'iy yo'ldosh tasvirlari va masofadan zondlash tahlilini o'tkazish katta va uzoq muddatli sana samarali. Geospatial katta ma'lumotlar bo'lishi mumkin uchungina emas, balki ushbu platformada muvaffaqiyatli kirish va qayta ishlash qurg'oqchilik monitoringi, balki boshqa atrof-muhit uchun ham monitoring ilovalari.

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References

Hayes, M., Svoboda, M., Wardlow, B., Anderson, M., & Kogan, F. (2012). Drought Monitoring Historical and Current Perspectives. Drought Mitigation Center Faculty Publications,94.

Akbaş, A. (2014). Turkiye Uzerindeki Onemli Kurak Yıllar. Coğrafi Bilimler Dergisi,12(2), 101-118.

Kogan, F. N. (1995a). Droughts of the Late 1980s in the United States as Derived from NOAA Polar-Orbiting Satellite Data. Bulletin of the American Meteorological Society,76(5), 655-668. doi:10.1175/1520- 0477(1995)0762.0.co;2

Gu, Y., Brown, J. F., Verdin, J. P., & Wardlow, B. (2007). A five-year analysis of MODIS NDVI and NDWI for grassland drought assessment over the central Great Plains of the United States. Geophysical Research Letters,34(6). doi:10.1029/2006gl029127

Wang, L., & Qu, J. J. (2007). NMDI: A normalized multi-band drought index for monitoring soil and vegetation moisture with satellite remote sensing. Geophysical Research Letters,34(20). doi:10.1029/2007gl031021

Mutanga, O., & Kumar, L. (2019). Google Earth Engine Applications. Remote Sensing,11(5), 591. doi:10.3390/rs11050591

Google Earth Engine, May 15, 2019. Redvived from https://earthengine.google.com/

Molavizadeh, N., Sertel, E., & Demirel, H. (2016). Drought Conditions in Turkey Between 2004 and 2013 Via Drought Indices Derived from Remotely Sensed Data. Energy, Transportation and Global Warming Green Energy and Technology,113-121. doi:10.1007/978-3-319- 30127-3_10

Vermote, E. (2015). MOD09A1 MODIS/Terra Surface Reflectance 8- Day L3 Global 500m SIN Grid V006 [Data set]. NASA EOSDIS Land Processes DAAC. doi: 10.5067/MODIS/MOD09A1.006

Du, T. L., Bui, D. D., Nguyen, M. D., & Lee, H. (2018). Satellite- Based, Multi-Indices for Evaluation of Agricultural Droughts in a Highly Dynamic Tropical Catchment, Central Vietnam. Water,10(5), 659. doi:10.3390/w10050659

Khampeera, A., Yongchalermchai, C., & Techato, K. (2018). Drought Monitoring using Drought Indices and GIS Techniques in Kuan Kreng Peat Swamp, Southern Thailand. Walailak J Sci & Tech,15(5), 357- 370.

Kogan, F. (1995b). Application of vegetation index and brightness temperature for drought detection. Advances in Space Research,15(11), 91-100. doi:10.1016/0273-1177(95)00079-t

Wang, L., Qu, J. J., & Hao, X. (2008). Forest fire detection using the normalized multi-band drought index (NMDI) with satellite measurements. Agricultural and Forest Meteorology,148(11), 1767- 1776. doi:10.1016/j.agrformet.2008.06.005

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