پایش تطبیقی خشکسالی با رویکرد تلفیقی داده‌های زمینی و فناوری سنجش از دور

Arkhi, S., Barzegar, S.M., Emadaldin, S. (2022).Investigating the efficiency of indices derived from remote sensing technology VCI, TCI and VHI in drought assessment with MODIS images (Case study: central regions of Iran).Geography and Environmental Hazards, 11(3), 189-224.https://doi.org/22067/geoeh.2021.72253.1102 (In Persian)

Bhattarai, A., Timilsina, S. , Ayer, S. , Paudel, G. and Maharjan, M. (2024). Evaluation of Drought in Gandaki River Basin of Nepal. Journal of Drought and Climate change Research, 2(2), 1-26. doi: https://doi.org/22077/jdc.2023.6865.1046

Chen, D., Hu, H., Liao, C., Ye,J., Bao,W., Mo,J., Wu, Y., Dong, T., Fan, H., Pei,J. (2023). Crop NDVI time series construction by fusing Sentinel-1, Sentinel-2, and environmental data with an ensemble-based framework. Computers and Electronics in Agriculture, Volume 215, 108388. https://doi.org/1016/j.compag.2023.108388

Du, L., Tian, Q., Yu, T., Meng, Q., Jancso, T., Udvardy, P., Huang, Y. (2013). A comprehensive drought monitoring method integrating MODIS and TRMM data. International Journal of Applied Earth Observation and geoinformation. Volume 23, Pages 245-253,ISSN 1569-8432. https://doi.org/1016/j.jag.2012.09.010

Dutta, D., Kundu, A., Patel, N.R., Saha, S.K., & Siddiqui, A.R., (2015). Assessment of agricultural drought in Rajasthan (India) using remote sensing derived Vegetation Condition Index (VCI) and Standardized Precipitation Index (SPI). J. Remote Sens. Sp. Sci. 18(1), 53–63; Elsevier. https://doi.org/10.1016/j.ejrs.2015.03.006

Fakhar, M. S. and Nazari, B. (2024). Monitoring and Assessing Spatial and Temporal Characteristics of Drought in Iran Using Remote Sensing. Journal of Drought and Climate change Research, 2(1), 39-58. https://doi.org/22077/jdcr.2024.7011.1050. (In Persian)

Ramezani Etedali, H. and Koohi, S. (2025). Investigating the impact of climate change on the aridity in Iran with population exposure approach. Journal of Drought and Climate change Research, 3(1), 17-38. https://doi.org/22077/jdcr.2024.8258.1079. (In Persian)

Hosseini, N., Ghorbanpour, M. & Mostafavi, H. (2024). Habitat potential modelling and the effect of climate change on the current and future distribution of three Thymus species in Iran using MaxEnt. Sci Rep. 14, 3641. https://doi.org/1038/s41598-024-53405-5. (In Persian)

Huete, A. R., 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. https://doi.org/1016/S0034-4257(02)00096-2

Huffman, G. J., Bolvin, D. T., Nelkin, E. J., Wolff, D. B., Adler, R. F., Gu, G., Stocker, E. F. (2007). The TRMM Multisatellite Precipitation Analysis (TMPA): Quasi-global, multiyear, combined-sensor precipitation estimates at fine scales. Journal of Hydrometeorology, 8(1), 38-55. https://doi.org/https://doi.org/1175/JHM560.1

Kogan, F. N. (1995). Application of vegetation index and brightness temperature for drought detection. Advances in Space Research, 15(11), 91-100. https://doi.org/1016/0273-1177(95)00079-T

Kogan, F. N. (1997). Global drought watch from space. Bulletin of the American Meteorological Society, 78(4), 621-636.https://doi.org/1175/1520-0477(1997)078%3C0621:GDWFS%3E2.0.CO;2

McKee, T.B., Doesken, N.J. and Kleist, J. 1993. The Relationship of Drought Frequency and Duration to Time Scales. 8th Conference on Applied Climatology, Anaheim, 17-22 January 1993, 179-184.

