1. Science
  2. Publications
  3. Information Processing Systems
  4. 1(156)'2019
  5. Modeling the tourist route using geoinformation technologies

Modeling the tourist route using geoinformation technologies

O. Pomortseva, M. Herasimenko
Annotations languages:


Description: The article describes the problems associated with the state of tourist services in Ukraine, namely in the city of Kharkov. The fact is that this segment of the service market is not sufficiently developed. And that is why the share of the contribution of the tourism business is quite small in the gross domestic product. A weak tourist infrastructure has been one of the obstacles to the effective development of the tourism industry in recent years. To solve the problem of the developing of the optimal tourist route, graph-theoretic methods and algorithms were used. The use of graphs is connected with the fact that they are the natural means of explaining complex navigational situations on an intuitive level. In cases of software development, graphs are used in the most cases. There are many effective algorithms for finding the shortest path on graphs. From our point of view, the best algorithm for building an optimal tourist route will be Dijkstra's algorithm, because of its relatively low computational complexity, ease of use and the possibility of software implementation on a machine. The development of the most optimal route between the points of interest, marked on maps (these are infrastructure objects, sights, natural objects and important places on the roads), the coordinates and the information on which are mapped ‒ this is the main priority for each program user, because it will save precious time and money. It was Dijkstra’s algorithm that was used to solve the applied problem of constructing a tourist route in the historical part of Kharkov. To implement the algorithm, the Python programming language embedded in the ArcGis software was chosen. This geoinformation system allows not only to create a cartographic basis, add attribute information to objects, but also to create program code for solving applied problems. The introduction of geoinformation technologies will allow to create a geoinformation model of the region for the tourism business aims, thereby, meet the requirements of the consumer. The creation of the applications that allow the tourist to make up optimal for him routes will lead to the development of the tourism industry.


Keywords: tourism, tourist infrastructure, tourist services, environment of tourist infrastructure objects

References

1. Trohimec, O.I. (2012), “Rozvitok turizmu v Ukraїnі ta ijogo strategіchne znachennya dlya nacіonal'noї ekonomіki” [Development of tourism in Ukraine and its strategic importance for the national economy], State and Region: A Science Magazine, No. 3, pp. 62-67.
2. State Statistics Service of Ukraine (2018), “Statistichniij zbіrnik “Turistichna dіyal'nіst' v Ukraїnі u 2017 rocі” [Statistical collection “Tourist activities in Ukraine in 2017”], Kyiv, 76 p.
3. Herasimenko, M.D. and Pomortseva, O.E. (2018), “Turistichna privablivіst mіsta Harkova. Problemi ta rіshennya” [Tourist attraction of the city of Kharkov. Problems and Solutions], Scientific-practical conference devoted to the international day of GIS, Kharkiv, pp. 92-95.
4. Barliani, I. (2015), “Ispol'zovanie geoinformacionnyh sistem v turisticheskom biznese” [The use of geo-information systems in the tourism business], Interexpo Geo-Sibir Journal, pp. 103-107, available at: www.cyberleninka.ru/article/n/ispolzovanie-geoinformatsionnyh-sistem-v-turisticheskom-biznese.
5. Pomortseva, O.E. (2018), “Vikoristannya geoіnformacіijnoї sistemi u proektuvannі іnfrastrukturi mіsta” [Use of the geographic information system in the design of the city infrastructure], International scientific and practical conference “Modern techniques, innovations and experience of practical application in the field of technical sciences”, Lublin, Republic of Poland, pp. 223-226.
6. Mitchell, A. (2005), The ESRI Guide to GIS Analysis, Volume 2: Spatial Measurements and Statistics, Esri Press, 252 р.
7. Poile, C. and Safayeni, F. (2016), Using computational modeling for building theory: A double-edged sword, Journal of Artificial Societies and Social Simulation, No. 19 (3), 8 р. https://doi.org/10.18564/jasss.3137.
8. Ananiij, V. (2009), “Algoritmy: vvedenie v razrabotku i analiz” [Algorithms: introduction to development and analysis], Williams, Moscow, 548 p.
9. Cormen, Thomas H., Leiserson, Charles E., Rivest, Ronald L. and Stein, Clifford (2009), Introduction to algorithms, The MIT Press, Cambridge, Massachusetts, 1312 p.
10. Filatova, T., Polhil,l J.G. and van Ewijk, S. (2016), Regime shifts in coupled socio-environmental systems: review of modelling challenges and approaches, Environmental Modelling & Software, No. 75, рр. 333-347. https://doi.org/10.1016/j.envsoft.2015.04.003.
11. Lorscheid, I., Heine, B-O. and Meyer, M. (2012), Opening the “black box” of simulations: increased transparency and effective communication through the systematic design of experiments, Computational and Mathematical Organization Theory, No. 18 (1), рр. 22-62. https://doi.org/10.1007/s10588-011-9097-3.
12. Cohn, A.G., Bennett, B., Gooday, J. and Gotts, N.M. (1997), Qualitative spatial representation and reasoning with the Region Connection Calculus, Geoinformatica, No. 1(3), рр. 275-316.

Reference:
 Pomortseva, O.Ye. and Herasymenko, M.D. (2019), “Rozrobka turystychnoho marshrutu za dopomohoiu heoinformatsiinykh tekhnolohii” [Modeling the tourist route using geoinformation technologies], Information Processing Systems, Vol. 1(156), pp. 37-43. https://doi.org/10.30748/soi.2019.156.05.