Analysis of the tourist destinations’ visiting using geographic information systems and the Python programming language
Mikhail Ya. Ponomarkov - Minister of Digital Development and Communications of Sverdlovsk Region. Ministry of Digital Development and Communications of Sverdlovsk Region
Mikhail A. Panov - Candidate of Economic Sciences, Associate Professor of the Department of Informational Technologies and Statistics. Ural State University of Economics
Abstract
The paper is devoted to analysing the dynamics of visiting tourist destinations using geographic information systems. The paper explores the possibilities of modern geographic information systems for visualisation and analysis of spatial data related to tourist flows in order to further optimise the management of tourist facilities and infrastructure planning. The methodological basis of the study is based on the conceptual framework of spatial analysis and the theory of sustainable tourism development, which allows for the integration of different data. The data on the attendance of tourist sites collected on the basis of mobile operators’ data using geographic information systems are used as an information base. The analysis of the obtained data and visualisation are performed using modern programming languages. The main results include identifying key trends in tourist behaviour, assessing the impact of infrastructural factors on visitation and developing recommendations for improving tourism services. The findings of the study confirm the effectiveness of using geographic information systems to solve planning and management tasks in the tourism industry, which contributes to improving the attractiveness and competitiveness of tourist destinations.
Keywords: geographical information systems; tourist destination; visitor dynamics; spatial analysis; tourism management; data visualisation; infrastructure; tourism planning
For citation: Ponomarkov M.Ya., Panov M.A. Analysis of the tourist destinations’ visiting using geographic. Digital models and solutions. 2024. Vol. 3, no. 3. Pp. 5–23. DOI: 10.29141/2949-477X-2024-3-3-1. EDN: CEFSWR.
