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Land surface temperature retrieval for arid regions based on Landsat-8 TIRS data: a case study in Shihezi, Northwest China

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Abstract

Scientific interest in geophysical information about land surface temperature (LST) is ever increasing, as such information provides a base for a large number of applications, including environmental and agricultural monitoring. Therefore, the research of LST retrieval has become a hot topic. Recent availability of Landsat-8 satellite imagery provides a new data source for LST retrieval. Hence, exploring an adaptive method with reliable accuracy seems to be essential. In this study, basing on features of Landsat-8 TIRS thermal infrared channels, we re-calculated parameters in the atmospheric transmittance empirical models of the existing split-window algorithm, and estimated the ground emissivity with the help of the land cover classification map of the study area. Furthermore, a split-window algorithm was rebuilt by virtual of the estimation model of the updated atmospheric transmittance and the ground emissivity, and then a remote sensing retrieval for the LST of Shihezi city in Xinjiang Uygur autonomous region of Northwest China was conducted on the basis of this modified algorithm. Finally, precision validation of the new model was implemented by using the MODIS LST products. The results showed that the LST retrieval from Landsat-8 TIRS data based on our algorithm has a higher credibility, and the retrieved LST is more consistent with the MODIS LST products. This indicated that the modified algorithm is suitable for retrieving LST with competitive accuracy. With higher resolutions, Landsat-8 TIRS data may provide more accurate observation for LST retrieval.

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References

  • Becker F, Li Z L. 1995. Surface temperature and emissivity at various scales: Definition, measurement and related problems. Remote Sensing Reviews, 12(3–4): 225–253.

    Article  Google Scholar 

  • Friedel M J. 2012. Data-driven modeling of surface temperature anomaly and solar activity trends. Environmental Modelling & Software, 37: 217–232.

    Article  Google Scholar 

  • Gao L, Qin Z H. 2007. Research on the fitting relation of the planck equation expansion parameter model in split window algorithm. Geography and Geo-Information Science, 23(4): 9–12.

    Google Scholar 

  • Hall M R, Dehdezi P K, Dawson A R, et al. 2012. Influence of the thermophysical properties of pavement materials on the evolution of temperature depth profiles in different climatic regions. Journal of Materials in Civil Engineering, 24(1): 32–47.

    Article  Google Scholar 

  • Irons J R, Dwyer J L, Barsi J A. 2012. The next Landsat satellite: The Landsat Data Continuity Mission. Remote Sensing of Environment, 122: 11–21.

    Article  Google Scholar 

  • Jiang L P, Qin Z H, Xie W. 2006. Retrieving atmospheric water vapor from modis near infrared data. Remote Sensing For Land & Resources, (3): 5–9, 88.

    Google Scholar 

  • Jiménez-Muñoz J C, Sobrino J A. 2003. A generalized single-channel method for retrieving land surface temperature from remote sensing data. Journal of Geophysical Research: Atmospheres, 108(D22): 4688–4695.

    Article  Google Scholar 

  • Jiménez-Muñoz J C, Sobrino J A. 2010. A single-channel algorithm for land-surface temperature retrieval from ASTER data. Geoscience and Remote Sensing Letters, IEEE, 7(1): 176–179.

    Article  Google Scholar 

  • Katsiabani K, Adaktilou N, Cartalis C. 2009. A generalised methodology for estimating land surface temperature for non-urban areas of Greece through the combined use of NOAA-AVHRR data and ancillary information. Advances in Space Research, 43(6): 930–940.

    Article  Google Scholar 

  • Kaufman Y J, Gao B C. 1992. Remote sensing of water vapor in the near IR from EOS/MODIS. IEEE Transactions on Geoscience and Remote Sensing, 30(5): 871–884.

    Article  Google Scholar 

  • Li H, Liu Q H, Zhong B, et al. 2010. A single-channel algorithm for land surface temperature retrieval from HJ-1B/IRS data based on a parametric model. Geoscience and Remote Sensing Symposium (IGARSS), 2010 IEEE International, 2448–2451.

    Chapter  Google Scholar 

  • Li Z L, Tang B H, Wu H, et al. 2013. Satellite-derived land surface temperature: Current status and perspectives. Remote Sensing of Environment, 131(2013): 14–37.

    Article  Google Scholar 

  • Ma Y, Kuang Y Q, Huang N S. 2010. Coupling urbanization analyses for studying urban thermal environment and its interplay with biophysical parameters based on TM/ETM+ imagery. International Journal of Applied Earth Observation and Geoinformation, 12(2): 110–118.

    Article  Google Scholar 

  • Maimaitiyiming M, Ghulam A, Tiyip T, et al. 2014. Effects of green space spatial pattern on land surface temperature: Implications for sustainable urban planning and climate change adaptation. ISPRS Journal of Photogrammetry and Remote Sensing, 89: 59–66.

    Article  Google Scholar 

  • McMillin L M. 1975. Estimation of sea surface temperatures from two infrared window measurements with different absorption. Journal of Geophysical Research, 80(36): 5113–5117.

