1. Arabi, Z. and badraghnejad, A., 2021. Correlation Analysis of Drought Time Series Based on Modis Satellite Images and Standardized Precipitation Climate Index (SPI) on the eastern slope of Zagros. Journal of Spatial Analysis Enviromental Hazarts, 8 (4), pp. 71-88.https://doi.org/10.22034/gp.2021.44939.2803 [In Persian].
2. Almamalachy, Y., 2017. Utilization of Remote Sensing in Drought Monitoring Over Iraq. PhD thesis, Portland State University, Portland.
3. Aydin, M., 2025. Evaluation of the Usability of the Rainfall Anomaly Index (RAI) Instead of the Standard Precipitation Index (SPI). Iranian Journal of Science and Technology, Transactions of Civil Engineering, 49(1), pp. 763-785. https://doi.org/10.1007/s40996-024-01516-4 .
4. Babaei, E., Asadi Zarch, M.A., Hosseini, S.Z. and Shahmoradi, S., 2025. Performance evaluation of composite remote sensing indices in drought assessment (case study: Chaharmahal and Bakhtiari Province, Iran). Journal of Natural Environmental Hazards, 14(43), pp. 155-180. https://doi.org/10.22111/jneh.2024.49797.2067. [In Persian].
5. Bhuiyan, C., Saha, A. K., Bandyopadhyay, N. and Kogan, F.N., 2017. Analyzing the impact of thermal stress on vegetation health and agricultural drought–a case study from Gujarat, India. GIScience & Remote Sensing, 54(5), pp. 678-699. https://doi.org/10.1080/15481603.2017.1309737
6. Chen, S., L. Zhang, Y. Zhang, M. and X. Liu., 2020. Evaluation of Tropical Rainfall Measuring Mission (TRMM) satellite precipitation products for drought monitoring over the middle and lower reaches of the Yangtze River Basin, China. Journal of Geographical Sciences, 30(1), pp. 53-67. https://doi.org/10.1007/s11442-020-1714-y
7. Degerli, S. and Turhan, E., 2025. An evaluation of spatiotemporal changes of meteorological drought in the Mediterranean sub-basins in Türkiye using discrepancy precipitation and standardized precipitation index. Natural Hazards, 121(2), pp. 2293-2322. https://ideas.repec.org/a/spr/nathaz/v121y2025i2d10.1007_s11069-024-06906-5.html
8. Guttman, N.B., 1999. Accepting the standardized precipitation index: a calculation algorithm. JAWRA Journal of the American Water Resources Association, 35(2), pp. 311-322. https://doi.org/10.1111/j.17521688.1999.tb03592.x
9. Hamzeh, S., Farahani, Z., Mahdavi, Sh., Chatrabgoun, A. and Gholamnia, M., 2017. Spatio-temporal monitoring of agricultural drought using remote sensing data: Case study of Markazi Province, Iran. Spatial Analysis of Environmental Hazards, 4(3), pp. 53-70. [In Persian].
10. Hao, C., Zhang, J. and Yao, F., (2015). Combination of multi-sensor remote sensing data for drought monitoring over Southwest China. International Journal of Applied Earth Observation and Geoinformation 35, pp. 270-283.
11. Hayes, M., Svoboda, M., Wall, N. and Widhalm, M., 2011. The Lincoln declaration on drought indices: universal meteorological drought index recommended. Bulletin of the American Meteorological Society, 92(4), pp.485-488. https://doi.org/10.1175/2010BAMS3103.1
12. Huffman, G.J., Bolvin, D.T., Nelkin, E.J. and Tan, J., 2015. Integrated multi-satellite retrievals for GPM (IMERG) technical documentation. Nasa/Gsfc Code, 612(47), 2019.
13. Huang, J., Zhuo, W., Li, Y., Huang, R., Sedano, F., Su, W. and Zhang, X., 2020. Comparison of three remotely sensed drought indices for assessing the impact of drought on winter wheat yield. International Journal of Digital Earth, 13 (4), 504–526. https://doi.org/10.1080/17538947.2018.1542040
14. Kogan, F.N., (1995). Application of vegetation index and brightness temperature for drought detection. Advances in space research, 15(11), pp. 91-100. https://doi.org/10.1016/0273-1177(95)00079-T
15. Kogan, F., B. Yang, G. Wei, P. and Xianfeng, J., 2005. Modelling corn production in China using AVHRR-based vegetation health indices. International Journal of Remote Sensing. 26(11), 2325–2336.
