A significant mechanism for wildland fire spread is ignition by embers lofted ahead of a flaming front (fire spotting). Little is known about ember production, transport and subsequent ignition of new fuel, despite the significant threat posed from flame spotting at wildland-urban intermixes and during intense burns. This is significant because ember production and subsequent fire spotting ignition data are needed for fire models used to inform fire management decisions. In this effort, ember production rates, sizes, velocities and temperatures will be determined using high-speed and infrared cameras. Visible and infrared images will be obtained and particle tracking software will be used to extract the ember data. Measurements will be collected for multiple vegetation and structural types, sizes, moisture contents, fire intensities, and wind speeds. This breadth of testing is enabled by experiments being performed at multiple scales ranging from the laboratory to prescribed burns. This will enable correlations between ember data from prescribed burns and more extensive measurements within the laboratory. Key parameters controlling ember production will be statistically determined from laboratory and field measurements. Correlations and data determined in this study will be used to implement an ember transport algorithm within a numerical wind modeling framework (WindNinja) and shared with the fire community. The algorithm will simulate ember transport as a function of wind speed, direction and ember size, shape and density. WindNinja is currently used throughout the world to simulate surface wind flow in support of fire behavior simulations. The coupled experimental and computational approach will provide essential data for modelling and wildland fire management, establish a methodology for multi-scale fire research, and provide a validated ember transport algorithm to increase the accuracy of models.