Drought Monitoring Using Vegetation Indices and MODIS Data (Case Study: Isfahan Province, Iran)

Document Type: Research and Full Length Article

Authors

1 PhD student, Department of Natural Resource, University of Sari, Iran.

2 Associate Professor, Dept of Range& Watershed management, Malayer University Iran.

3 Davoud Akhzari, Department of Watershed and Rangeland Management, Malayer University, Malayer 6571995863, Iran. E-mail: akhzari@malayeru.ac.ir, d_akhzari@yahoo.com

Abstract

Drought is a major problematic phenomenon mostly for semi-arid areas of Iran. During drought periods, reduction in vegetation levels causes such problems as soil erosion, surface runoff, flood risk, etc. Therefore, the assessment of drought effects on plant covers is the most important issue. This research was conducted in 2015 using the extracted vegetation indices from Moderate Resolution Imaging Spectroradiometer (MODIS) sensor data during 2000-2008. In Esfahan province, monthly rainfall data from 25 stations were used to derive the Standardized Precipitation Index (SPI) at 3 month scale, March to September. SPI was used to validate three index results in drought estimation. The result of calculating SPI showed that droughts occurred in 2000, 2001 and 2008. The result of Pearson correlations between SPI and Vegetation Indices showed thatthe highest correlation was related to VCI index and the lowest correlation was related to TCI index. The result of NDVI index in 2000, 2001 and 2008 indicated that the poor vegetation cover was increasingly occurred. Based on the results of this study, it can be concluded that the NDVI and VCI indices concerning MODIS sensor can be a good alternative for estimating the drought with respect to meteorological indices and consequently can give a better idea on drought conditions in the study area. It was shown that remote sensing data can be practically useful in analyzing the drought events in Esfahan province.

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Akbari, M., Toomanian, N., Droogers, P., Bastiaanssen, W., Gieske, A., 2007. Monitoring irrigation performance in Esfahan, Iran, using NOAA satellite imagery. Water Management., 88(1): 99–109.

Bedagh Jamali, J., Asiaii, M., Samadi, S., Javanmard, S., 2005. Drought management, Sokhan Gostar Publications, Mashhad, Iran, p.79. (In Persian)

Bhuiyan, C., Singh, R.P., Kogan, F.N., 2006. Monitoring Drought Dynamics in the Aravalli Region (India) Using Different Indices Based on Ground and Remote Sensing Data. Inter. Jour. of App. Earth Ob. Geo., 8(2): 289–302.

Brown, J. F., Wardlow, B. D., Tadesse, T., Hayes, M. J., and Reed, B. C., 2008. The Vegetation Drought Response Index (VegDRI): A new integrated approach for monitoring drought stress in vegetation. GISci. Rem. Sen., 45(1):16–46.

Chopra, P., 2006. Drought Risk Assessment Using Remote Sensing and GIS, a Case Study in Gujarat. M. Sc. Thesis. Dept. of Geo-information Science and Earth Observation, ITC, Netherlands, p.138.

Choudhary, S. S., Garg, P.K., and Ghosh, S.K., 2013. Drought Analysis Using Digital Image Processing & Meteorological Data. Inter. Jour. of Adv. Rem. Sen. and GIS., 2(1): 280-302.

Dabroska, K., Kogan, F., Ciolkos, A., Gruszczynska, M., and Kowalik, W., 2002. Modeling of crop growth conditions and crop yield in Poland using AVHRR-based indices. Inter. Jour. of Rem. Sen., 23(1): 1109–1123.

Damavandi, A.A., Rahimi, M.R., Yazdani,M.R., Noroozi, A.A., 2016. Assessment of Drought Severity Using Vegetation Temperature Condition Index (VTCI) and Terra/MODIS Satellite Data in Rangelands of Markazi Province, Iran. Jour. of Rangeland Sci., 6(1):33-42.

Mahmoud, A. M.A., Hasmadi, M., Alias, M.S. Alias, M. A. 2016. Rangeland Degradation Assessment in the South Slope of the Al-Jabal Al-Akhdar, Northeast Libya Using Remote Sensing Technology. Jour. of Rangeland Sci., 6(1):73-81.

Feng, G., 2014. ProQuest Dissertations and Theses; Thesis (M.S.)--Southern Illinois University at Carbondale, 135 p.

Gu, Y., Jesslyn, F. B., James, P. V., Brian, W., 2007. A five-year analysis of MODIS NDVI and NDWI for grassland drought assessment over the central Great Plains of the United States. Geophisi. Res. lett., 34(1):10-14.

