Assessment of Drought Severity Using Vegetation Temperature Condition Index (VTCI) and Terra/MODIS Satellite Data in Rangelands of Markazi Province, Iran
الموضوعات :
Ali Akbar Damavandi
1
,
Mohammad Rahimi
2
,
Mohammad Reza Yazdani
3
,
Ali Akbar Noroozi
4
1 - ITVHE Academic Member, Ph.D. Student in Combat Desertification, Semnan University, Iran
2 - Assistant Prof. Semnan university,Semnan,Iran
3 - Assistant Prof. Semnan university, Semnan,Iran
4 - Assistant Prof .soil conservation and Watershed management research Institute, Tehran.Iran
الکلمات المفتاحية: drought, Rangelands, Remote Sensing, MODIS, VTCI,
ملخص المقالة :
The drought caused a series of effects on many sectors of economy, especially natural resources. During two last decades, Iran has suffered from several severe to extreme agricultural droughts which caused significant decreases in rangeland and agriculture yields. This paper discusses the detection of agricultural drought severity over the rangelands of Markazi Province between 2000 and 2014 using remotely sensed data. Vegetation Temperature Condition Index (VTCI) is a near-real time drought assessment and monitoring approach which have been developed using Terra-MODIS normalized difference vegetation index (NDVI) and Land Surface Temperature (LST) products. VTCI is defined as the ratio of LST differences among pixels with a specific NDVI value in a sufficiently large study area. VTCI has capability of drought stress classification which therein lower VTCI is for drought and higher one for wet conditions. The ground-measured precipitation data from the synoptic stations of Markazi Province are used to validate the VTCI drought monitoring approach (11 stations). For this objective, after the calculation of Standardized Precipitation Index ) SPI) with different periods and VTCI month of July during 2000 to 2014 (warm and cold edges from NDVI and LST scatter gram extracted), linear regression analysis between VTCI (15 maps) and SPI 1, 3,6,9,12,18 months were surveyed and finally, the best map was extracted. Based on the statistical analysis, higher correlations were found for July 2006 (R2 =0.73 for warm edge and R2=0.86 for cold edge) and the best linear correlation was created for SPI-18 month in July. Results showed that within VTCI classified map, moderate and low drought classes constituted most area of studied region. Also, the results showed that VTCI is closely related not only to recent rainfall events but also to past rainfall amount (18 month) indicating that VTCI is a better and near-real time drought monitoring approach for rangelands.
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