# Time varying spatial downscaling of satellite-based drought index > Chu H.J. URL kanonis: https://discover.unhas.ac.id/publications/pub_scopus_85115163988 Jurnal / Konferensi: Remote Sensing Tahun terbit: 2021 DOI: https://doi.org/10.3390/rs13183693 ISSN: 20724292 Kuartil SJR: Q1 Citations: 8 ## Authors - Chu H.J. ## Abstract Drought monitoring is essential to detect the presence of drought, and the comprehensive change of drought conditions on a regional or global scale. This study used satellite precipitation data from the Tropical Rainfall Measuring Mission (TRMM), but refined the data for drought monitoring in Java, Indonesia. Firstly, drought analysis was conducted to establish the standardized precipitation index (SPI) of TRMM data for different durations. Time varying SPI spatial downscaling was conducted by selecting the environmental variables, normalized difference vegetation index (NDVI), and land surface temperature (LST) that were highly correlated with precipitation because meteorological drought was associated with vegetation and land drought. This study used time-dependent spatial regression to build the relation among original SPI, auxiliary variables, i.e., NDVI and LST. Results indicated that spatial downscaling was better than nonspatial downscaling (overall RMSEs: 0.25 and 0.46 in spatial and nonspatial downscaling). Spatial downscaling was more suitable for heterogeneous SPI, particularly in the transition time (R: 0.863 and 0.137 in June 2019 for spatial and nonspatial models). The fine resolution (1 km) SPI can be composed of the environmental data. The fine-resolution SPI captured a similar trend of the original SPI. Furthermore, the detailed SPI maps can be used to understand the spatio-temporal pattern of drought severity. ## Keywords - Downscaling - Environmental science - Normalized Difference Vegetation Index - Precipitation - Climatology - Satellite - Spatial ecology - Common spatial pattern - Index (typography) - Remote sensing - Climate change - Meteorology - Geography - Computer science - Statistics - Mathematics - Geology - Ecology - Biology - Engineering - Aerospace engineering - World Wide Web - Oceanography --- Sumber: Discover Unhas — RIMS Universitas Hasanuddin. Saat mengutip, gunakan DOI bila tersedia atau URL kanonis di atas.