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A Comparative Analysis of Urban Land Use Sustainability Using a Cloud-Based Decision Support Framework with Rule-Based Spatial Analytics: The Cases of Barcelona and Izmir
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DOI：10.3390/land15081448.png)
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Abstract
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This study presents a comparative analysis of urban land-use sustainability in Barcelona and Izmir using a four-tier Decision Support Framework (DSF) supported by automated Google Earth Engine workflows. The framework integrates open satellite data, cloud-based spatial analysis, and policy-oriented indicators derived from Sentinel-2 and Landsat imagery. Outputs include LULC classification, NDVI, NDBI, a Sentinel-2-derived relative thermal proxy (sLST), the Composite Environmental Biophysical Index (CEBI), and distance-weighted urban expansion pressure. Classification accuracy reached 86.85% for Barcelona and 91.03% for Izmir. The cities exhibited distinct morphological and environmental profiles. Izmir had higher vegetation density than Barcelona (NDVI: 0.320 vs. 0.142), while harmonized Landsat summer LST values were similar in 2023, with Barcelona slightly warmer than Izmir (39.343 °C vs. 39.146 °C). Accordingly, sLST was used for relative intra-urban thermal assessment rather than absolute inter-city comparison. CEBI indicated higher environmental biophysical performance in Izmir (0.526) than Barcelona (0.446), interpreted strictly within the vegetation, thermal, and built-up components included in the index. Barcelona’s compact urban fabric exhibited stronger expansion pressure, whereas Izmir’s geographically constrained morphology indicated a more controlled growth dynamic. The findings demonstrate the value of transparent cloud-based spatial analytics for reproducible, evidence-based urban planning.
Keywords:
spatial analytics
rule-based LULC
decision support framework
urban sustainability
sustainable land management
Google Earth Engine
urban expansion pressure
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