Open Access

ARTICLE

Assessing the Potential of Urban Blue Spaces for Sustainable Mobility in Bucharest: A GIS-Based Multi-Criteria Analysis

Mihnea-Ștefan Costache^1,*, Simona-Elena Paraschiva², Teodora-Patricia Pătru²

1 Simion Mehedinţi Doctoral School, Faculty of Geography, University of Bucharest, Bucharest, Romania
2 Humanistic and Economic Geography Department, Faculty of Geography, University of Bucharest, Bucharest, Romania

* Corresponding Author: Mihnea-Ștefan Costache. Email:

Revue Internationale de Géomatique 2026, 35, 351-371. https://doi.org/10.32604/rig.2026.083243

Received 31 March 2026; Accepted 25 May 2026; Issue published 18 June 2026

Abstract

Urban blue spaces are increasingly recognized as critical components of sustainable cities. However, a significant gap exists in understanding their role not just as recreational areas, but as functional mobility corridors, especially within urban fabric of Eastern Europe countries. This study addresses this gap by assessing the accessibility and integration potential of blue infrastructure within Bucharest, Romania. The novelty of the research lies in the development of the Blue Areas Accessibility Index (BAAI), using a GIS-based Multi-Criteria Analysis (MCA). Eight spatial parameters were standardized using Likert scale and weighted using the Analytic Hierarchy Process to develop the Blue Areas Accessibility Index (BAAI). The resulting index was validated based on participatory GIS data collected from 103 respondents, offering a hybrid methodological approach that combines objective spatial modelling with subjective citizen perception. Results reveal significant spatial disparities in blue space potential accessibility. Only 1.53% of the city exhibits very high accessibility, primarily concentrated along the main hydrographic networks: Dâmboviţa River, Colentina lake chain, and some selected central lakes, while approximately 27% of the territory falls into low or very low accessibility classes, particularly in southern and peripheral parts of the city, in Districts 4 and 5. The model demonstrated strong predictive performance (AUC = 0.816), confirming the reliability of the index. The findings identify key structural barriers, including industrial zones and fragmented infrastructure, that limit the integration of blue spaces into Bucharest’s mobility network. This study provides a novel spatial framework for incorporating blue infrastructure into sustainable mobility planning.

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Keywords

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