Drought is the meteorological phenomenon with the greatest impact on agriculture. Accordingly, drought forecasting is vital in lessening its associated negative impacts. Utilizing remote exploration in the agricultural sector allows for the collection of large amounts of quantitative data across a wide range of areas. In this study, we confirmed the applicability of drought assessment using the evaporative stress index (ESI) in major East Asian countries. The ESI is an indicator of agricultural drought that describes anomalies in actual/reference evapotranspiration (ET) ratios that are retrieved using remotely sensed inputs of land surface temperature (LST) and leaf area index (LAI). The ESI is available through SERVIR Global, a joint venture between the National Aeronautics and Space Administration (NASA) and the United States Agency for International Development (USAID). This study evaluated the performance of ESI in assessing drought events in South Korea. The evaluation of ESI is possible because of the availability of good statistical data. Comparing drought trends identified by ESI data from this study to actual drought conditions showed similar trends. Additionally, ESI reacted to the drought more quickly and with greater sensitivity than other drought indices. Our results confirmed that the ESI is advantageous for short and medium-term drought assessment compared to vegetation indices alone.

South Korea has experienced severe droughts and water scarcity problems that have influenced agriculture, food prices, and crop production in recent years. Traditionally, climate-based drought indices using point-based meteorological observations have been used to help quantify drought impacts on the vegetation in South Korea. However, these approaches have a limited spatial precision when mapping detailed vegetation stress caused by drought. For these reasons, the development of a drought index that provides detailed spatial-resolution information on drought-affected vegetation conditions is essential to improve the country’s drought monitoring capabilities, which are needed to help develop more effective adaptation and mitigation strategies. The objective of this study was to develop a satellite-based hybrid drought index called the vegetation drought response index for South Korea (VegDRI-SKorea) that could improve the spatial resolution of agricultural drought monitoring on a national scale. The VegDRI-SKorea was developed for South Korea, modifying the original VegDRI methodology (developed for the USA) by tailoring it to the available local data resources. The VegDRI-SKorea utilizes a classification and regression tree (CART) modelling approach that collectively analyses remote-sensing data (e.g. normalized difference vegetation index (NDVI)), climate-based drought indices (e.g. self-calibrated Palmer drought severity index (PDSI) and standardized precipitation index (SPI)), and biophysical variables (e.g. elevation and land cover) that influence the drought-related vegetation stress. This study evaluates the performance of the recently developed VegDRI-SKorea for severe and extreme drought events that occurred in South Korea in 2001, 2008, and 2012. The results demonstrated that the hybrid drought index improved the more spatially detailed drought patterns compared to the station-based drought indices and resulted in a better understanding of drought impacts on the vegetation conditions. The VegDRI-SKorea model is expected to contribute to the monitoring of drought conditions nationally. In addition, it will provide the necessary information on the spatial variations of those conditions to evaluate local and regional drought risk assessment across South Korea and assist local decision-makers in drought risk management.