Physics-Based Fusion of Sentinel-2 and Sentinel-3 for Higher Resolution Vegetation Monitoring

Monitoring vegetation growth, phenology, and health in agriculture requires very high spatial and spectral resolution sensors. Sentinel-2 is among the spaceborne sensors that tried to meet these requirements. However, due to physical constraints, few visible bands are present with relatively large spectral responses, which limits the leaf pigment content estimation. In this work, we propose to fuse Sentinel-2 bands with a Sentinel-3 image, which has a lower spatial resolution but contains several spectral narrower bands in both the visible and near-infrared (NIR) domains. The fusion procedure consists in sharpening the Sentinel-3 bands to match the Sentinel-2 spatial resolution leading to a higher spatial resolution Sentinel-3 image. The proposed fusion technique follows a physics-based approach based on the use of a radiative transfer model (RTM) for establishing a correspondence between Sentinel-2 and Sentinel-3 images. In greater details, the main spectrally pure constituent of each high-resolution Sentinel-2 pixel is identified for each pixel, and it is then related to the corresponding low-resolution Sentinel-3 pixel. Pure materials are the barycenters of clusters obtained by an unsupervised classification of the Sentinel-2 image. Sentinel-3 signatures are obtained using coarse resolution pixel matching with the Sentinel-2 image. The latter result is then corrected using radiative transfer modeling allowing the production of more realistic signatures. Validation was done using real Sentinel-2/Sentinel-3 images taken with a delay of only one day or less and by comparing the sharpened Sentinel-3 bands Oa04, Oa06, Oa08, and Oa17 with the corresponding Sentinel-2 bands B2, B3, B4, and B8A, as they are, respectively, spectrally close. For all the bands, the rms is lower than 0.007, and compared with the state-of-the-art techniques, it shows competitive results and robustness against scene heterogeneity. Besides, our findings prove that the retrieved Sentinel-3 signatures at full resolution (FR) are physically consistent and in good agreement with the Sentinel-2 data.