Land cover use practices and the ongoing human activities and climate changes have significantly affected agricultural and forest productivity by imposing severe and novel combinations of multiple stresses on the natural ecosystems. There is a strong need to develop an approach for quantifying the spateo-temporal changes in vegetation condition and photosynthetic function at moderate ground resolution (20-30 m) across large regional/continental/global scales. In the spring of 2015 ESA’s Sentinel-2 (S-2) satellite joined NASA’s Landsat-8 (L-8) in providing moderate-resolution, multispectral measurements with global extent, therefore increasing the temporal resolution of such data. We propose to use the recently developed homogenized L-8 and S-2 (HLS) high-frequency time series to develop a new canopy chlorophyll content product, and to evaluate the seasonal changes in land cover chlorophyll content and associated productivity for key agricultural crops, grasslands and forested ecosystems. The key objectives of the proposed effort are to: 1) using in a seamless fashion the dense time series of HLS, L-8 and S-2 images to develop algorithms for estimating canopy chlorophyll (Chl) content; and 2) generate robust workflows and produce high density time series of land cover Chl products for major vegetation cover types (crops, grasslands and forests). Earlier studies using individual Landsat scenes (e.g. Landsats TM and ETM+) were not able to detect the early stages in vegetation damage. Those studies only partially accounted for variations in atmospheric conditions, terrain elevation and illumination. Using the improved spectral resolution of the HLS L-8 and S-2 data (narrower red edge bands and additional blue, near-infrared, short-infrared and thermal bands), complemented with very high resolution (2 m) World View images/triplets to characterize canopy variations and structural effects, we will produce dense time series of vegetation indices and Chl products sensitive to the fine changes in chlorophyll content for improved monitoring of agricultural crops and forest biomass production. To generate robust workflows, the algorithms will be tested, refined and validated at established research areas and instrumented sites representing major agricultural crops and forested ecosystems. We will use the L-8 thermal bands (TIRS1) to quantify the effects from changes in Chl content and vegetation damage on agricultural and forest productivity, comparing the phenology trends in canopy Chl, TIRS1 and ecosystem primary production, as measured at the sites. By analyzing these coupled dense time series, we will provide essential information about the major biophysical drivers of vegetation health and function. This effort leverages the ongoing international collaborations between USA and European Union researchers, which will provide expertise and satellite imagery available at their organizations as well as field spectral data obtained from established sites with on-going field data collections. The proposed work directly supports the goals of NASA’s LCLUC program, to further "develop the capability for periodic satellite-based inventories of land cover, and monitoring and characterizing land-cover and land-use change." This effort provides a significant step forward towards developing an approach and tools for evaluation of vegetation health and photosynthetic function at 30 m resolution, that will enhance our ability to identify the drivers and quantify the rates of land cover change for critical vegetation types across the globe. This enhanced capability will greatly improve the information available for timely management decisions that have potential to reduce the associated agricultural, economic and climate impacts of environmental and anthropogenic factors.