DOI QR코드

DOI QR Code

Analysis on the Effect of Spectral Index Images on Improvement of Classification Accuracy of Landsat-8 OLI Image

  • Magpantay, Abraham T. (College of Computer Studies, Far Eastern University Institute of Technology) ;
  • Adao, Rossana T. (College of Computer Studies, Far Eastern University Institute of Technology) ;
  • Bombasi, Joferson L. (College of Computer Studies, Far Eastern University Institute of Technology) ;
  • Lagman, Ace C. (College of Computer Studies, Far Eastern University Institute of Technology) ;
  • Malasaga, Elisa V. (College of Computer Studies, Far Eastern University Institute of Technology) ;
  • Ye, Chul-Soo (Department of Aviation and IT Convergence, Far East University)
  • Received : 2019.08.05
  • Accepted : 2019.08.21
  • Published : 2019.08.31

Abstract

In this paper, we analyze the effect of the representative spectral indices, normalized difference vegetation index (NDVI), normalized difference water index (NDWI) and normalized difference built-up index (NDBI) on classification accuracies of Landsat-8 OLI image.After creating these spectral index images, we propose five methods to select the spectral index images as classification features together with Landsat-8 OLI bands from 1 to 7. From the experiments we observed that when the spectral index image of NDVI or NDWI is used as one of the classification features together with the Landsat-8 OLI bands from 1 to 7, we can obtain higher overall accuracy and kappa coefficient than the method using only Landsat-8 OLI 7 bands. In contrast, the classification method, which selected only NDBI as classification feature together with Landsat-8 OLI 7 bands did not show the improvement in classification accuracies.

References

  1. Feyisa, G. L., H. Meilby, R. Fensholt, and S. R. Proud, 2014. Automated water extraction index: a new technique for surface water mapping using Landsat imagery, Remote Sensing of Environment, 140: 23-35. https://doi.org/10.1016/j.rse.2013.08.029
  2. Gao, B.C., 1996. NDWI - normalized difference water index for remote sensing of vegetation liquid water from space, Remote Sensing of Environment, 58(3): 257-266. https://doi.org/10.1016/S0034-4257(96)00067-3
  3. Japitana, M.V., C. S. Ye, and M. E. C. Burce, 2019. Combining water indices to detect water bodies using Landsat 8 OLI, Journal of Institute of Control, Robotics and Systems, 25(5): 470-475. https://doi.org/10.5302/J.ICROS.2019.18.0220
  4. Mcfeeters, S.K., 1996. The use of normalized difference water index (NDWI) in the delineation of open water features, International Journal of Remote Sensing, 17(7): 1425-1432. https://doi.org/10.1080/01431169608948714
  5. Park, J.H., R. T. Adao, J. L. Bombasi, A.C. Lagman, and C. S. Ye, 2018. Improvement of classification accuracy using index image combination, Proc. of 2018 International Symposium on Remote Sensing, Pyeongchang, Korea, May 9-11, pp. 619-620.
  6. Rouse, J.W., R.H. Haas, J.A. Schell, and D.W. Deering, 1974. Monitoring vegetation systems in the Great Plains with ERTS, Proc. of Third Earth Resources Technology Satellite-1 Symposium, vol. 1, pp. 309-317.
  7. Thakkar, A., V. Desai, A. Patel, and M. Potdar, 2015. Land use/land cover classification using remote sensing data and derived indices in a heterogeneous landscape of a khan-kali watershed, Gujarat, Asian Journal of Geoinformatics, 14(4): 1-12.
  8. Xu, H., 2006. Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery, International Journal of Remote Sensing, 27(14): 3025-3033. https://doi.org/10.1080/01431160600589179
  9. Ye, C. S., C. G. Moon, and J. H. Jeon, 2007. Stereo matching method using directional feature vector, Journal of Control, Automation, and Systems Engineering, 13(1): 52-57. https://doi.org/10.5302/J.ICROS.2007.13.1.052
  10. Ye, C.S., 2015. Extraction of water body in before and after images of flood using Mahalanobis distance-based spectral analysis, Korean Journal of Remote Sensing, 31(4): 293-302. https://doi.org/10.7780/kjrs.2015.31.4.2
  11. Zha, Y., J. Gao, and S. Ni, 2003. Use of normalized difference built-up index in automatically mapping urban areas from TM imagery, International Journal of Remote Sensing, 24(3): 583-594. https://doi.org/10.1080/01431160304987