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Abstract The dynamics of Leaf Area Index (LAI) from space is key to identify crop types and their phenology over large areas, and to characterize spatial variations within growers’ fields. However, for years remote-sensing applications have been constrained by a trade-off between the spatial and temporal resolutions. This study resolves this limitation. Over the past decade, the number of companies and organizations developing CubeSat constellations has increased. These new satellites make it possible to acquire large image collections at high spatial and temporal resolutions at a relatively low cost. However, the images obtained from CubeSat constellations frequently suffer from inconsistency in the data calibration between the different satellites within the constellation. To overcome these inconsistencies, a new method to fuse a time series of images sourced from two different satellite constellations is proposed …