Assessment of agricultural drought using MODIS derived FAO's agriculture stress index system (ASIS) over the Iran croplands

Document Type : Research Paper

Authors

1 Remote Sensing and GIS,Faculty of Geography, University of Tehran, Iran

2 Department of Geography and Urban Planning, Shahid Beheshti University, Tehran, Iran

3 FAO Sub-regional Office for Mesoamerica, Panama

Abstract

In Iran, the drought is one of the costliest natural disasters, which has devastating consequences for the food security of agricultural households. Drought monitoring characteristics are important for better understanding of the drought phases in mitigation planning. Various satellite-based drought indices and systems have been developed and applied at both the regional and global scales. Recently the remotely sensed agricultural stress index system (ASIS) based on imagery from the Advanced Very High Resolution Radiometer (AVHRR-NOAA) and Meteorological Operational Satellite (METOP) by the Global Information and Early Warning System (GIEWS) of FAO developed. It shows considerable potential for drought monitoring at the global scale. Vegetation Health Index (VHI), start and end of the crop season (SOS-EOS) are the main inputs of ASI S. While the GIEWS models use the METOP-AVHRR images (1984 at present), in this study, an attempt has been made to retrieve key ASI inputs from the Moderate Resolution Imaging Spectroradiometer (MODIS) to evaluate the ability of the MODIS ASIS for characterizing agricultural drought severity and explore the impacts of drought on crop production during growing season.
Comparing national and sub-national wheat and barley yields with the ASIS drought maps, demonstrated that the proposed approach could identify major historical droughts over the observed period (2002-2015) in Iran. We detected that the extreme severe drought occurred during the year 2007-2008 crop season, affecting approximately 64% of crop land.

Keywords

References

References 
 
Ababaei, B., H.R. Etedali, 2016. Water footprint assessment of main cereals in Iran. Agricultural Water      Management., 179;401-411.  Abbaspour, K.C., M. Faramarzi, S. Seyed Ghasemi, H .Yang, 2009. Assessing the impact of climate change     on water resources in Iran. Water Resour. Res, 45(10).  Golian, S., O .Mazdiyasni, A. AghaKouchak, 2015. Trends in meteorological and agricultural droughts in       Iran. Theor. Appl. Climatol, 119; 679-688. Hoolst, R.V., H .Eerens, D .Haesen, A .Royer, L. Bydekerke, O .Rojas, Y .Li, P .Racionzer, 2016. FAO’s       AVHRR-based Agricultural Stress Index System (ASIS) for global drought monitoring, Int. J.       Remote Sens, 37(2); 418-439. Iranian Ministry of Agriculture- Jahad (MAJ), 2008. Agriculture Statistics: Volume 1, Field Crops (In       Farsi). Iranian Ministry of Agriculture-Jahad (MAJ),2015. A Statistical Overview of Field Crops Harvested       Area and Production in the Past 36 Years (In Farsi). Keshavarz, R., M. Vazifedoust, A .Alizadeh, 2014. Drought monitoring using a Soil Wetness Deficit Index       (SWDI) derived from MODIS satellite data. Agric. Water Manage, 132; 37– 45. Khoshkam, M., F. Rahimzadeh, 2009. Southwest Asia, Iran in State of the Climate in 2008. Bull. Amer.       Meteor. Soc, 90 (8);S1–S196. Kogan, F., 1995. Application of vegetation index and brightness temperature fordrought detection. Adv.       Space Res, 15 (11); 91–100. Kogan, F., 2002. World droughts in the new millennium from AVHRR-based vegetation health indices.       Eos. Trans. AGU, 83; 557–572. Kogan, F., B .Yang, W .Guo, P. Zhiyuan,, J. xianfeng, 2005. Modelling corn production in China using AVHRR-      based vegetation health indices. Int. J. Remote Sens, 26(11); 2325−2336. Kogan, F.N, 1997. Global drought watch from space. Bull. Am. Meteorol. Soc, 78; 621–636. Madani, K., A. AghaKouchak, A.  Mirchi ,2016. Iran’s Socio-economic Drought: Challenges of a Water-      Bankrupt Nation. Iranian Studies, 49(6); 997-1016. Modarres, R., A .Sarhadi, D.H.Burn ,2016. Changes of extreme drought and flood events in Iran. Glob.       Planet. Chang, 144;67–81. Morid, S., V. Smakhtin, M. Moghaddasi, 2006. Ccomparison of seven meteorological indices for       droughtmonitoring in Iran. Int. J. Climatol, 26;971–985. Pittman, K., C.M .Hansen, I .Becker-Reshef, V.P.O. Potapov, C. Justice, 2010. Estimating global cropland       extent with multi-year MODIS data. Remote Sens, 2; 1844-1863. Qu, J, 2015. Agricultural drought monitoring using MODIS based drought indices over the USA Corn       Belt. Int. J. Remote Sens, 36 (21);5403-5425. Rojas, O., A .Vrieling, F. Rembold, 2011. Assessing drought probability for agricultural areas in Africa       with coarse resolution remote sensing imagery. Remote Sens. Environ, 115 (2); 343–352. Rouse, J.W, R.H . Haas, J.A .Schell, D.W .Deering, J.C .Harlan, 1974. Monitoring the vernal advancements       and retrogradation of natural vegetation. In: NASA/GSFC. Final Report: 1–137pp. Safari Shad, M., A .Ildoromi, D. Akhzari, 2017. Drought Monitoring Using Vegetation Indices and       MODIS Data (Case Study: Isfahan Province, Iran). J. of Range. Sci, 7(2);148-159. 
41  Asgarzadeh et al. 
 
 
 
Salazar, L., F .Kogan, L.Roytman, 2007. Use of remote sensing data for estimation of winter wheat yield       in the United States. Int. J. Remote Sens, 28(17); 3795−3811. Seiler, R.A., F .Kogan, W .Guo, M.Vinocur, 2007. Seasonal and inter annual responses of the vegetation       and production of crops in Cordoba, Argentina assessed by AVHRR-derived vegetation indices. Adv.       Space Res, 39(1); 88−94. Singh, R.P., S .Roy, F. Kogan, 2003. Vegetation and temperature condition indices from NOAA AVHRR       data for drought monitoring over India. Int. J. Remote Sens, 24; 4393–4402. United States Department of Agriculture Foreign Agricultural Service (USDA), 2007-2009. World       Agricultural Production. https://www.pecad.fas.usda.gov. Wu, C., D .Peng, K. Soudani, L. Siebicke, C.M .Gough, M.A .Arain, M .Peichl, A .Gonsamo, S. Xu, B Fang,      Q. Ge ,2017. Land surface phenology derived from normalized difference vegetation index (NDVI)       at global FLUXNET sites. Agric. For. Meteorol. 233, 171–182. Zoljoodi, M., A. Didevarasl,. 2013. Evaluation of spatial-temporal variability of drought events in Iran       using palmer drought severity index and its principal factors (through 1951-2005). A.C.S, 3;193207. 
Desert
Volume 26, Issue 1
June 2021
Pages 29-41

Files

Share

How to cite

Statistics