Java Island is the center of Indonesia's economic, government and tourism activities. Drought is a disaster that causes severe consequences without water supplies. Drought monitoring can help us to determine drought conditions and to prevent significant losses and severe impacts of the catastrophe. This study used precipitation data in 2015-2019 from Tropical Rainfall Measuring Mission (TRMM) and considered the Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI) from Sentinel-3 Level-2 in 2018 - 2019. Standardized Drought Analysis is conducted to establish the Standardized Precipitation Index (SPI) for different timescales (SPI 3, SPI 6, and SPI 9). Furthermore, composite drought analysis was used to determine the correlation between NDVI, LST, and SPI. Moreover, the estimation model is derived by Multivariate Linear Regression (MLR) and Geographically Weighted Regression (GWR). This study found that the GWR generates a better model than MLR because the GWR has a higher coefficient of determination for every month of each time scale. Besides, the standard deviation in GWR generates the same pattern as the observation model. The fine-resolution SPI (1 km) was composed of Sentinel-3 SLSTR NDVI and LST and matched the original SPI trend with a 27.75 km resolution. Furthermore, the most drought season happened in 2019, especially in November 2019, and the most drought location occurred in Central Java.

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