Geoinformation modelling of social space of the city of Tashkent

Lola Gulyamova

doi:10.30533/scidata-2023-14-06.

VAK Russia 1.6.20 UDC 528.94 CSCSTI 36.33

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GEOINFORMATION MODELLING OF SOCIAL SPACE OF THE CITY OF TASHKENT Geoinformation modelling of social space of the city of Tashkent

АА Аа

Published in Spatial Data: Science, Research and Technology · Volume 14, Issue 1 · Pages 30–48 · Rubric: Geoinformatics, cartography

DOI: https://doi.org/10.30533/scidata-2023-14-06.

Received: 29.05.2023 Accepted: 23.06.2023 Published: 17.10.2025

Authors

Lola Gulyamova

Russian Federation

ABSTRACT

The article deals with methodological issues of geoinformation modeling of social space (SS) on the example of the city of Tashkent. The purpose of the study is based on a geospatial approach that allows spatial analysis, assessment and geoinformation modeling of the SS. Research objectives include: 1. Establish the leading factors that determine the properties of the SS. 2. Develop a cartographic model of SS. The paper used materials for the study: 1. Data from official statistics of the "Open Data" section on the portal of the Government of the Republic of Uzbekistan. 2. Cartographic materials of the city of Tashkent (including electronic maps). 3. Remote sensing materials posted on the Google Earth Pro portal. 4. Materials of outsourcing OpenStreetMap. 5. Housing rental data obtained from sociological surveys and data from official sources and social networks. The methods of regression analysis, field theory and graphs were used to obtain the following parameters of the SS score. Results of the study: 1. The regularities of the territorial distribution of the main factors determining the SS were examined. 2. The characteristic features of the SS that are amenable to geoinformation modeling have been identified. 3. For the first time, a map for assessing the joint venture of the city of Tashkent has been compiled. 4. A 3-point scale has been adopted, taking into account the main factors: 1. Connectivity of individual zones of the joint venture. 2. Transport security. 3. Demographic component. The results obtained can serve as a basis for improving urban planning methods to improve SS. The identified patterns of territorial distribution of the main factors make it possible to solve the problems of improving the quality of SS and developing plans for the development of urban infrastructure.

KEYWORDS

social space, geoinformation modelling, spatial assessment

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Editor-in-Chief, editorial board chair

EDITOR-IN-CHIEF Nadezhda Rostislavovna KAMYNINA PhD in Engineering, Doctor of Economics, Associate Professor; Rector of the Moscow State University of Geodesy and Cartography; Member of the Bologna Process Follow-up Group (BFUG); Executive Secretary of the Working Group of the Ministry of Science and Higher Education of the Russian Federation on the Bologna Process; Member of the Working Group on Spatial Data Infrastructure of the CIS Interstate Council on Geodesy, Cartography, Cadastre, and Remote Sensing, member of the Russian Federation's team of experts on higher education reform under the Erasmus+ program; Awarded the Medal of the Ministry of Education and Science of the Russian Federation "For Contribution to the Implementation of State Education Policy."

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GOST

Gulyamova L. X. Geoinformation modelling of social space of the city of Tashkent // Spatial Data: Science, Research and Technology. 2025. no. 1. pp. 30-48. DOI: https://doi.org/10.30533/scidata-2023-14-06.. (Date of access 11.10.2026).

MLA

Lola Gulyamova. "Geoinformation modelling of social space of the city of Tashkent." Spatial Data: Science, Research and Technology 14.1 (2025): 30-48. DOI: https://doi.org/10.30533/scidata-2023-14-06..

APA

Gulyamova L. X. (2025). Geoinformation modelling of social space of the city of Tashkent. Spatial Data: Science, Research and Technology, 14(1), 30-48. https://doi.org/10.30533/scidata-2023-14-06.

Chicago

Lola Gulyamova. "Geoinformation modelling of social space of the city of Tashkent." Spatial Data: Science, Research and Technology 14, no. 1 (2025): 30-48. https://doi.org/10.30533/scidata-2023-14-06..

WIKI

{{cite journal | author = Gulyamova L. X. | title = Geoinformation modelling of social space of the city of Tashkent | journal = Spatial Data: Science, Research and Technology | year = 2025 | volume = 14 | issue = 1 | pages = 30-48 | doi = 10.30533/scidata-2023-14-06. }}

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GEOINFORMATION MODELLING OF SOCIAL SPACE OF THE CITY OF TASHKENT Geoinformation modelling of social space of the city of Tashkent

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