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Short abstract:

This study outlines the opportunities and risks of GIS integrated with AI and ML to improve disaster preparedness. Identifying opportunities and risks benefits disaster management professionals to understand and influence policy design for climate change action and disaster management.

Long abstract:

Climate change is leading to more frequent and severe disasters, highlighting the inadequacy of the current disaster response capabilities of government agencies and emergency teams across the globe. Although geographic information systems (GIS) have been useful for disaster preparedness modeling and emergency response planning, the emergence and integration of artificial intelligence (AI) and machine learning (ML) algorithms can be leveraged to improve disaster management and preparedness. This study utilized a systematic review methodology to outline the opportunities and risks of GIS integrated with AI And ML to improve disaster preparedness. First, integrating GIS with AI and ML creates new opportunities to improve predictive capabilities that can be leveraged to explore weather patterns and historical records, enabling more accurate predictions of extreme events and disasters. The predictability of AI-powered GIS enables government agencies and emergency teams to issue early warnings, plan evacuations, and mobilize resources, potentially saving lives and reducing the impact of such events. Second, risks associated with AI and ML result from issues related to data quality, bias, and over-reliance on existing data to perform predictive analysis. If data is biased or incomplete, models can generate inaccurate or unfair predictions, worsening existing disaster preparedness and response inequalities. Identifying opportunities and risks benefits disaster management professionals to understand and influence policy design for climate change action and disaster management.