Identifying Drought Classes in Northwest Syria Using MODIS Satellite Image Spectral Indices EVI, LAI, TVI

(Suzan Fathe Karmok , Ahmad Al haj Ahmad and Eyad Ahmad Alkhaled )

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Abstract

Drought monitoring and determining its impact on vegetation cover has become easier due to the emergence of modern technologies, such as remote sensing which are comprehensive, cost and efforts effective compared to traditional methods. The study aimed to use the MODIS image products, Enhanced Vegetation Index (EVI), Leaf Area Index (LAI), Land Surface Temperature (LST) to determine drought classes in northwest Syria for the period from 2001-2016 in relation to agriculture throughout the calculation of the thermal vegetation index (TVI). The results showed the possibility of using spatial data to study environmental phenomena in addition to their ability to allocate the spatial distribution of these phenomena. The results indicated that the year 2003 was the least affected by drought, while 2016 was the driest. The percentage of areas affected by very dry drought class were 39.42% , and 88.26% of the total examined area for these years, respectively. The correlation coefficient of precipitation with EVI, LAI was 0.57 and 0.59, respectively indicating an insignificant positive relationship. Meawhile, the coefficient of correlation with TVI recorded a significant negative mean value of - 0.65 at 0.05 significance level. This indicates that TVI index is more feasible and efficient than LAI and EVI in Defining drought severity and its spatial distribution. Key words: Agricultural drought, Vegetation cover.
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