Description
Studies have shown that globally, riverine and coastal floods are increasing in intensity and duration. In addition, the number of people living in flood-prone areas has increased substantially during the last two decades. Therefore, monitoring and predicting floods in support of early warning, response, and relief operations have become major foci for disaster management activities worldwide. Remote sensing observations from optical and synthetic aperture radar (SAR) sensors are routinely used for detecting and mapping flooding. Moreover, empirical methodologies developed using remote sensing observations of rainfall, terrain, soil moisture, and landcover, as well as weather modeling data, have been used for flood monitoring. Sophisticated and complex land hydrology and runoff routing models are also being used for mapping and predicting riverine and urban flooding.
NASA's Applied Remote Sensing Training Program (ARSET) has offered several trainings on flood monitoring based on optical and SAR observations in the past. This training focuses on developments and updates in flood monitoring tools and flood modeling techniques. Specifically, an overview of the Hydrological Modeling and Analysis Platform (HyMAP), a routing model used with NASA’s Land Information System (LIS), and examples of flood modeling cases are presented in this training.