Volume XLI-B7
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B7, 647-652, 2016
https://doi.org/10.5194/isprs-archives-XLI-B7-647-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B7, 647-652, 2016
https://doi.org/10.5194/isprs-archives-XLI-B7-647-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

  21 Jun 2016

21 Jun 2016

SOME ASPECTS OF SATELLITE IMAGERY INTEGRATION FROM EROS B AND LANDSAT 8

A. Fryskowska, M. Wojtkowska, P. Delis, and A. Grochala A. Fryskowska et al.
  • Department of Remote Sensing and Photogrammetry, Geodesy Institute, Faculty of Civil Engineering and Geodesy, Military University of Technology, Warsaw, Poland

Keywords: Image Processing, Fusion data, Pan-sharpening, Multispectral imagery, IHS resolution merge, Brovey transform

Abstract. The Landsat 8 satellite which was launched in 2013 is a next generation of the Landsat remote sensing satellites series. It is equipped with two new sensors: the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS). What distinguishes this satellite from the previous is four new bands (coastal aerosol, cirrus and two thermal infrared TIRS bands). Similar to its antecedent, Landsat 8 records electromagnetic radiation in a panchromatic band at a range of 0.5‐0.9 μm with a spatial resolution equal to 15 m. In the paper, multispectral imagery integration capabilities of Landsat 8 with data from the new high resolution panchromatic EROS B satellite are analyzed. The range of panchromatic band for EROS B is 0.4‐0.9 μm and spatial resolution is 0.7 m. Research relied on improving the spatial resolution of natural color band combinations (bands: 4,3,2) and of desired false color band composition of Landsat 8 satellite imagery. For this purpose, six algorithms have been tested: Brovey’s, Mulitplicative, PCA, IHS, Ehler's, HPF. On the basis of the visual assessment, it was concluded that the best results of multispectral and panchromatic image integration, regardless land cover, are obtained for the multiplicative method. These conclusions were confirmed by statistical analysis using correlation coefficient, ERGAS and R-RMSE indicators.