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Analysis of Slope and NDVI Effects on Land Surface Temperature Retrieval Accuracy in Mountain Area Based on WIS Data of Tiangong-2

  • Jingxu Wang
  • Bing Wang
  • Yangyang Liu
  • Huaguo Huang
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 541)

Abstract

The relationship between land surface temperature (LST) and Normalized Difference Vegetation Index (NDVI) is evaluated in mountain areas using the Wide-band Imaging Spectrometer (WIS) data on Chinese Tiangong-2 (TG-2) Space Lab. The WIS is composed of three regions: Visible Near-Infrared (VNIR) (14 channels), Short-Wave Infrared (SW) (2 channels), and Thermal Infrared (TIR) (2 channels). The two TIR channels, T1 (8.125–8.825 μm) and T2 (8.925–9.275 μm) have not been fully exploited to extract LST. Thus, a modified split window method was proposed to retrieve LST and evaluated by comparing to the MODIS LST product. Then, the LST retrieval accuracy affected by slope and NDVI is analyzed. Results show that: (a) TG-2 LST is positively correlated to MODIS LST (R2 = 0.74) but overestimated (about 3.5 K); further improvement on the split window method is still needed; (b) the TG-2 LST accuracy is different in vegetation and non-vegetation area, where non-vegetation area with small NDVI standard deviation has better agreement between MODIS LST and TG-2 than vegetation area; (c) the LST retrieval accuracy in vegetation area is independent on slopes; while increasing with the slope in non-vegetation area.

Keywords

LST retrieval Split-window algorithm NDVI Slope TIR WIS data of Tiangong-2 

Notes

Acknowledgements

This work was supported by the Natural Science Foundation of China (41571332). Thanks to China Manned Space Engineering for providing Wide-band Imaging Spectrometer (WIS) data products of Tiangong-2.

References

  1. 1.
    Wang, K., Wan, Z., Wang, P., Sparrow, M., Liu, J., Haginoya, S.: Evaluation and improvement of the MODIS land surface temperature/emissivity products using ground-based measurements at a semi-desert site on the western Tibetan Plateau. Int. J. Remote Sens. 28(11), 2549–2565 (2007)CrossRefGoogle Scholar
  2. 2.
    Wang, K., et al.: Estimation of surface long wave radiation and broadband emissivity using Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature emissivity products. J. Geophys. Res. Atmos. 110(D11109) (2005)Google Scholar
  3. 3.
    Arnfield, A.J.: Two decades of urban climate research: a review of turbulence, exchanges of energy and water, and the urban heat island. Int. J. Climatol. 23(1), 1–26 (2003)CrossRefGoogle Scholar
  4. 4.
    Bastiaanssen, W.G.M., Menenti, M., Feddes, R.A., Holtslag, A.A.M.: The Surface energy balance algorithm for land (SEBAL): Part 1 formulation. J. Hydrol. 212(98), 801–811 (1998)Google Scholar
  5. 5.
    Hansen, J., Ruedy, R., Sato, M., Lo, K.: Global surface temperature change. Rev. Geophys. 48(4), G4004 (2010)CrossRefGoogle Scholar
  6. 6.
    Kanani, K., Poutier, L., Nerry, F., Stoll, M.P.: Directional effects consideration to improve out-doors emissivity retrieval in the 3–13 mum domain. Opt. Express 15(19), 12464–12482 (2007)CrossRefGoogle Scholar
  7. 7.
    Weng, Q., Lu, D., Schubring, J.: Estimation of land surface temperature-vegetation abundance relationship for urban heat island studies. Remote Sens. Environ. 89(4), 467–483 (2004)CrossRefGoogle Scholar
  8. 8.
    Weng, Q.: Thermal infrared remote sensing for urban climate and environmental studies: Methods, applications, and trends. Isprs J. Photogramm. Remote Sens. 64(4), 335–344 (2009)CrossRefGoogle Scholar
  9. 9.
    Voogt, J.A., Oke, T.R.: Thermal remote sensing of urban climates. Remote Sens. Environ. 86(3), 370–384 (2003)CrossRefGoogle Scholar
  10. 10.
    Dash, P., Göttsche, F.M., Olesen, F.S., Fischer, H.: Retrieval of land surface temperature and emissivity from satellite data: Physics, theoretical limitations and current methods. J. Indian Soc. Remote Sens. 29(1–2), 23 (2001)CrossRefGoogle Scholar
  11. 11.
    Li, Z.L., Tang, B.H., Wu, H., Ren, H.Z., Yan, G.J., Wan, Z.M., Trigo, I.F., Sobrino, J.: Satellite-derived land surface temperature: Current status and perspectives. Remote Sens. Environ. 131(131), 14–37 (2013)CrossRefGoogle Scholar
  12. 12.
    Liu, X., Huang, J.X., Qin, J., Wang, P., Xu, T.: Estimating of land surface turbulent fluxes based on weak constraint variational method and GOES data. Trans. Chin. Soc. Agric. Mach. 45(1), 236–245 (2014)Google Scholar
  13. 13.
    Zhang, X., Tang, Y.Y., Huang, X.X., Wei, J.: Performance analysis of split-window algorithms for retrieving land surface temperature using remote sensing data of 8.0–9.3μm. Remote Sens. Land Resour. 27(2), 88–93 (2015)Google Scholar
  14. 14.
    Weng, Q.: A remote sensing-GIS evaluation of urban expansion and its impact on surface temperature in the Zhujiang Delta, China. Int. J. Remote Sens. 22(10), 1999–2014 (2001)Google Scholar
  15. 15.
    Weng, Q.: Fractal analysis of satellite-detected urban heat island effect. Photogramm. Eng. Remote Sens. 69(5), 555–566 (2003)CrossRefGoogle Scholar
  16. 16.
    Franca, G.B., Cracknell, A.P.: Retrieval of land and sea surface temperature using NOAA-11 AVHRR data in north-eastern Brazil. Int. J. Remote Sens. 15(8), 1695–1712 (1994)CrossRefGoogle Scholar
  17. 17.
    Sobrino, J.A., Coll, C., Caselles, V.: Atmospheric correction for land surface temperature using NOAA-11 AVHRR channels 4 and 5. Remote Sens. Environ. 38(1), 19–34 (1991)CrossRefGoogle Scholar
  18. 18.
    Qin, H.Z., Zhang, M.H., Karnieli, A., Berliner, P.: Mono-window algorithm for retrieving land surface temperature from Landsat TM6 data. Acta Geogr. Sin. 56(4), 456–466 (2001)Google Scholar
  19. 19.
    Mao, K.B.: A study of method for land surface temperature retrieval from MODIS data. Nanjing University, Nanjing (2004)Google Scholar
  20. 20.
    Huang, L., Huang, H., Xiang, D., Zhu, J.: The diurnal change of air temperature in four types of land cover and urban heat island effect in Nanjing, China. Ecology Environ. 16(5), 1411–1420 (2007)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Jingxu Wang
    • 1
  • Bing Wang
    • 1
  • Yangyang Liu
    • 1
  • Huaguo Huang
    • 1
  1. 1.Key Laboratory for Silviculture and Conservation of Ministry of EducationBeijing Forestry UniversityBeijingChina

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