Digital methods for assessing the quality of the urban environment

https://doi.org/10.58224/2618-7183-2024-7-4-9
The article considers various methods for assessing the quality of the urban environment, their content, identifies strengths and weaknesses. In addition, the main users of these methods, who is the target audience, who the data is intended for and the possibility of making management decisions based on this data were identified. The article also presents a methodology developed by the authors that allows assessing the quality of urban areas by five main parameters using digital methods based on open city data. This will allow obtaining an objective picture of the state of the urban space and making adequate management decisions. This work is based on an integrated approach to assessing urbanized space, developing universal assessment models that allow correlating different-quality characteristics of city subsystems into a single assessment system, which will allow obtaining a quantitative assessment of the state of spatial indicators of the city. Digital methods of managing the life cycle of urban development systems imply entering a new stage of forecasting, programming and modeling the development of urbanized systems, eliminating serious consequences of urban development errors with large budget losses when implementing poor-quality development scenarios. The priority task of reforming the public authority system is to create a qualitatively new level of public administration efficiency, including in matters of spatial development of territories. The development of a methodological basis for modeling spatial development processes lays the foundation for creating new technological tools, developing digital platforms for spatial modeling of territorial systems development based on a big data system. As a result of the study, the main criteria and indicators of environmental quality were developed. The criteria matrix includes such evaluation blocks as transport and mobility; functionality of space; safety of space; accessibility; improvement of the environment. The evaluation criteria were tested in the Shaksha residential area and refined during a field survey of the city territory.
[1] Chen D., Lu X., Liu X., Wang X. Measurement of the eco-environmental effects of urban sprawl: theoretical mechanism and spatiotemporal differentiation. Ecological Indicators. 2019. 105. P. 6 – 15.
[2] Mandeli K. Public Space and the Challenge of Urban Transformation in Cities of Emerging Economies: Jeddah Case Study. Cities. 2019. 95. P. 2 – 3.
[3] Sanchez-Sepulveda M., Fonseca D., Franquesa J., Redondo E: Virtual interactive innov tions applied for digital urban transformations. Mixed Approach. Future Gener. Comput. Syst. 2019. 91. P. 371 – 381.
[4] The UNECE – ITU Smart Sustainable Cities Indicators J. United Nations, Economic and Social Council. 2015. 4. P. 1 – 13.
[5] Smart Cities: Smart Technologies and Infrastructure for Energy, Water, Transportation
[6] Buildings, and Government: Business Drivers, City and Supplier Profiles Market Analysis and Forecasts Research Report: Executive Summary Boulder (CO, USA: Navigant Consult ing, Inc). 2011. P. 88 – 112.
[7] Sweet E.L., Etienne H. Journal of Planning Education and Research. 2011. 31 (3). P. 332 – 339 DOI:10.1177/0739456X11414715
[8] Yilbas B S, Patel F and Karatas C. Laser Surface Engineering Waugh J.L.G. Woodhead Publishing. 2014. P. 97 – 105.
[9] Dessouky N. Procedia Environmental Sciences. 2016. 34. P. 401 – 410. Doi:10.1016/j.proenv.2016.04.035
[10] Pryadko I.P., Ivanova Z.I. Biosphere and social processes in the aspect of the design of the urban environment Industrial and civil construction. 2017. 10. P. 12 – 17.
[11] Maruna M., Rodic D.M., Colic R. Remodelling urban planning education for sustainable development: the case of Serbia. Int. J. Sustain. High. Educ. 2018. 19 (4). P. 658 – 680.
[12] Balova S.L., de Velazco J.J.H.G., Polozhentseva I.V., Chernavsky M.Y., Shubtsova L.V. The formation of the concept of smart sustainable city with the purpose of environmental protection. J. Environ. Managem. Tourism. 2021. 12 (5). P. 1269 – 1275
[13] Digital Talent. Road to 2020 and beyond: A national strategy to develop Canada’s talent in a Global Digital Economy. Information and communications technology council, Ottawa, 7-8 2017.
[14] Lagutenkov A. Smart city: from concept to implementation. Sci. and Life. 2018. 8. P. 102 – 106 (2018)
[15] Ivashova V.A., Tokareva G.V., Agalarova E.G., Nadtochiy Y.B., Yushchenko I.V. Social practice of urban environment quality assessment. In: IOP Conference Series: Materials Science and Engineering. 775. IOP Publishing Ltd, Samara. 2020. P. 3 – 5.
[16] Jagodzińska K., Sanetra-Szeliga J., Purchla J., Balen K.V., Thys C., Vandesande A., Auwera S.V. Cultural Heritage Counts for Europe: Full Report. 2015. P. 9 – 11.
[17] Karakova T.V., Kolesnikov S.A., Radulova J.I., Vorontsova Y.S. Shopping streets as an instrument of architectural and design formation of consumer and investment attractiveness of functional-planning structure of city. In: IOP Conference Series: Materials Science and Engineering. 775. IOP Publishing Ltd, Samara. 2020. P. 2 – 8.
[18] Kudasheva D.R., Baimuratova S.Kh. The concept of development of the territory of the Dolgoe Lake in Ufa. Archyort. 2016. 2 (4). P. 8 – 9.
[19] Vysokovskiy A. Theory. Grey Matter, Moscow. 2015. P. 163 – 165.
[20] Debord G. Psychogeography. Ad Marginem Press, Moscow. 2017. P. 75 – 78.
[21] Vavilonskaya T.V. Architectural and historical environment of the Samara Volga region: Formation, state, concept of sustainable development: Thesis for the degree of Doctor of Architecture. Bibliography, Nizhny Novgorod. 2017. P. 232 – 250.
[22] Adli M. Stress and the City. Tochka Publishing group, Moscow, 2019. P. 1 – 12.
Baymuratova S.Kh., Baymuratov R.F., Kudasheva D.R., Plotnikova M.N., Kinyagulov N.R., Ovechkina E.K., Khannanova E.A. Digital methods for assessing the quality of the urban environment. Construction Materials and Products. 2024. 7 (4). 9. https://doi.org/10.58224/2618-7183-2024-7-4-9