Derivation of a tasselled cap transformation based on Landsat 8 at-satellite reflectance

Abstract

The tasselled cap transformation (TCT) is a useful tool for compressing spectral data into a few bands associated with physical scene characteristics with minimal information loss. TCT was originally evolved from the Landsat multi-spectral scanner (MSS) launched in 1972 and is widely adapted to modern sensors. In this study, we derived the TCT coefficients for the newly launched (2013) operational land imager (OLI) sensor on-board Landsat 8 for at-satellite reflectance. A newly developed standardized mechanism was used to transform the principal component analysis (PCA)-based rotated axes through Procrustes rotation (PR) conformation according to the Landsat thematic mapper (TM)-based tasselled cap space. Firstly, OLI data were transformed into TM TCT space directly and considered as a dummy target. Then, PCA was applied on the original scene. Finally, PR was applied to get the transformation results in the best conformation to the target image. New coefficients were analysed in detail to confirm Landsat 8-based TCT as a continuity of the original tasselled cap idea. Results show that newly derived set of coefficients for Landsat OLI is in continuation of its predecessors and hence provide data continuity through TCT since 1972 for remote sensing of surface features such as vegetation, albedo and water. The newly derived TCT for OLI will also be very useful for studying biomass estimation and primary production for future studies.

Acknowledgements

We would like to thank Prof. Bruce Wylie from USGS and Prof. W.B. Cohen from Oregon State University for their useful feedback during this research process. We are indebted to Dr. Mohtashim H. Shamsi from the University of Toronto, Mr. Qin Bangyong and Mr. Jiang Gaozhen for their valuable contribution. Last but not least, we owe debt of gratitude to the Editor, two unknown reviewers and the administrative assistant of RSL for giving us very important feedback to improve the quality of this letter.

Funding

This work was funded by the National Natural Science Foundation of China [grant numbers 41371362, 41371359 and 41201348].