The results of the study of spatio-temporal changes in surface temperatures of Zaporizhya based on satellite data

Authors

  • Lyidmila Lischenko Scientific Centre for Aerospace Research of the Earth of the Institute of Geological Sciences of the National Academy of Sciences of Ukraine, Kyiv, Ukraine https://orcid.org/0000-0001-6766-6884
  • Alexandr Kudryashov Scientific Centre for Aerospace Research of the Earth of the Institute of Geological Sciences of the National Academy of Sciences of Ukraine, Kyiv, Ukraine

DOI:

https://doi.org/10.36023/ujrs.2021.8.3.198

Keywords:

land surface temperature, landscape functional areas, thermal profiling., urban heat island, thermal profiling, Landsat, Sentinel-2

Abstract

Zaporizhzhia is one of the largest industrial cities located in the central steppe part of Ukraine on both banks of the Dnieper. The presence of a large number of metallurgical, mechanical engineering, chemical and construction industrial facilities forms a powerful thermal island (UHI) which size varies in space and time. The distribution of surface temperatures within the thermal anomaly is influenced by the landscape-functional use of the territory and the established changes that occurred during the 33-year period according to the data obtained from the thermal channels of the Landsat series. The average increase in the land surface temperatures (LST) calculated for this period was 0.149 оС per year for July. The analysis of LST temperature curves according to the data of July and August has been carried out for three profiles that cross the majority of the landscape-functional areas of the city (residential, industrial and post-industrial). The landscape characteristics expressed in the satellite image as land cover are divided on the surface with a decreasing and increasing effect of temperature compared to the mean. Over time, a decrease in contrast between different land cover has been observed due to greater heating of the entire surface over the city and the establishment of a stable effect of UHI with an excess up to 14 оС in industrial areas. The annual increase in LST is in the range from 0.15 to 0.30 оС for the majority of the city. The maximum increase in temperature to 0.6 оС per year has been observed in the densely built-up Pivdennyi residential area and in the zones of industrial facilities in the Factory district of Zaporizhya. Only landscapes of water surfaces and separate agricultural croplands have a reducing thermal effect while the natural cover under meadows, wastelands and even wood vegetation within the city warms up to the mean values. Comparisons of the mean for the whole city of July and August LST has showed the rate of July to be 8 оС higher and temperature fluctuations in August become less amplitude by 2–3 оС.

References

Action Plan for Adaptation to the Consequences of Climate Change in the City of Zaporizhia. (2020). https://zp.gov.ua/uk/sessions/99/resolution/41273.pdf. (in Ukrainian)

Alavipanah, Sadroddin, Wegmann, Martin, Qureshi, Salman, Weng, Qihao, Koellner, Thomas. (2015). The role of vegetation in mitigating urban land surface temperatures: a case study of Munich. Germany during the warm season / Sustainability, 15 (7). 4689–4706 doi:10.3390/su7044689.

Hidalgo, García D., Arco, Díaz J. (2021). Spatial and Multi-Temporal Analysis of Land Surface Temperature through Landsat 8 Images: Comparison of Algorithms in a Highly Polluted City (Granada). Remote Sensing, 13. 1012. https://doi.org/10.3390/rs13051012/

Kottmeier, C., Corsmeierm U., Biegert, C. (2007). Effects of Urban Land Use on Surface Temperature in Berlin: Case Study. doi:10.1061/(ASCE)0733-9488(2007)133:2(128)

Li, Xiaoma, Zhou, Weiqi, Ouyang, Zhiyun, Xu, Weihua, Zheng, Hua. (2012). Spatial pattern of greenspace affects land surface temperature: evidence from the heavily urbanized Beijing Metropolitan area, China, Landscape Ecology, 27 (6). 887–898. https://link.springer.com/article/10.1007/s10980-012-9731-6

Lischenko, L., Pazynych, N., Filipovych, V. (2019). Summer surface temperature distribution analysis of Mykolayiv city based on the Landsat series thermal infrared data. Ukrajinsjkyj zhurnal dystancijnogho zonduvannja Zemli, 21, 49–59. https://doi.org/10.36023/ujrs.2019.21.148. (in Ukrainian)

Lischenko, L. (2020). Monitoring of land surface temperature of post-industrial areas and industrial sites in Kyiv using remote sensing data. Ukrajinsjkyj zhurnal dystancijnogho zonduvannja Zemli, 25. 17–27. https://doi.org/10.36023/ujrs.2020.25.172 (in Ukrainian)

Maimaitiyiming, Matthew, Ghulam, Abduwasit, Tiyip, Tashpolat, Pla, Filiberto, Latorre-Carmona, Pedro, Halik, Umut, Sawu, Mamat, Caetan, Mario. (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. http://repositori.uji.es/xmlui/handle/10234/1355

Stankevich, S. A., Filipovich, V. E., Lubsky, N. S., Krylova, A. B., Kritsuk, S. G., Brovkina, ... Tronin A. A. (2015). Intercalibration of methods for restoring the thermodynamic temperature of the surface of an urbanized area based on materials of thermal space imagery. Ukrajinsjkyj zhurnal dystancijnogho zonduvannja Zemli, 7. 14–23. https://ujrs.org.ua/ujrs/article/view/59/77. (in Russian)

Subhanil, Guha, Himanshu, Govil, Anindita, Dey, Neetu, Gill. (2018). Analytical study of land surface temperature with NDVI and NDBI using Landsat 8 OLI and TIRS data in Florence and Naples city, Italy. European Journal of Remote Sensing, 51:1. 667–678. doi:10.1080/22797254.2018.1474494

Voogt, J. (2014). How researchers measure urban heat islands. Department of Geography, University of Western Ontario London ON Canada. https://www.epa.gov/sites/production/files/2014-07/documents/epa_how_to_measure_a_uhi.pdf

Wienert, Uwe, Kuttler, Wilhelm. (2005.) The dependence of the urban heat island intensity on latitude. A statistical approach. Meteorologische Zeitschrift, 14 (5). 677–686. doi:10.1127/0941-2948/2005/0069

Published

2021-09-21

Issue

Section

Earth observation data applications: Challenges and tasks