A spatial and temporal reflectance fusion model considering sensor observation differences

This article proposes a spatial–temporal expansion method for remote-sensing reflectance by blending observations from sensors with different spatial and temporal characteristics. Compared with the methods used in the past, the main characteristic of the proposed method is consideration of sensor observation differences between different cover types when calculating the weight function of the fusion model. The necessity of the temporal difference factor commonly used in spatial–temporal fusion is also analysed in this article. The method was tested and quantitatively assessed under different landscape situations. The results indicate that the proposed fusion method improves the prediction accuracy of fine-resolution reflectance.

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