Remotely sensed observations in the visible to the shortwave infrared (VSWIR) and thermal infrared (TIR) regions of the electromagnetic spectrum can be used synergistically to provide valuable products of land surface properties for reliable assessments of carbon and water fluxes. The high spatial, spectral and temporal resolution VSWIR and TIR observations provided by the proposed Hyperspectral ? InfraRed (HyspIRI) mission will enable a new era of global agricultural monitoring, critical for addressing growing issues of food insecurity. To enable predictions at fine spatial resolution (<100m), modeling efforts must rely on a combination of high-frequency temporal and highresolution spatial information. In this study, spatialtemporal sampling frequency is improved by employing a multi-scale and multi-sensor data fusion approach, integrating spatial detail from Landsat (30m/16 day) with the high temporal frequency of MODIS (1km/daily).