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Vol. 3 No. 02 (2022)

Articles

Impact of land cover change on land surface temperature over Greater Beirut Area – Lebanon

https://doi.org/10.38094/jastt302174

Published 2022-10-25

  • Ali Khyami

Ali Khyami
Department of Geography, Faculty of Humanities, Lebanese University, Beirut, Lebanon

Abstract

Remote sensing (RS) technology has been used together with geographic information systems (GIS) to determine the LC types, retrieve LST, and analyze their relationships. The term Greater Beirut Area (GBA) is used to refer to the city of Beirut and its suburbs, which witnessed rapid urban growth after the end of the civil war in the last decade of the twentieth century, due to the increase in the number of its inhabitants, and the prosperity and development of sectors such as; industrial, trade, tourism, and construction. These factors led to a wide change in land cover (LC) types and increased land surface temperature (LST). The results showed an increase in built-up areas by 29.1% and agricultural lands by 6%, while bare land, forests, and seawater decreased by 28.5%, 4.9%, and 1.9%, respectively. These changes caused large differences in the LST between built-up areas and other LC types. The highest LST recorded was in built-up areas (33.03°C in 1985, and 34.01°C in 2020), followed by bare lands (32.61 °C in 1985 and 33.49°C in 2020), cropland (31.23°C in 1985 and 32.17°C in 2020), forest (30.08°C in 1985 and 30.47°C in 2020), and water (24.97°C in 1985 and 28.15°C in 2020). Consequently, converting different LC types into built-up areas led to increases in LST and a changed microclimate.

Keywords

Land surface temperature (LST), Land Cover (LC), Greater Beirut Area (GBA), Geographic Information System (GIS), Remote Sensing (RS)

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References

  1. Z. Sun, R. Ma, and Y. Wang, "Using Landsat data to determine land use changes in Datong basin, China," Environmental Geology, vol. 57, pp. 1825-1837, 2008 2008.
  2. N. R. Khwarahm, "Spatial modeling of land use and land cover change in Sulaimani, Iraq, using multitemporal satellite data," Environmental Monitoring and Assessment, vol. 193, no. 3, pp. 1-18, 2021 2021.
  3. S. Pal and S. Ziaul, "Detection of land use and land cover change and land surface temperature in English Bazar urban center," The Egyptian Journal of Remote Sensing and Space Sciences, vol. 20, pp. 125-145, 2017 2017.
  4. V. Vijayaraj, N. Younan, and C. O'Hara, "Concepts of image fusion in remote sensing applications," presented at the International Symposium on Geoscience and Remote Sensing, 2006, 2006.
  5. A. Rajeshwari and D. Mani, "Estimation of land surface temperature of dindigul district using Landsat 8 data," International journal of research in engineering and technology, vol. 3, no. 5, pp. 122-126, 2014 2014.
  6. S. Gorgani, M. Panahi, and F. Rezaie, "The Relationship between NDVI and LST in the urban area of Mashhad, Iran," presented at the International Conference on Civil Engineering Architecture & Urban Sustainable Development, 2013, 2013.
  7. Y. T. Mustafa, R. T. Ali, and R. M. Saleh, "Monitoring and evaluating land cover change in the Duhok city, Kurdistan region-Iraq, by using remote sensing and GIS," International Journal of Engineering Inventions, vol. 1, no. 11, pp. 28-33, 2012.
  8. F. Faour and M. Mhawej, "Mapping Urban Transitions in the Greater Beirut Area Using Different Space Platforms," Land, vol. 2073, no. 445X, pp. 941-956, 2014 2014.
  9. R. T. Mzuri, A. A. Omar, and Y. T. Mustafa, "Spatiotemporal Analysis of Land Surface Temperature and Vegetation Changes in Duhok District, Kurdistan Region, Iraq," The Iraqi Geological Journal, pp. 68-81, 2022.
  10. G. Chander and B. Markham, "Revised Landsat-5 TM radiometric calibration procedures and postcalibration dynamic ranges," IEEE Transactions on Geoscience and Remote Sensing, vol. 41, no. 11, pp. 2674-2677, 2003 2003.
  11. O. Orhan and M. Yakar, "Investigating Land Surface Temperature Changes Using Landsat Data in Konya, Turkey," Remote Sensing and Spatial Information Sciences, vol. XLI, no. B8, pp. 285-289, 2016 2016.
  12. T. Carlson and D. Ripley, "On the relation between NDVI, fractional vegetation cover, and leaf area index," Remote Sensing of Environment, vol. 62, no. 3, pp. 241-252, 1997 1997.
  13. A. Sobrino, C. Jiménez-Muñoz, and L. Paolini, "Land surface temperature retrieval from Landsat TM 5," Remote Sensing of Environment, vol. 90, no. 4, pp. 434-440, 2004 2004.
  14. Q. Weng, "A remote sensing–GIS evaluation of urban expansion and its impact on surface temperature in the Zhujiang Delta, China," International Journal of Remote Sensing, vol. 22, no. 10, pp. 1999-2014, 2001 2001.
  15. L. Thomas, R. Kiefer, and J. Chipman, Remote Sensing and Image Interpretation, 7th ed. Wiley, 2015.
  16. Y. T. Mustafa, "Multi-temporal satellite data for land use/cover (LULC) change detection in Zakho, Kurdistan Region-Iraq," Environmental Remote Sensing and GIS in Iraq, pp. 161-180, 2020.
  17. R. J. Jensen, Introductory Digital Image Processing, 3rd ed. New York: Prentice Hall, 2005.
  18. A. Kuzucu and F. Balcik, "Testing the potential of vegetation indices for land use/cover classification using high resolution data," Remote Sensing and Spatial Information Sciences, vol. IV-4, no. W4, pp. 279-283, 2017 2017.
  19. K. Thakkar, V. Desai, A. Patel, and M. Potdar, "Impact assessment of watershed management programs on land use/ land cover dynamics using remote sensing and GIS," Remote Sensing Applications: Society and Environment, vol. 5, pp. 1-15, 2017 2017.
  20. Y. Mustafa, "Spatiotemporal analysis of vegetation cover in Kurdistan region-Iraq using MODIS image data," Journal of Applied Science and Technology Trends, vol. 1, no. 1, pp. 01-07, 2020.
  21. R. Monserud and R. Leemans, "Comparing global vegetation maps with the Kappa statistic," Ecological Modelling, vol. 62, no. 4, pp. 275-293, 1992 1992.

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