Identification of Vegetation-Vulnerable Areas to Drought Using Remote Sensing (Case study: Boushehr Province)

Document Type : Research Paper


1 university of Tehran

2 Assis. Prof. of Faculty of Natural Resources and Earth Sciences, university of Kashan, Iran

3 Faculty of Natural Resources, university of Tehran. Iran


The complexity of drought phenomenon hinders our full understanding of its impact. Field sampling, Geographic Information Systems, SPI and NDVI, EVI and SAVI indices derived from 16-day interval MODIS images during 2000-2015 were used to better understand the effects of drought on vegetation In recent study, ground true map was prepared by sampling and field surveys and vegetation cover data was obtained from 32 sampling units in 320 plots over the entire study area. Then, the correlation between field sampling data and vegetation indices was estimated and vegetation cover models were produced for different indices. In this study, precipitation data of 14 stations within and around the study area were used and SPI was calculated at the same time scales with the vegetation indices to study the effect of drought on vegetation. The results showed that NDVI has had the highest correlation coefficient (R2=0.56) amongst the indices so it was selected for vegetation cover percentage mapping. Investigating NDVI rates and drought index in different temporal periods, 9-month SPI was found to have the best correlation with NDVI. On the basis of SPI analysis, it was found that the study area had the most severe drought in 2012 and the best wet condition in 2004. The similar trend was observed in NDVI. The comparison of classified images between 2004 and 2012 (with 42 % changes in poor vegetation) indicates the effect of drought on vegetation in the study area.


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Volume 71, Issue 2
September 2018
Pages 341-354
  • Receive Date: 18 April 2017
  • Revise Date: 26 February 2018
  • Accept Date: 06 February 2018
  • First Publish Date: 23 August 2018