Analysis of Performance of vegetation indices on agricultural drought using remote sensing technique in Karkheh basin

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Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:

Drought is one of the natural disasters that may occur in any climate. In recent decades, Iran has been affected by severe droughts and its harmful effects in various sectors, such as agriculture, environment and water resources of the country. Today, vegetation indices, which are obtained through remote sensing technology, are used to identify and analyze agricultural droughts. Accordingly, the aim of this study was to investigate the effectiveness of NDVI, EVI and VCI vegetation indices in agricultural drought identification and analysis in Karkheh basin. In order to calculate these indices, MODIS sensor Images (Terra satellite, MOD13A2 product) were used during the 2000-2017 statistical period. The accuracy of these profiles was evaluated with the ZSI index calculated at 11 meteorological stations located in Karkheh basin for the statistical period of 2000-2017. The results showed that the changes of NDVI, EVI and VCI in the studied stations were approximately the same during the statistical period. Based on NDVI, EVI and VCI values, the lowest and highest vegetation cover was observed in 2000, dehno station and 2001, helilan-seymareh station, respectively. The ZSI survey showed that most stations Faced with droughts from 2000 to 2008, and the most severe drought occurred in 2008, nazarabad station. Then, in order to validation of the results, the vegetation indices with ZSI index were evaluated. Pearson correlation between mean vegetation indices of NDVI, EVI and VCI with mean ZSI was 0.766, 0.725 and 0.776, respectively, and all vegetation indices with ZSI index are significant at 0.99% confidence level. As seen, according to the results, the ZSI index confirms the results of NDVI, EVI, and VCI. So, according to the results, there is no conformity of meteorological and agricultural droughts in all years, Therefore, in addition to other precipitation, climate variables should also be considered.

Language:
Persian
Published:
Iranian Journal of Remote Sencing & GIS, Volume:11 Issue: 4, 2020
Pages:
29 to 46
https://magiran.com/p2126481  
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