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Drought Monitoring Using Vegetation Index Based on Satellite Image Data

Author(s): Joo-Heon Lee; Ho-Won Jang; Seul-Gi Baek; Hyeong-Won Cho

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Keywords: Drought; MODIS; NDVI; EVI; SPI; VSI

Abstract: Natural disaster is increasing day by day due to meteorological disasters such as global warming and climate changes. Among such natural disasters, drought is ranked at top. Because drought is progressed slowly as compared with other natural disasters, there may be ample time to react against drought. However, since damages by drought don’t be exposed immediately, it is difficult to establish countermeasures and to execute it. In this research, NDVI (Normalized Difference Vegetation Index) and EVI (Enhanced Vegetation Index) which can observe the changes in the vegetation were estimated by using image data from MODIS sensor which was loaded in the earth observing satellite Terra in order to investigate damages by the spatial agricultural drought through a satellite. The estimation result exhibited strong seasonal nature. Therefore, to supplement the seasonal nature of the obtained data, the VCI (Vegetation Condition Index) and VSIA (Vegetation Stress Index Anomaly) which are normalizing indices of EVI were calculated per each sub-basin by classifying land cover. Further, the representative drought index SPI (Standardized Precipitation Index) was calculated by utilizing monthly rainfall data from the rainfall gaging stations, and then VCI and VSIA were compared with historical drought events occurred in the Korean peninsula. Besides, spatial analysis was evaluated for the applicability and possibility to monitor the agricultural drought in the Korean Peninsula. It was found through the present research that VSIA which is a normalizing index of EVI could be effectively utilized in monitoring agricultural drought.


Year: 2016

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