Mirmousavi, S.H., Karimi, H. (2013).Effect of drought on vegetation using MODIS sensor images, case: Kurdistan Province.Geography and Development, 11(31), 57-76. https://doi.org/22111/gdij.2013.794. (In Persian)

Moezanzadeh, R., Arshad, S., Ghahraman, B., Davari, K. (2012). Drought monitoring in non-irrigated crops using remote sensing techniques. Quarterly Journal of Water and Irrigation Management, Volume: 2, Issue: 2.P1-14.https://doi.org/22059/jwim.2013.30339. (In Persian)

Owe, M., de Jeu, R. A. M., & Holmes, T. R. H. (2008). Multi-Sensor Historical Climatology of Satellite-Derived Global Land Surface Moisture. Journal of Geophysical Research, 113, Article F01002. https://doi.org/1029/2007JF000769

Pokhrel, Y., Felfelani, F., Satoh, Y., Boulange, J., Burek, P., Gädeke, A., & Wada, Y. (2021). Global terrestrial water storage and drought severity under climate change. Nature Climate Change, 11(3), 226-233. https://doi.org/1038/s41558-020-00972-w

Rhee, J., Im, J., & Carbone, G. J. (2010). Monitoring agricultural drought for arid and humid regions using multi-sensor remote sensing data. Remote Sensing of Environment, 114(12), 2875-2887. https://doi.org/10.1016/j.rse.2010.07.005

Rodell, M., Houser, P. R., Jambor, U., Gottschalck, J., Mitchell, K., Meng, C.-J., Toll, D. (2004). The global land data assimilation system. Bulletin of the American Meteorological Society, 85(3), 381–394. https://doi.org/1175/BAMS-85-3-381

Rostami, A., Bazaneh, M., Raeini M. (2017).Spatial and temporal monitoring of agricultural drought using MODIS sensor images and remote sensing technology (case study: East Azerbaijan province).Soil and Water Science. Volume 27. Number 3. Pages 213-226. https://water-soil.tabrizu.ac.ir/article_6228.html. (In Persian)

Seiler, R. A., Kogan, F., Sullivan, J. (1998). AVHRR-based vegetation and temperature condition indices for drought detection in Argentina. Advances in Space Research, 21(3), 481-484. https://doi.org/1016/S0273-1177(97)00884-3

Shamsi pur, A.A., Alavi panah, S.A., Mohammadi, H. (2010). Efficiency of vegetation and thermal indices of NOAA-AVHRR satellite in ecological drought analysis of Kashan region.Iranian Rangeland and Desert Research, 445-465. https://ijrdr.areeo.ac.ir/article_102940.html?lang=en. (In Persian)

Siasar, H, Mohammad Rezapour, U, Khodamoradpour, M. (2024).'Drought monitoring using MODIS sensor data and comparison with SPI meteorological index in short-term periods, case study: Golestan province', Journal of Geography and Development, 22(74), pp. 166-186. https://doi.org/10.22111/gdij.2024.8175. (In Persian)

Vicente-Serrano, S.M., Beguería, S., & López-Moreno, J.I. (2010). A multiscalar drought index sensitive to global warming: the standardized precipitation evapotranspiration index. Journal of Climate, 23(7), 1696-1718. https://doi.org/1175/2009JCLI2909.1

Wan, Z., Zhang, Y., Zhang, Q., & Li, Z. L. (2002). Validation of the land-surface temperature products retrieved from Terra Moderate Resolution Imaging Spectroradiometer data. Remote Sensing of Environment, 83(1-2), 163-180. https://doi.org/1016/S0034-4257(02)00093-7

Wang, Jl., Yu, Yh. (2021). Comprehensive drought monitoring in Yunnan Province, China using multisource remote sensing data. J. Mt. Sci. 18, 1537–1549. org/10.1007/s11629-020-6333-7

Zhang, A., Jia, G. (2013). Monitoring meteorological drought in semiarid regions using multi-sensor microwave remote sensing data, Remote Sensing of Environment, Volume134,12-23. https://doi.org/1016/j.rse.2013.02.023

Zhao, X., Xia, H., Pan, L., Song, H., Niu, W., Wang, R., Li, R., Bian, X., Guo, Y., & Qin, Y. (2021). Drought Monitoring over Yellow River Basin from 2003–2019 Using Reconstructed MODIS Land Surface Temperature in Google Earth Engine. Remote Sensing, 13(18), 3748. https://doi.org/3390/rs13183748