Spatial monitoring of agricultural drought by NDVI and LST time series using MODIS data (Case study: Markazi Province

Drought is a natural phenomenon that befalls nearly on all climatic zones worldwide. Because of especially susceptible to drought conditions and their low annual precipitation, the effects of this creeper and gentle phenomenon in arid and semi-arid regions are higher than other regions. For spatial analysis of drought in the present research, Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra satellite has been used Normalized Difference Vegetation Index (NDVI) and land surface temperature (LST) to calculate the Vegetation Condition Index (VCI), Temperature Condition Index (TCI) and finally vegetation health index (VHI) over Markazi Province, for the growth months from 2000 to 2014.Then drought severity classes extracted based on VHI maps into five classes:1-very high 2-High 3-moderate 4-slight and 5-no drought, and their variations surveyed with VHI time series. The survey of VCI and VHI time series showed that there are meaningful correlation between NDVI and LST. In certain years, they were corresponded to each other, while in other years they were one counter the other and their resultant determined the occurrence and severity of drought, which is reflected in the VHI. Based on results of this research, years of 2000 and 2001 had highest drought severity and years of 2004 and 2007 lowest. For growth months, May and August had highest and lowest respectively. With regard to drought classes, results consisted of: no drought (56%), slight (19%), moderate (15%), high (8%) and very high (2%).Comparison of this research results and National Meteorology Organization report demonstrated accuracy of remotely sensed index of VHI in monitoring of agricultural drought. Our study proves drought indices such as VCI, TCI and VHI can help to decision makers and planners by eliminate of point method weakness.