A spatial and temporal reflectance fusion model considering sensor observation differences

Abstract

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.

Acknowledgement

The authors gratefully acknowledge the research support from the Major State Basic Research Development Programme (973 Programme) of China under Grant No. 2011CB707103, the National High Technology Research and Development Programme (863 Programme) under Grant 2013AA12A301, National Natural Science Foundation of China under Grant 41271376, and Fundamental Research Funds for the Central Universities under Grant 2012205020205. We are grateful to the reviewers for their helpful comments and suggestions.