Research Article
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A Study of the Impact of Aerosols on The Estimation of Land Surface Temperature from Space Using Simulation of Satellite Data

Year 2021, Volume: 2 Issue: 1, 11 - 20, 13.03.2021
https://doi.org/10.48123/rsgis.839293

Abstract

Accurate estimation of land surface temperature (LST) is strongly required for many applications such as environmental studies. However, there are several algorithms in the literature for estimating LST from satellite those do not take into account the effect of the aerosols. Actually, these aerosols can exert an important influence on the estimation of LST from satellite thermal infrared data. Therefore, in this paper we presented a theoretical study and a simple methodology to show the impact of the aerosols on the estimation of LST from satellite in the thermal infrared region. For this, the simulation by the radiative transfer code Modtran3.5 has been carried out. The results showed that, the impact of aerosols on the estimation of LST depends on the Viewing angle, atmospheric situation, type of aerosols and surface emissivity. The results showed also that, the difference between LST estimated when the aerosol model is considered with respect to atmosphere without aerosol content varies increasingly with the viewing angle and is very sensitive to the situation of the atmosphere and varies decreasingly with the visibility and varies increasingly with the surface emissivity. This work shows that, for the lowest values of the visibility, the impact of aerosols is important and correction is needed for estimating LST. Discussion about this is given in this work.

References

  • Abreu, L.W. & Anderson, G.P. (Eds), (1996). The MODTRAN 2/3 Report and LOWTRAN 7 MODEL, Modtran Report, Contract F19628-91-C-0132, Hanscom, MA: USA.
  • Becker, F., & Li Z.-L. (1990). Towards a local split window method over land surfaces. International Journal of Remote Sensing, 11(3), 369-393. doi.org/10.1080/01431169008955028.
  • Dash, P., Gottsche, F.M., Olesen, F.S., & Fisher, H. (2002). Land surface temperature and emissivity estimation from passive sensor data: Theory and practice-current trends. International Journal of Remote Sensing, 23(13), 2563-2594. doi.org/10.1080/01431160110115041.
  • De Paepe B., Ignatov A., Dewitte S., & Ipe A. (2008). Aerosol retrieval over ocean from SEVIRI for the use in GERB Earth's radiation budget analyses. Remote Sensing of Environment. 112(5), 2455–2468. doi.org/10.1016/ j.rse.2007.11.005.
  • François, C., & Ottlé, C. (1996). Atmospheric corrections in the thermal infrared: global and water vapor dependent split-window algorithms-applications to ATSR and AVHRR data. IEEE transactions on geoscience and remote sensing, 34(2), 457-470. DOI: 10.1109/36.485123.
  • Gao, C., Qiu, S., Zhao, E. Y., Li, C., Tang, L. L., Ma, L. L., ... & Ren, L. (2017). Land surface temperature retrieval from FY-3C/VIRR data and its cross-validation with Terra/MODIS. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10(11), 4944-4953. DOI: 10.1109/JSTARS.2017.2728082.
  • Gao, C., Zhao, E., Li, C., Qian, Y., Ma, L., Tang, L., Jiang, X., & Huo, H. (2015). Study of aerosol influence on nighttime land surface temperature retrieval based on two methods. Advances in Meteorology, 2015, 1-16. doi.org/ 10.1155/2015/496458.
  • Jiang, G. M., & Li, Z. L. (2008). Split‐window algorithm for land surface temperature estimation from MSG1‐SEVIRI data. International Journal of Remote Sensing, 29(20), 6067-6074. doi.org/10.1080/01431160802235860.
  • Jiménez-munoz, J. C. & Sobrino, j. A. (2006). Error sources on the land surface temperature retrieved from thermal infrared single channel remote sensing data. International Journal of Remote Sensing, 27(5), 999–1014. doi.org/ 10.1080/01431160500075907.
  • Labbi, A., & Mokhnache, A. (2015). Derivation of split-window algorithm to retrieve land surface temperature from MSG-1 thermal infrared data. European Journal of Remote Sensing, 48 (1), 719-742. doi.org/10.5721/ EuJRS20154840.
  • Li, Z.L. (1990). L’émissivité spectrale en télédétection infrarouge thermique: mesure relative, analyse spectrale et impacts sur la détermination de la température de surface. Thesis, University of Strasbourg I, France, 163 pp.
  • Malkevich, M.S., & Gorodetsky, A.K. (1988). Determination of ocean surface temperature taking account of atmospheric effects by measurements of the angular IR-Radiation distribution of the “Ocean-Atmosphere” system made from the satellite “Cosmos-1151”. Remote sensing reviews, 3(3), 137-161, doi.org/10.1080/ 02757258809532093.
  • Qin, Z., & Karnieli, A. (2001). 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, 3719-3746. doi.org/10.1080/01431160010006971.
  • Sobrino, J.A., & Romaguera, M. (2004). Land surface temperature retrieval from MSG1-SEVIRI data. Remote Sensing of Environment, 92(2), 247-254. doi.org/10.1016/j.rse.2004.06.009.
  • Vergé-Dépré, G., Legrand, M., Moulin, C., Alias, A., & François, P. (2006). Improvement of the detection of desert dust over the Sahel using Meteosat IR imagery. Annales Geophysicae, 24(8), 2065-2073.doi.org/10.5194/angeo-24-2065-2006.
  • Zhao, E., Gao, C., & Yao, Y. (2020). New land surface temperature retrieval algorithm for heavy aerosol loading during nighttime from Gaofen-5 satellite data. Optics express, 28(2), 2583-2599. doi.org/10.1364/OE.382813.

