利用GIS技术和元胞自动机对区域空间发展和区域间合作的多种社会经济情景进行建模

I. Musikhin, A. Karpik
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引用次数: 2

摘要

推进有效的空间规划以支持可持续发展和区域间合作已成为区域当局严重关注的问题。空间规划研究有助于识别经济集群并分析其不断变化的空间格局,这对于理解区域经济空间动态和潜在的区域间合作至关重要。为了支持决策者制定有效的空间发展计划,包括确定最适合的地区,采用基于地理信息系统的组合方法,以基于定量地图的分级适宜性来解释定性表达的多种社会经济情景,并提供了对该领土进行社会经济评估的正式方法。本研究基于GIS技术,结合集成的元胞自动机决策分析技术,提供了一种根据生成的区域空间和社会经济发展情景对研究区域进行社会经济评估的方法。该方法应用于俄罗斯远东地区的普里莫尔斯基和哈巴罗夫斯克边疆区。对投资者和区域当局提出的空间发展的社会经济情景进行了评估。生成的社会经济情景说明了如何将一套统一的空间和社会经济变量联系起来,并用于深入了解区域间的社会经济和空间发展。应用结果表明,该方法在确定最适合区域发展的单元区域方面具有优势。
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Use of GIS technology and cellular automata for modeling multiple socio-economic scenarios of regional spatial development and inter-regional cooperation
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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