Document Type : Research Article

Authors

Faculty of Environment, College of Engineering, University of Tehran, Tehran, Iran.

Abstract

One of the environmental problems today is the rising land surface temperature and the formation of heat islands in metropolitan areas, which have arisen due to the unplanned expansion of these cities. Satellite imagery is widely used in urban environmental studies to provide an integrated view and reduce costs and time. In this study, Landsat satellite imagery in TM, ETM+, and OLI sensors from 1984 to 2020, remote sensing techniques, and GIS is used to analyze the data, and SPSS software is employed to examine the correlation between the data. The results indicate that the land surface temperature in District 1 of Tehran has increased during the last 38 years. Moreover, land use in District 1 has changed significantly over this period, and urban land use increased from 16 % (1984) to 35 % (2020) while vegetation declined from 32 % to 14 %. The results of linear regression analysis show a significant correlation between satellite images and weather station data. The significance coefficient (Sig) in all stations is less than 0.05 with a 95 % confidence interval. Besides, the coefficient of variation (R) for all stations is above 80 %, and the coefficient R2 has a desirable value. The findings suggest that the trend of rising temperatures in District 1 of Tehran has become an environmental problem and the changes in land use such as declining vegetation and increasing the acceleration of urbanization are among the factors that affect it.

Keywords

Main Subjects

  1. Ahmed, (2018). Assessment of urban heat islands and impact of climate change on socioeconomic over Suez Governorate using remote sensing and GIS techniques. The Egyptian Journal of Remote Sensing and Space Sciences, 21(1), 15-25. https://doi.org/10.1016/j.ejrs.2017.08.001
  2. Akbari, (2000). Consideration of temperature distribution pattern of Tehran using Landsat TM thermal data. [MA dissertation, Tarbiat Modarres University]. https://ganj.irandoc.ac.ir. (In Persian).
  3. Al-Hatab, M., Amany, , & Lamia, T. (2018). Monitoring and assessment of urban heat islands over the Southern region of Cairo Governorate, Egypt. The Egyptian Journal of Remote Sensing and Space Sciences, 21(3), 311-323. https://doi.org/10.1016/j.ejrs.2017.08.008
  4. Chander, G., Markham, B., & Helder, (2009). Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors. Remote Sensing of Environment, 113. https://doi.org/10.1016/j.rse.2009.01.007
  5. El-Hadidy, Sh.M. (2021). The relationship between urban heat islands and geological hazards in Mokattam plateau, Cairo, Egypt. The Egyptian Journal of Remote Sensing and Space Sciences, 24. https://doi.org/10.1016/j.ejrs.2021.02.004
  6. Galdies, C., & Lau, H.S. (2020). Urban heat island effect, extreme temperatures and climate change: A case study of Hong Kong SAR. Climate Change, Hazards and Adaptation Options. https://link.springer.com/chapter/10.1007/978-3-030-37425-9_20
  7. Guo, A., Yang, J., Xiao, X., Xia, J., Jin, C., & Li, X. (2019). Influences of urban spatial form on urban heat island effects at the community level in China. Sustainable Cities and Society, 53. https://doi.org/10.1016/j.scs.2019.101972
  8. Harun, , Reda, E., Abdulrazzaq, A., Amer Abbas, A., Yusup, Y., & Zaki Sh.A. (2020). Urban heat island in the modern tropical Kuala Lumpur: Comparative weight of the different parameters. Alexandria Engineering Journal, 59. https://doi.org/10.1016/j.aej.2020.07.053
  9. Kabano, P., Lindley, S., & Harris, (2020). Evidence of urban heat island impacts on the vegetation growing season length in a tropical city. Landscape and Urban Planning, 206. https://doi.org/10.1016/j.landurbplan.2020.103989
  10. Koopmans, S., Heusinkveld, B.G., & Steeneveld, J. (2020). A standardized physical equivalent temperature urban heat map at 1-m spatial resolution to facilitate climate stress tests in the Netherlands. Building and Environment, 181. https://doi.org/10.1016/j.buildenv.2020.106984
