Inundated areas, including lakes, streams, some wetlands, as well as episodically flooded areas, play important roles in many Earth system processes and provide a broad range of ecosystem services. In the meantime, they are being lost at alarming rates. However, present knowledge of the spatial and temporal dynamics of terrestrial inundation is limited. Existing surface water maps often disagree on the di stribution and extent of relatively stable water bodies, and wetlands and other episodically inundated areas that are more difficult to map are among the least accurate classes in many land cover products. Further, no existing national to global scale prod ucts provide near daily, sub - hectare details on terrestrial inundation, which are critical for fully characterizing the dynamics of many inundated areas. When completed in 2017, the constellations of the European Space Agency's (ESA) Sentinel - 1 and - 2 toge ther with Landsat - 8 will, for the first time, provide near daily global datasets at sub - hectare spatial resolutions. The primary goal of this study is to utilize this constellation of satellites to develop and demonstrate improved capability to monitor ter restrial inundation. We will develop automated algorithms suitable for inundation monitoring at the global scale using Landsat - 8/Sentinel - 2 (L8S2) optical data and Sentinel - 1 (S1) SAR data. These algorithms will be calibrated and tested extensively over study areas selected from different biomes, and will be used to generate near daily inundation products for temperate, subtropical, and tropical North America, including the United States and southern Canada. According to current launch schedules, we expec t to have the data necessary to generate these products for one full year (~2017 - 2018) through this project. Delays in the launch of one or more of these systems will result in less than near daily coverage but will not impede the overall project. This s tudy responds to the LCLUC NRA by maximizing "the utility of current and near - future remote sensing capabilities" to study terrestrial inundation, a highly dynamic phenomenon that needs to be characterized at sub - hectare resolutions on a near daily basis. It provides an "efficient use and seamless combination" of L8S2 optical data and S1 SAR data for understanding global inundation dynamics. Being fully automated, the developed algorithms can be implemented in an operational system to generate global, long - term inundation records. The products derived through this study will represent multi - order improvements over existing knowledge. This study will help develop techniques to rapidly incorporate NASA - ISRO's future NISAR data into an operational inundation mo nitoring framework, and will benefit multiple ongoing US federal efforts, including NASA's Arctic - Boreal Vulnerability Experiment, USGS's National Water Census (http://water.usgs.gov/watercensus/), EPA's efforts to clarify the definition of Waters of the U S under the Clean Water Act, and NOAA's Coastal Change Analysis Program.