Uydu Verilerinin Simülasyonunu Kullanılarak Aerosollerin Uzaydan Yer Yüzey Sıcaklığının Tahmini Üzerindeki Etkisine İlişkin Bir Çalışma

Year 2021, Volume: 2 Issue: 1, 11 - 20, 13.03.2021
https://doi.org/10.48123/rsgis.839293

Abstract

Birçok çevre araştırması için yer yüzey sıcaklığının (LST) doğru tahmin edilmesi büyük ölçüde gereklidir. Literatürde uydu verilerinden yer yüzey sıcaklığını tahmin etmek için önerilen birçok algoritma aerosollerin etkisini dikkate almaz. Oysaki bu aerosoller, uydu termal kızılötesi verilerinden yapılan yer yüzey sıcaklığı tahminleri üzerinde önemli bir etki yaratabilmektedir. Bu nedenle, bu çalışma, aerosollerin termal kızılötesi bölgede yer yüzey sıcaklığı tahmini üzerindeki etkisini göstermek için teorik bir araştırma ve basit bir metodoloji sunmaktadır. Bu amaçla, ışınımsal transfer kodu Modtran3.5 ile simülasyon gerçekleştirilmiştir. Elde edilen sonuçlar, aerosollerin yer yüzey sıcaklığı tahmini üzerindeki etkisinin görüş açısına, atmosferik duruma, aerosol tipine ve yüzey emisyonuna bağlı olduğunu göstermektedir. Ayrıca, aerosol modelinin dikkate alındığında ve alınmadığında oluşan yer yüzey sıcaklığı farklarının atmosferin durumuna duyarlı olduğunu, görüş açısına bağlı olarak arttığını, görünürlüğe bağlı olarak azaldığını ve yüzey yayılımına bağlı olarak azaldığını göstermektedir. Bu çalışma, aerosollerin etkisinin görünürlüğün en düşük değerleri için önemli olduğunu ve yer yüzey sıcaklığını tahmin etmek için düzeltmeye ihtiyaç duyulduğunu göstermektedir. Bununla ilgili tartışma bu çalışmada verilmektedir.

