Creatura Inc. (Headquarters: Chuo-ku, Tokyo; CEO: Michiyasu Hattori; hereinafter "Creatura"), a climate tech company, has announced new research findings in the peer-reviewed academic journal "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS)," which has a high citation record in the field of satellite Earth observation. This research demonstrates that an AI framework integrating meteorological and topographical data with satellite imagery can significantly improve the accuracy of surface water detection in rice paddies. According to the research, it was confirmed that surface water detection performance could be improved more than twofold compared to conventional methods, even under conditions with thick and dense crop cover. Alexis Declaro, Head of Data Science & GIS at the company, stated: "The key is not which satellite data is best on its own, but to reproduce what is happening on the ground by combining multiple elements. We hope this research will serve as an opportunity to reconsider the premise of SAR*1 dependency in rice paddy water management monitoring and to re-evaluate the optimal use of optical data according to its application and context." Features of this Framework (Figure 1) Overview of the framework proposed in this research In conditions where rice plants have fully grown, it has been difficult to determine the presence or absence of water using conventional satellite analysis, forcing reliance on estimation. This research has shown that by integrating meteorological and topographical data in addition to satellite imagery, it is possible to detect inundation events that were previously difficult to detect with high accuracy. The feature of this framework is not merely data integration, but rather the explicit handling of how each input data reflects the physical conditions on the ground. It is based on observable elements such as the interaction between vegetation and surface water, atmospheric and soil mo