This study develops an integrative framework for embedding Big Data, Internet of Things (IoT), and Geographic Information Systems (GIS) into the implementation of Strategic Environmental Assessment (SEA), with the aim of enhancing urban environmental governance in Indonesia. While SEA has been widely adopted as a policy instrument for sustainable development, its effectiveness remains constrained by limited data integration, delayed monitoring processes, and weak institutional coordination. This research addresses these limitations by proposing a data-driven approach that aligns digital technologies with environmental assessment practices. Methodologically, the study employs a qualitative research design combining document analysis, systematic literature review, and policy framework evaluation. Empirical insights are further enriched through stakeholder-oriented analysis of technology applications in urban environmental management. The findings demonstrate that the integration of Big Data, IoT, and GIS enables real-time environmental monitoring, improves predictive capacity, and supports evidence-based policymaking. Moreover, these technologies facilitate enhanced transparency and multi-stakeholder engagement, thereby strengthening the governance dimension of SEA. However, the study also identifies critical barriers to implementation, including bureaucratic inertia, limited technical capacity, fragmented data systems, and insufficient political commitment. These constraints highlight the need for institutional reform and capacity development alongside technological adoption. This research contributes to the literature by advancing a novel conceptual and operational framework that bridges the gap between digital innovation and environmental governance. It extends existing SEA models by incorporating data-driven governance principles and provides actionable insights for policymakers and urban planners. The study emphasizes that effective integration of digital technologies in SEA requires not only technological readiness but also robust data governance, inter-agency collaboration, and adaptive policy frameworks.
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