Modelling of ecosystem services “cooling effect” supply in the city of Тyumen

https://doi.org/10.35595/2414-9179-2021-3-27-196-209

View or download the article (Rus)

About the Authors

Valentina A. Dobryakova

University of Tyumen, Institute of Earth Sciences,
Volodarsky str., 6, 625003, Tyumen, Russia;
E-mail: v.a.dobryakova@utmn.ru

Liliia D. Sulkarnaeva

University of Tyumen, Institute of Earth Sciences,
Volodarsky str., 6, 625003, Tyumen, Russia;
E-mail: sulkarnaeva1992@mail.ru

Abstract

This article aims to identify the main factors influencing the supply of the “Cooling Effect” ecosystem service, which is important for creating a comfortable urban environment. The parameters of the ecosystem service “Cooling effect” (supply and demand) are expressed quantitatively as the difference between the surface temperatures and the maximum comfort temperature for the summer period (23°C) for the mathematical regression model of the process.

The results of field observations and analysis of space images allowed us to verify the cartographic basis of the Open Street Map and organize thematic data for modeling: we sorted natural objects by area (selected with an area of at least 1 hectare), buildings by the criterion of multi-story, roads by the criterion of the number of lanes. To determine the dependence of temperatures on the selected indicators, the urban area was covered with a hexagonal grid with a hexagon radius of 500 m. The cells (bins) of the constructed hexagonal grid were selected as the operational research units. Areas are calculated as a percentage within the bin, distances—as the nearest in meters from the bin to the specified objects in a straight line.

Calculations were performed in ArcGIS Pro software using tools from the Spatial Statistics—Spatial Relationship Modeling toolbox. The model building algorithm includes sequential launch of two analysis tools: Exploratory Regression and Ordinary Least Squares (OLS).

Based on the results of the work of the tools, the following were performed: interpretation and analysis of reports, messages and maps. As a result of the study, the main factors influencing the temperature distribution have been identified. The strongest variables are the area of multi-storey buildings and the distance to major roads. The third most important factor is the forest area.

Keywords

urban heat island, ecosystem services, spatial analysis, geographic information systems.

References

  1. Arnfield A. Two decades of urban climate research: a review of turbulence, exchanges of energy and water, and the urban heat island. International Journal of Climatology: a Journal of the Royal Meteorological Society, 2003. V. 23.1 (2003). P. 1 –26.
  2. Burkart K., Canário P., Breitner S., Schneider A., Scherber K., Andrade H., Alcoforado M.J., Endlicher W. Interactive short-term effects of equivalent temperature and air pollution on human mortality in Berlin and Lisbon. Environmental pollution, 2013. V. 183. P. 54–63.
  3. Chang C.R., Li M.H., Chang S.D. A preliminary study on the local cool-island intensity of Taipei city parks. Landscape and urban planning, 2007. V. 80 (4). P. 386–395.
  4. Getis A., Ord J.K. The Analysis of Spatial Association by Use of Distance Statistics. Geographical analysis, 1992. V. 24. P. 191–206.
  5. Haque U., Scott L.M., Hashizume M., Fisher E., Haque R., Yamamoto T., Glass G.E. Modelling malaria treatment practices in Bangladesh using spatial statistics. Malar Journal, 2012. V. 11. P. 11–63. DOI: 10.1186/1475-2875-11-63.
  6. Höppe P. The physiological equivalent temperature—a universal index for the biometeorological assessment of the thermal environment. International journal of Biometeorology, 1999. V. 43 (2). P. 71–75.
  7. Kolde Ya.K. Training materials on the theory of probability and mathematical statistics. Moscow: Vysshaja shkola, 1991. 157 p. (in Russian).
  8. Kowarik I., Bartz R., Brenck M. Ökosystemleistungen in der Stadt: Gesundheit Schützen und Lebens-Qualität Erhöhen. Berlin, Leipzig, 2016. 300 p.
  9. Kuttler W., Weber S., Schonnefeld J., Hesselschwerdt A. Urban/rural atmospheric water vapour pressure differences and urban moisture excess in Krefeld, Germany. International Journal of Climatology: A Journal of the Royal Meteorological Society. 2007. V. 27 (14). P. 2005–2015.
  10. Larsen L. Urban climate and adaptation strategies. Frontiers in Ecology and the Environment, 2015. V. 13 (9). P. 486–492.
  11. Mell I.C., Henneberry J., Hehl-Lange S., Keskin B. Promoting urban greening: Valuing the development of green infrastructure investments in the urban core of Manchester, UK. Urban forestry & urban greening, 2013. V  12.3. P. 296–306.
  12. Oke T.R. City size and the urban heat island. Atmospheric Environment, 1973 (1967). V. 7 (8). P. 769–779.
  13. Schär C., Jendritzky G. Hot news from summer 2003. Nature, 2004. V. 432 (7017). P. 559–560.
  14. Schär C., Vidale P.L., Lüthi D., Frei C., Häberli C., Liniger M.A., Appenzeller C. The role of increasing temperature variability in European summer heatwaves. Nature, 2004. V. 427 (6972). P. 332–336.
  15. Scherber K., Langner M., Endlicher W. Spatial analysis of hospital admissions for respiratory diseases during summer months in Berlin taking bioclimatic and socio-economic aspects into account. DIE ERDE–Journal of the Geographical Society of Berlin, 2013. V. 144 (3–4). P. 217–237.
  16. Stocker T.F., Qin D., Plattner G.-K., Tignor M., Allen S.K., Boschung J., Nauels A., Xia Y., Bex V., Midgley P.M. IPCC: Summary for Policymakers. Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge: Cambridge University Press, 2013. 28 p.
  17. Streutker D.R. Satellite-measured growth of the urban heat island of Houston, Texas. Remote Sensing of Environment, 2003. V. 85 (3). P. 282–289.
  18. Theory of statistics: textbook / ed. Gromyko G.L. 2nd edition, rev. M.: Infra, 2005. 476 p. (in Russian).

For citation: Dobryakova V.A., Sulkarnaeva L.D. Modelling of ecosystem services “cooling effect” supply in the city of Тyumen InterCarto. InterGIS. GI support of sustainable development of territories: Proceedings of the International conference. Moscow: MSU, Faculty of Geography, 2021. V. 27. Part 3. P. 196–209. DOI: 10.35595/2414-9179-2021-3-27-196-209 (In Russian)