RESDEM, a tool for integrating temporal remote sensing data for use in hydrogeologic investigations

The dramatic increase in space-borne sensors over the past two decades is presenting unique opportunities for new and enhanced applications in various scientific disciplines. Using these data sets, hydrogeologists can now address and understand the partitioning of water systems on regional and global scales, yet such applications present mounting challenges in data retrieval, assimilation, and analysis for scientists attempting to process relevant large temporal remote sensing data sets (e.g., TRMM, SSM/I, AVHRR, MODIS, QuikSCAT, and AMSR-E). We describe solutions to these problems through the development of an interactive data language (IDL)-based computer program, the remote sensing data extraction model (RESDEM) for integrated processing and analysis of a suite of remote sensing data sets. RESDEM imports, calibrates, and georeferences scenes, and subsets global data sets for the purpose of extracting and verifying precipitation over areas and time periods of interest. Verification of precipitation events is accomplished by integrating other long-term satellite based data sets. The modules in RESDEM process data for cloud detection and others for detecting changes in soil moisture, vegetative water capacity and vegetation intensity following targeted precipitation events. Using the arid Sinai Peninsula (SP; area: 61,000km^2) and the Eastern Desert (ED; area: 220,000km^2) of Egypt as test sites, we demonstrate how RESDEM outputs (verified precipitation events) are now enabling regional scale applications of continuous (1998-2006) rainfall-runoff and groundwater recharge computations.