  11. Lemus-Canovas, , Martin-Vide, J., Moreno-Garcia, M.C., & Lopez-Bustins, J.A. (2019). Estimating Barcelona's metropolitan daytime hot and cold poles using Landsat-8 Land Surface Temperature. Science of the Total Environment, 699. https://doi.org/10.1016/j.scitotenv.2019.134307
  12. Li, , Zhou, Y., Jia, G., Zhao, K., & Dong, J. (2021). Quantifying the response of surface urban heat island to urbanization using the annual temperature cycle model. Geoscience Frontiers, 13. https://doi.org/10.1016/j.gsf.2021.101141
  13. Lia, L., Zha, Y., & Zhang, J. (2020). Spatially non-stationary effect of underlying driving factors on surface urban heat islands in global major cities. International Journal of Applied Earth Observation and Geoinformation, 90. https://doi.org/10.1016/j.jag.2020.102131
  14. Liu, , Yang, M., Hou, Y., Zhao, Y., & Xue, X. (2021). Spatiotemporal evolution of island ecological quality under different urban densities: A comparative analysis of Xiamen and Kinmen Islands, Southeast China. Ecological Indicators, 124. https://doi.org/10.1016/j.ecolind.2021.107438
  15. Makhdoom, M., Darwish Sefat, A., Jafarzadeh, H., & Makhdoom, A. (2004). Environmental assessment and planning with geographic information systems "GIS". University of Tehran, Publishing and Printing Institute. https://www.gisoom.com/book/1826711/. (In Persian).
  16. Macintyre, H.L., Heaviside, C., Cai, X., & Phalkey, R. (2021). The winter urban heat island: Impacts on cold-related mortality in a highly urbanized European region for present and future climate. Environment International, 154. https://doi.org/10.1016/j.envint.2021.106530
  17. Mendez-Astudillo, , Lau, L., Tang, Y., & Moore, T. (2020). A new Global Navigation Satellite System (GNSS) based method for urban heat island intensity monitoring. International Journal of Applied Earth Observations and Geoinformation, 94. https://doi.org/10.1016/j.jag.2020.102222
  18. Portela, C.I., Massi, K.G., Rodrigues, T., & Alcântara, E. (2020). Impact of urban and industrial features on land surface temperature: Evidences from satellite thermal indices. Sustainable Cities and Society, 56. https://doi.org/10.1016/j.scs.2020.102100
  19. Rajeshwari, A., & Mani, N.D. (2014). Estimation of land surface temperature of Dindigul district using Landsat 8 data. International Journal of Research in Engineering and Technology, 3. https://ijret.org/volumes/2014v03/i05/IJRET20140305025.pdf
  20. Sadeghinia, , Alijani, B., Ziaeian, P., & Khaledi, S. (2013). Application of spatial autocorrelation techniques in the analysis of the thermal island of Tehran. Applied Research in Geographical Sciences, 30. https://www.sid.ir/en/Journal/ViewPaper.aspx?ID=354812. (In Persian).
  21. Sekertekin, A., & Zadbagher, (2021). Simulation of future land surface temperature distribution and evaluating surface urban heat island based on impervious surface area. Ecological Indicators, 122. https://doi.org/10.1016/j.ecolind.2020.107230
  22. Tepanosyan, G., Muradyan, V., Hovsepyan, A., Pinigin, G., Medvedev, A., & Shushanik Asmaryan, Sh. (2020). Studying spatial-temporal changes and relationship of land cover and surface urban heat island derived through remote sensing in Yerevan. Armenia Building and Environment, 187. https://doi.org/10.1016/j.buildenv.2020.107390
  23. United Nations Department of Economic and Social Affairs. (2019). World Urbanization Prospects: The 2018 Revision, ISBN (PDF): 9789210043144. https://doi.org/10.18356/b9e995fe-en
  24. 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, 1119-1131. https://doi.org/10.1080/01431169308904400
  25. Vasenev, , Varentsova, M., Konstantinov, P., Romzaykina, O., Kanareykina, I., Dvornikov, V., & Manukyana, Y. (2021). Projecting urban heat island effect on the spatial-temporal variation of microbial respiration in urban soils of Moscow megalopolis. Science of the Total Environment, 786. https://doi.org/10.1016/j.scitotenv.2021.147457
  26. Wang, , Yi, G., Zhou, X., Zhang, T., Bie, X., Li, J., & Ji, B. (2021). Spatial distribution and influencing factors on urban land surface temperature of twelve megacities in China from 2000 to 2017. Ecological Indicators, 125. https://doi.org/10.1016/j.ecolind.2021.107533