Gu, Y., Eric, H., Brian, W., Jeffrey Basara, B., Jesslyn, F., James, P., 2008., Evaluation of MODIS NDVI and NDWI for vegetation drought monitoring using Oklahoma Mesonet soil moisture data. Geophisi. Res. lett., 35(1):15-25.

Gopinath, G., Ambili, G.K., Gregory, S. J., Anusha, C.K., 2014. Drought risk mapping of south-western state in the Indian peninsula a web based application. Jour. of. Environ. Manag., 34(1):1-7.

Jain, S., K., Keshri, R., Goswami, A., Sarkar, A., Chaudhry, A., 2009. Identification of drought-vulnerable areas using NOAA AVHRR data. Jour. of Rem. Sen., 30(1): 2653-2668.

Kogan, F. N., 1990. Remote sensing of weather impacts on vegetation in non-homogeneous areas. Inter. Jour. of Rem. Sen., 11(8): 1405-1419.

Kogan, F. N., 1995. Application of vegetation index and brightness temperature for drought detection. Adv. in Space Res., 15(11): 91-100

Koltunov, A., Ustin, S.L., Asner, G.P., Fung, I., 2009. Selective logging changes forest phenology in the Brazilian Amazon: evidence from MODIS image time series analysis. Rem. Sen. of Envir., 113(1): 2431– 2440.

Liu L. M., Hu Y., Yan J. J., Tan D. B., 2005. Analysis of parameters and their powers of MODIS drought monitoring model. Geoma. Info. Sci. Wuhan University., 30(1): 139-142

McKee, T.B., Doesken, N.J., Kleist, J., 1995. Drought monitoring with multiple time scales. In: Proceedings of the Nineth Conference on Applied Climatology. American Meteoro. Soci., 12(1): 233–236.

Mahyou, H., Karrou, M., Mimouni, J., Mrabet, R., El Mourid, M. 2010. Drought risk assessment in pasture arid Morocco through remote sensing. Afr. Jou. Environ.Sci. Technol.,4(12): 845-852.

Mu, Q., Kimball, J.S., McDowell, N.G., Running, S.W., 2013. A remotely sensed global terrestrial drought severity index. American Meteoro. Soci. 94(1): 83-98.

Orhan O.,  Ekercin, S. and  Celik, F., 2014. Use of Landsat Land Surface Temperature and Vegetation Indices for Monitoring Drought in the Salt Lake Basin Area, Turkey. Th. Scien World Jour., 2014(1): 1-11.

Patel, N. R., Anapashsha, R., Kumar, S., Saha, S. K., Dadhwa, V. K., 2009. Assessing potential of MODIS derived temperature/ vegetation condition index (TVDI) to infer soil moisture status. Inter. Jour. of Rem. Sen., 30(1): 23-39.

Rouse Jr, J., Haas, R., Schell, J. and Deering, D., 1974. Monitoring vegetation systems in the great plains with erts. NASA special publication, 351, 309.

Riebsame, W.E., Changnon, S.A., Karl, T.R., 1991. Drought and Natural Resource Management in the United States: Impacts and Implications of the 1987–89 Drought. Westview Press, Boulder, CO., p. 174.

Ramesh, P.S., Sudipa, R., Kogan, F., 2010. Vegetation and temperature condition indices from NOAA AVHRR data for drought monitoring over India. Inter. Jour. of Rem. Sen., 24(22): 4393-4402.

Singh, R. P., Roy, S., Kogan, F., 2003. Vegetation and temperature condition indices from NOAA AVHRR data for drought monitoring over India. Inter. Jour of. Rem. Sen., 24(22): 4393–4402.

Thiruvengadachari, S. and Gopalkrishna, H. R., 1993. An integrated PC environment for assessment of drought. Jour of. Re. Sen., 14(2): 3201-3208.

Thenkabail, P. S., Gamage, M. S. D. N., Smakhtin, V. U., 2003. The Use of Remote Sensing Data for Drought Assessment and Monitoring in Southwest Asia. IWMI Research Report., 85(1):45-76.

Zargar, A., Sadiq, R., Naser, B, & Khan, I. F., 2011. A review of drought indices. Environ. Rev. 19, 333–349.

Zarei, R., Sarajiana, M., Bazgeer, S., 2013. Monitoring Meteorological Drought in Iran Using Remote Sensing and Drought Indices. Desert., 18(1): 89-97.