16. Li, M., Wang, P., Tansey, K., Sun, Y., Guo, F. and Zhou, J., 2025. Improved field-scale drought monitoring using MODIS and Sentinel-2 data for vegetation temperature condition index generation through a fusion framework. Computers and Electronics in Agriculture, 234, 110256.
17. Liu, Q., Zhang, S., Zhang, H., Bai, Y. and Zhang, J., 2020. Monitoring drought using composite drought indices based on remote sensing. Science of the Total Environment, 711, 134585.
18. McKee, T. B., Doesken, N. J. and Kleist, J., 1993. The relationship of drought frequency and duration to time scales, In Proceedings of the 8th Conference on Applied Climatology, Anaheim, 17(22), pp. 179-183.
19. Mtilatila, L., Bronstert, A., Bürger, G. and Vormoor, K., 2020. Meteorological and hydrological drought assessment in Lake Malawi and Shire River basins (1970–2013). Hydrological Sciences Journal, 65(16), pp.2750-2764. https://doi.org/10.1080/02626667.2020.1837384
20. Nawabi, N., Maghdesi, M. and Ganji, N., 2019. Assessment of agricultural drought monitoring using various indices based on ground and remote sensing data: Case study of Lake Urmia watershed. Journal of Watershed Engineering and Management, 13(1), pp. 1–12. [in Persian].
21. Salimi, M., Sanaeinezhad, S, H., Sepehr, A. and Sabet, L., 2018. Drought monitoring based on satellite index (SDI) and TRMM data. (Case Study; Khorasan Razavi province. Nivar, 42(102), pp. 19–30. [in Persian].
22. Tafi, Sh., Baladi, A., Soltani, A. and Pighan, Kh., 2021.Comparison and Evaluation of Estimating Reference Evapotranspiration Methods in Three General Categories Based onTemperature, Radiation and Mass Transfer (Case Study: Lorestan Province). Nivar, 44(110), pp. 107-120. [in Persian].
23. Vahidi, S., Amini, AS. and Hatamzadeh, V., 2023. Remote Sensing Indexes Assessment for Drought Monitoring Using Sentinel Satellite Imagery: A Case Study from Natanz County, Iran. Asian Journal of Geographical Research, 6(1), pp. 35-43.https://doi.org/10.9734/ajgr/2023/v6i1175
24. Wei, W., Zhang, J., Zhou, L., Xie, B., Zhou, J. and Li, C., 2021. Comparative evaluation of drought indices for monitoring drought based on remote sensing data. Environmental Science and Pollution Research, 28 (16), pp. 20408–20425. https://doi.org/10.1080/01431160500034235
25. Wilhite, D., 2000. Chapter 1. Drought as a natural hazard: concepts and definitions. In: Donald A. Wilhite (Ed.), Drought Mitigation Center Faculty, a global assessment. Vol. I. London (UK): Routledge; pp. 3–18.
26. Zhang, L., Jiao, W., Zhang, H., Huang, C. and Tong, Q., 2017. Studying drought phenomena in the continental United States in 2011 and 2012 using various drought indices. Remote Sensing of Environment, 190, pp. 96–106. https://doi.org/10.1016/j.rse.2016.12.010
27. Zhang, Y., Liu, X., Jiao, W., Zeng, X., Xing, X., Zhang, L. and Hong, Y., 2021. Drought monitoring based on a new combined remote sensing index across the transitional area between humid and arid regions in China. Atmospheric Research, 264, pp. 105850. https://doi.org/10.1016/j.atmosres.2021.105850
28. Zhao, X., Xia, H., Liu, B. and Jiao, W., 2022. Spatiotemporal comparison of drought in Shaanxi–Gansu–Ningxia from 2003 to 2020 using various drought indices in Google Earth Engine. Remote Sensing, 14, pp. 1570. https://doi.org/10.3390/rs14071570
29. Zhong, S., Sun, Z. and Di, L., 2021. Characteristics of vegetation response to drought in the CONUS based on long-term remote sensing and meteorological data. Ecological Indicators, 127, pp. 107767. https://doi.org/10.1016/j.atmosres.2021.105850