    Article  Google Scholar 

  • Peng S S, Piao S L, Zeng Z Z, et al. 2014. Afforestation in China cools local land surface temperature. Proceedings of the National Academy of Sciences, 111(8): 2915–2919.

    Article  Google Scholar 

  • Price J C. 1984. Land surface temperature measurements from the split window channels of the NOAA 7 Advanced Very High Resolution Radiometer. Journal of Geophysical Research: Atmospheres, 89(D5): 231–237.

    Article  Google Scholar 

  • Qin Z H, Olmo G D, Karnieli A. 2001a. Derivation of split window algorithm and its sensitivity analysis for retrieving land surface temperature from NOAA-advanced very high resolution radiometer data. Journal of Geophysical Research, 106(D19): 22655–22670.

    Article  Google Scholar 

  • Qin Z H, Karnieli A, Berliner P. 2001b. A mono-window algorithm for retrieving land surface temperature from Landsat TM data and its application to the Israel-Egypt border region. International Journal of Remote Sensing, 22(18): 3719–3746.

    Article  Google Scholar 

  • Qin Z H, Zhang M H, Arnon K. 2001c. Split window algorithms for retrieving land surface temperature from NOAA-AVHRR data. Remote Sensing For Land & Resources, 56(2): 33–42.

    Google Scholar 

  • Sobrino J, Raissouni N, Li Z L. 2001. A comparative study of land surface emissivity retrieval from NOAA data. Remote Sensing of Environment, 75(2): 256–266.

    Article  Google Scholar 

  • Son N T, Chen C F, Chen C R, et al. 2012. Monitoring agricultural drought in the Lower Mekong Basin using MODIS NDVI and land surface temperature data. International Journal of Applied Earth Observation and Geoinformation, 18: 417–427.

    Article  Google Scholar 

  • Srivastava P K, Majumdar T J, Bhattacharya A K. 2009. Surface temperature estimation in Singhbhum Shear Zone of India using Landsat-7 ETM+ thermal infrared data. Advances in Space Research, 43(10): 1563–1574.

    Article  Google Scholar 

  • Stathopoulou M, Cartalis C, Petrakis M. 2007. Integrating Corine Land Cover data and Landsat TM for surface emissivity definition: application to the urban area of Athens, Greece. International Journal of Remote Sensing, 28(15): 3291–3304.

    Article  Google Scholar 

  • Van de Griend A A, Owe M. 1993. On the relationship between thermal emissivity and the normalized difference vegetation index for natural surfaces. International Journal of Remote Sensing, 14(6): 1119–1131.

    Article  Google Scholar 

  • Vinnikov K Y, Yu Y Y, Goldberg M D, et al. 2011. Scales of temporal and spatial variability of midlatitude land surface temperature. Journal of Geophysical Research: Atmospheres (1984–2012), 116(D2): 2156–2202.

    Article  Google Scholar 

  • Wan Z, Zhang Y, Zhang Q, et al. 2004. Quality assessment and validation of the MODIS global land surface temperature. International Journal of Remote Sensing, 25(1): 261–274.

    Article  Google Scholar 

  • Wan Z M. 2008. New refinements and validation of the MODIS land-surface temperature/emissivity products. Remote Sensing of Environment, 112(1): 59–74.

    Article  Google Scholar 

  • Yao J Q. 2012. Temporal-spatial distribution of the water vapor content and evolution character of water vapor during heavy rain in Tianshan Mountains. MSc Thesis. Urumqi: Xinjiang Normal University.

    Google Scholar 

  • Zheng G Q, Lu M, Zhang T, et al. 2010. The impact of difference of land surface emissivity on the land surface temperature retrieval in Jinan City. Journal of Shandong Jianzhu University, 25(5): 519–523.

    Google Scholar 

  • Zhou J, Zhan W F, Hu D Y, et al. 2010. Improvement of mono-window algorithm for retrieving land surface temperature from HJ-1B satellite data. Chinese Geographical Science, 20(2): 123–131.

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Remote Sensing and Geographic Information Engineering, Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, 611756, China

    Lei Yang & YunGang Cao

  2. Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China

    XiaoHua Zhu

  3. Institute of Farmland Water Conservancy and Soil-fertilizer, Xinjiang Academy of Agricultural and Reclamation Science, Shihezi, 832000, China

    ShengHe Zeng, GuoJiang Yang & JiangYong He

  4. Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, 100081, China

    XiuChun Yang

  5. College of Environment and Planning, Shangqiu Normal University, Shangqiu, 476000, China

    XiuChun Yang

Authors
  1. Lei Yang
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  2. YunGang Cao
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  3. XiaoHua Zhu
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  4. ShengHe Zeng
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  5. GuoJiang Yang
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  6. JiangYong He
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  7. XiuChun Yang
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Correspondence to XiuChun Yang.

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Yang, L., Cao, Y., Zhu, X. et al. Land surface temperature retrieval for arid regions based on Landsat-8 TIRS data: a case study in Shihezi, Northwest China. J. Arid Land 6, 704–716 (2014). https://doi.org/10.1007/s40333-014-0071-z

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  • DOI: https://doi.org/10.1007/s40333-014-0071-z

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