Mapping Urban Site Suitability Analysis Using Sentinel-2 Data for Bayelsa State, Nigeria
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Keywords:
Urban Site Suitability, Google Earth Engine, Sentinel-2, Multi-Criteria Decision Analysis, Bayelsa State, Remote Sensing.Abstract
Accelerated urban growth in coastal areas challenges sustainable progress, especially in environmentally vulnerable regions like Bayelsa State, Nigeria. Traditional methods for assessing urban site suitability are often prolonged, rigid, and lack detailed spatial data crucial for strategic planning. This study introduces a resilient framework using Sentinel-2 satellite images and Google Earth Engine (GEE) to identify areas suitable for urban development. By combining Multi-Criteria Decision Analysis (MCDA) with remote sensing data, it assesses key geographical factors like land use/land cover (LULC), vegetation density (NDVI), distance to water bodies, and elevation. The methodology harnesses the multispectral capabilities of the Sentinel-2 Multi-Spectral Instrument (MSI) to produce high-resolution suitability assessments for Bayelsa State. The analysis reveals that 4% of the area exhibits very high suitability, 18% high suitability, 32% moderate suitability, 32% low suitability, and 13% very low suitability. While considerable tracts demonstrate elevated suitability for urban expansion, particularly within the Yenagoa metropolis, significant impediments persist due to extensive wetlands and flood-prone zones. This study underscores the effectiveness of GEE in managing and processing vast geospatial datasets, offering an adaptable and scalable model for urban strategists operating in regions characterized by limited data availability.
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