Use of GIS technology and cellular automata for modeling multiple socio-economic scenarios of regional spatial development and inter-regional cooperation

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Abstract

The advancement of effective spatial planning to support sustainable development and inter-regional cooperation has become an issue of serious concern for regional authorities. Spatial planning research helps to identify economic clusters and analyze their changing spatial patterns, which is important for understanding regional economic space dynamics and potential inter-regional cooperation. To support decision-makers in the development of efficient plans of spatial development encompassing the identification of the best-suited territories, a combined Geographic Information System (GIS) based approach to interpret qualitatively expressed multiple socio-economic scenarios in quantitative map-based terms of graded suitability, and a formalized approach to the socio-economic evaluation of the territory is offered. Based on GIS technology coupled with integrated cellular automata decision analysis techniques, the study provides a method that performs socio-economic assessment of the study area according to the generated scenarios of regional spatial and socio-economic development. The proposed method is applied to Primorsky and Khabarovsk Krais, located in the Russian Far East. Socio-economic scenarios of spatial development initiated by investors and regional authorities were assessed and evaluated. The generated socio-economic scenarios illustrate how the unified set of spatial and socio-economic variables can be linked and used to gain insights into inter-regional socio-economic and spatial development. The application results demonstrate the advantage of the proposed method in identifying the best-suited unit areas for targeted regional development.

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Musikhin, I., & Karpik, A. (2023). Use of GIS technology and cellular automata for modeling multiple socio-economic scenarios of regional spatial development and inter-regional cooperation. Geo-Spatial Information Science, 26(1), 71–93. https://doi.org/10.1080/10095020.2023.2182237

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