References

  • Abreu, L.W. & Anderson, G.P. (Eds), (1996). The MODTRAN 2/3 Report and LOWTRAN 7 MODEL, Modtran Report, Contract F19628-91-C-0132, Hanscom, MA: USA.
  • Becker, F., & Li Z.-L. (1990). Towards a local split window method over land surfaces. International Journal of Remote Sensing, 11(3), 369-393. doi.org/10.1080/01431169008955028.
  • Dash, P., Gottsche, F.M., Olesen, F.S., & Fisher, H. (2002). Land surface temperature and emissivity estimation from passive sensor data: Theory and practice-current trends. International Journal of Remote Sensing, 23(13), 2563-2594. doi.org/10.1080/01431160110115041.
  • De Paepe B., Ignatov A., Dewitte S., & Ipe A. (2008). Aerosol retrieval over ocean from SEVIRI for the use in GERB Earth's radiation budget analyses. Remote Sensing of Environment. 112(5), 2455–2468. doi.org/10.1016/ j.rse.2007.11.005.
  • François, C., & Ottlé, C. (1996). Atmospheric corrections in the thermal infrared: global and water vapor dependent split-window algorithms-applications to ATSR and AVHRR data. IEEE transactions on geoscience and remote sensing, 34(2), 457-470. DOI: 10.1109/36.485123.
  • Gao, C., Qiu, S., Zhao, E. Y., Li, C., Tang, L. L., Ma, L. L., ... & Ren, L. (2017). Land surface temperature retrieval from FY-3C/VIRR data and its cross-validation with Terra/MODIS. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10(11), 4944-4953. DOI: 10.1109/JSTARS.2017.2728082.
  • Gao, C., Zhao, E., Li, C., Qian, Y., Ma, L., Tang, L., Jiang, X., & Huo, H. (2015). Study of aerosol influence on nighttime land surface temperature retrieval based on two methods. Advances in Meteorology, 2015, 1-16. doi.org/ 10.1155/2015/496458.
  • Jiang, G. M., & Li, Z. L. (2008). Split‐window algorithm for land surface temperature estimation from MSG1‐SEVIRI data. International Journal of Remote Sensing, 29(20), 6067-6074. doi.org/10.1080/01431160802235860.
  • Jiménez-munoz, J. C. & Sobrino, j. A. (2006). Error sources on the land surface temperature retrieved from thermal infrared single channel remote sensing data. International Journal of Remote Sensing, 27(5), 999–1014. doi.org/ 10.1080/01431160500075907.
  • Labbi, A., & Mokhnache, A. (2015). Derivation of split-window algorithm to retrieve land surface temperature from MSG-1 thermal infrared data. European Journal of Remote Sensing, 48 (1), 719-742. doi.org/10.5721/ EuJRS20154840.
  • Li, Z.L. (1990). L’émissivité spectrale en télédétection infrarouge thermique: mesure relative, analyse spectrale et impacts sur la détermination de la température de surface. Thesis, University of Strasbourg I, France, 163 pp.
  • Malkevich, M.S., & Gorodetsky, A.K. (1988). Determination of ocean surface temperature taking account of atmospheric effects by measurements of the angular IR-Radiation distribution of the “Ocean-Atmosphere” system made from the satellite “Cosmos-1151”. Remote sensing reviews, 3(3), 137-161, doi.org/10.1080/ 02757258809532093.
  • Qin, Z., & Karnieli, A. (2001). 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, 3719-3746. doi.org/10.1080/01431160010006971.
  • Sobrino, J.A., & Romaguera, M. (2004). Land surface temperature retrieval from MSG1-SEVIRI data. Remote Sensing of Environment, 92(2), 247-254. doi.org/10.1016/j.rse.2004.06.009.
  • Vergé-Dépré, G., Legrand, M., Moulin, C., Alias, A., & François, P. (2006). Improvement of the detection of desert dust over the Sahel using Meteosat IR imagery. Annales Geophysicae, 24(8), 2065-2073.doi.org/10.5194/angeo-24-2065-2006.
  • Zhao, E., Gao, C., & Yao, Y. (2020). New land surface temperature retrieval algorithm for heavy aerosol loading during nighttime from Gaofen-5 satellite data. Optics express, 28(2), 2583-2599. doi.org/10.1364/OE.382813.
There are 16 citations in total.

Details

Primary Language English
Subjects Photogrammetry and Remote Sensing
Journal Section Research Articles
Authors

Abdelkader Labbı 0000-0003-2278-5446

Publication Date March 13, 2021
Submission Date December 11, 2020
Acceptance Date February 2, 2021
Published in Issue Year 2021 Volume: 2 Issue: 1

Cite

APA Labbı, A. (2021). A Study of the Impact of Aerosols on The Estimation of Land Surface Temperature from Space Using Simulation of Satellite Data. Türk Uzaktan Algılama Ve CBS Dergisi, 2(1), 11-20. https://doi.org/10.48123/rsgis.839293