The development of drought index that provides detailed-spatial-resolution drought information is essential for improving drought planning and preparedness. The objective of this study was to develop the concept of using satellite-based hybrid drought index called the Vegetation Drought Response Index in South Korea (VegDRI-SKorea) that could improve spatial resolution for monitoring local and regional drought. The VegDRI-SKorea was developed using the Classification And Regression Trees (CART) algorithm based on remote sensing data such as Normalized Difference Vegetation Index (NDVI) from MODIS satellite images, climate drought indices such as Self Calibrating Palmer Drought Severity Index (SC-PDSI) and Standardized Precipitation Index (SPI), and the biophysical data such as land cover, eco region, and soil available water capacity. A case study has been done for the 2012 drought to evaluate the VegDRI-SKorea model for South Korea. The VegDRI-SKorea represented the drought areas from the end of May and to the severe drought at the end of June. Results show that the integration of satellite imageries and various associated data allows us to get improved both spatially and temporally drought information using a data mining technique and get better understanding of drought condition. In addition, VegDRI-SKorea is expected to contribute to monitor the current drought condition for evaluating local and regional drought risk assessment and assisting drought-related decision making.