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Probability assessment of vegetation vulnerability to drought based on remote sensing data
- Alamdarloo, Esmail Heydari, Manesh, Maliheh Behrang, Khosravi, Hassan
- Environmental monitoring and assessment 2018 v.190 no.12 pp. 702
- drought, moderate resolution imaging spectroradiometer, normalized difference vegetation index, probability, risk management, spatial data, surface temperature, topography, vegetation, Iran
- Drought is one of the important factors causing vegetation degradation. Determination of areas with vegetation more sensitive to drought can be effective in drought risk management. Considering the ability to describe vegetation conditions, vegetation health index (VHI) was used to determine the probability of vegetation vulnerability to drought and to provide the map of Iran showing sensitive areas to drought. This study tries to express the probability of vegetation vulnerability to drought in four main climatic classes including hyper-arid, arid, semi-arid and semi-humid, and humid in Iran. Temperature condition index (TCI) and vegetation condition index (VCI) were calculated using land surface temperature (LST) derived from the MOD11A2 product and normalized different vegetation index (NDVI) obtained from MOD13A2 product, MODIS sensor. Combining these two indices, VHI was calculated for late of March, April, May, and June during 2000–2017. VHI was classified into five classes representing the drought intensity. Then, the probability of occurrence (%) of each class was calculated and multiplied with weight of each class, varying from 0 to 40 based on drought intensity. Finally, probability of vegetation vulnerability index (PVVI) was calculated by summing of the values obtained for each class. The results showed that PVVI was higher in arid and hyper-arid areas than that in other areas in the four studied periods. The highest mean values of PVVI in humid as well as semi-arid and semi-humid classes were found in April as 59.87 and 62.4, respectively, while the highest mean values of PVVI in arid and hyper-arid classes were observed in May as 70.98 and 68.13, respectively. In total, our results showed that PVVI is affected by different climatic and topographic conditions, and it suggested that this index be used to determine the probability of vegetation vulnerability.