Drought Monitoring Using MODIS Land Surface Temperature and Normalized Difference Vegetation Index Products in Semi-Arid Areas of Iran

Document Type : Research and Full Length Article


1 Assistant Professor, Department of Ecological Engineering, Faculty of Natural Resources, University of Jiroft, Kerman, Iran

2 Assistant Professor, Department of Geography, Faculty of Literature and Humanities, University of Jiroft, Kerman, Iran.

3 Ph.D Candidate of Combating Desertification, Department of Natural Resources Engineering, Faculty of Agriculture and Natural Resources, University of Hormozgan, Iran

4 Ph.D Candidate of Combating Desertification, Department of Arid and Mountainous Regions Reclamation, Faculty of Natural Resources, University of Tehran, Iran.


Reduction in vegetation cover and increasing land surface temperature are the most important consequences of drought which leads to land degradation. Therefore, the evaluation of drought effects on vegetation cover and its relationship with land surface temperature is very important. To that end, the objective of this study was to evaluate the relationship among vegetation cover, drought and land surface temperature in the north-west of Iran during 2001-2014. The annual (12 months) Standardized Precipitation Index (SPI) was calculated using monthly precipitation time series from 26 meteorological stations in the study area. Then, the interpolated maps of drought were produced using the Kriging method in the GIS environment. The Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) index were calculated from 2001-2014 using MODIS satellite images. Then, the Pearson correlation coefficient (R) was calculated to investigate the relationship among NDVI, LST and SPI. According to the results, the changes trend of mean NDVI was similar to drought trends over the years (2001-2014) and the NDVI values have experienced its greatest reduction in 2008 (NDVI=0.087). The results also showed that LST values had a significant inverse relationship with SPI and NDVI indices (P<0.05). So, Land Surface Temperature (LST) was the highest (LST=22.3) where SPI and NDVI were the lowest (SPI=0.04 and NDVI=0.087) and there was the most severe drought in these conditions. Therefore, mean NDVI and LST could be suitable alternatives for climate indicators in the monitoring and evaluation of drought events in semi-arid areas.


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