A Framework for a Geospatial Predictive Decision Support System for Hazard Risk Profiling
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Natural hazards consistently pose significant challenges to urban communities, particularly in regions vulnerable to these threats, such as Catbalogan City, Samar, Philippines. Effective hazard risk profiling is essential for proactive disaster preparedness, resource allocation, and policy development. However, current approaches utilized by Catbalogan City and many Local Government Units (LGUs) in the Philippines continue to rely on static hazard maps and descriptive assessments, which limit predictive capability and decision-support effectiveness. This paper presents a conceptual, expert-validated framework for a Geospatial Predictive Decision Support System (GPDSS) to enhance hazard risk profiling and disaster preparedness. The study synthesizes findings from existing hazard-mapping, predictive modeling, and decision-support literature using a systematic review, a design science research approach, and a structured framework development process. The findings reveal persistent reliance on static data, regression-based analyses, and limited integration of decision-support mechanisms. These findings serve as the foundation for the proposed GPDSS framework, which integrates spatiotemporal geospatial datasets, GIS-based analysis, predictive modeling using machine learning techniques, and AI-assisted policy interpretation. Domain experts evaluated the framework, confirming its conceptual relevance, usability, scalability, and innovation for local disaster-risk governance. Rather than a deployed system, the proposed GPDSS is positioned as a governance-oriented framework that offers conceptual advantages over traditional hazard-mapping approaches by enabling predictive risk assessment, interactive visualization, and policy-oriented decision support. The study introduces a scalable, adaptive, and innovative framework intended to guide future system development and implementation for disaster-risk governance in hazard-prone localities in the Philippines.
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