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Intensity Transformation Fusion of Landsat 8 Thermal Infrared (TIR) Imagery

  • Kul Vaibhav SharmaEmail author
  • Sumit Khandelwal
  • Nivedita Kaul
Conference paper
  • 12 Downloads
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1122)

Abstract

The spatial resolution of panchromatic (PAN) and thermal infrared (TIR) band is 15 m and 100 m respectively in Landsat-8 satellite dataset. The current research proposes an Intensity transformation based fusion method (ITFM) of PAN and TIR imagery. The proposed fusion method introduces unscented spatial filtering of input TIR and PAN images and component based fusion to downscale coarse resolution thermal data. The proposed algorithm has been examined with three thermal image downscaling methods, i.e., DisTrad, TsHARP and Local model. The relative comparison of fusion algorithms results has shown that the proposed ITFM fusion method has outperformed the other conventional methods. The proposed ITFM fusion method has merged edge details from PAN band and earth surface thermal information from TIR band precisely.

Keywords

Data fusion Land surface temperature Thermal infrared (TIR) Panchromatic (PAN) 

References

  1. 1.
    Yang, J., Zhang, J., Li, H., et al.: Pixel level fusion methods for remote sensing images: a current review. In: Remote Sensing Symposium (ISPRS), vol. 38, pp. 680–686 (2010)Google Scholar
  2. 2.
    Gao, F., Masek, J., Schwaller, M., Hall, F.: On the blending of the Landsat and MODIS surface reflectance: predicting daily Landsat surface reflectance. IEEE Trans. Geosci. Remote Sens. 44, 2207–2218 (2006)CrossRefGoogle Scholar
  3. 3.
    Li, X., et al.: Generating a series of fine spatial and temporal resolution land cover maps by fusing coarse spatial resolution remotely sensed images and fine spatial resolution land cover maps. Remote Sens. Environ. 196, 293–311 (2017)CrossRefGoogle Scholar
  4. 4.
    Wang, Q., Alan, G., Onojeghuo, A.O., et al.: Fusion of Landsat 8 OLI and sentinel-2 MSI data, pp. 1–24 (2015)Google Scholar
  5. 5.
    Al-Wassai, F.A., Kalyankar, D.N.: A novel metric approach evaluation for the spatial enhancement of pan-sharpened, pp. 479–493. CS & IT-CSCP (2012)Google Scholar
  6. 6.
    Rodríguez-Galiano, V.F., et al.: Increasing the spatial resolution of thermal infrared images using cokriging. Procedia Environ. Sci. 3, 117–122 (2011)CrossRefGoogle Scholar
  7. 7.
    Rodriguez-Galiano, V., et al.: Downscaling Landsat 7 ETM+ thermal imagery using land surface temperature and NDVI images. Int. J. Appl. Earth Obs. Geoinf. 18, 515–527 (2012)CrossRefGoogle Scholar
  8. 8.
    Zhu XX, Bamler R.: A Sparse Image Fusion Algorithm With Application to Pan-Sharpening. Vol. 51, pp. 2827–2836. IEEE Transactions on Geoscience and Remote Sensing (IEEE), (2013)Google Scholar
  9. 9.
    Jin, H., Han, D.: Multisensor fusion of Landsat images for high-resolution thermal infrared images using sparse representations. Math. Probl. Eng. 2017, 1–10 (2014)Google Scholar
  10. 10.
    Baraldi, A., Despini, F., Teggi, S.: Multi-spectral image panchromatic sharpening – outcome and process quality assessment protocol, pp. 1–39. IEEE (2017)Google Scholar
  11. 11.
    Rahaman, K.R., Hassan, Q.K., Ahmed, M.R.: Pan-sharpening of Landsat-8 images and its application in calculating vegetation greenness and canopy water contents. Int. J. Geo-Inf. (MDPI) 6, 168 (2017)CrossRefGoogle Scholar
  12. 12.
    Farhanj, F., Akhoondzadeh, M.: Fusion of Landsat-8 thermal infrared and visible bands with multi-resolution analysis contourlet methods. Int. Arch. Photogramm Remote Sens. (ISPRS) 42, 77–81 (2017)CrossRefGoogle Scholar
  13. 13.
    Jamshidi, S., et al.: Application of a simple Landsat-MODIS fusion model to estimate evapotranspiration over a heterogeneous sparse vegetation region. Int. J. Geo-Inf. (MDPI) 11, 741 (2019)Google Scholar
  14. 14.
    Cho, K., Kim, Y., Kim, Y.: Disaggregation of Landsat-8 thermal data using guided SWIR imagery on the scene of awildfire. Int. J. Geo-Inf. (MDPI) 10, 105 (2018)Google Scholar
  15. 15.
    Wang, F., Qin, Z., Song, C., et al.: An improved mono-window algorithm for land surface temperature retrieval from Landsat 8 thermal infrared sensor data. Int. J. Geo-Inf. (MDPI) 7, 4268–4289 (2015)Google Scholar

Copyright information

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Kul Vaibhav Sharma
    • 1
    Email author
  • Sumit Khandelwal
    • 1
  • Nivedita Kaul
    • 1
  1. 1.Civil Engineering DepartmentMNIT JaipurJaipurIndia

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