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Urban growth models are useful tools to understand the patterns and processes of urbanization. In recent years, the bottom-up approach of geo-computation, such as cellular automata and agent-based modeling, is commonly used to simulate urban landuse dynamics. This study has developed an integrated model of urban growth called agent-integrated irregular automata (AIIA) by using vector geographic information system environment (i.e. both the data model and operations). The model was tested for the city of San Marcos, Texas to simulate two scenarios of urban growth. Specifically, the study aimed to answer whether incorporating commercial, industrial and institutional agents in the model and using social theories (e.g. utility functions) improves the conventional urban growth modeling. By validating against empirical land-use data, the results suggest that a holistic framework such as AIIA performs better than the existing irregular-automata-based urban growth modeling.

Megacities are predominantly concentrated along coastlines, making them exposed to a diverse mix of natural hazards. The assessment of climatic hazard risk to cities rarely has captured the multiple interactions that occur in complex urban systems. We present an improved method for urban multi-hazard risk assessment. We then analyze the risk of New York City as a case study to apply enhanced methods for multi-hazard risk assessment given the history of exposure to multiple types of natural hazards which overlap spatially and, in some cases, temporally in this coastal megacity. Our aim is to identify hotspots of multi-hazard risk to support the prioritization of adaptation strategies that can address multiple sources of risk to urban residents. We used socioeconomic indicators to assess vulnerabilities and risks to three climate-related hazards (i.e., heat waves, inland flooding and coastal flooding) at high spatial resolution. The analysis incorporates local experts' opinions to identify sources of multi-hazard risk and to weight indicators used in the multi-hazard risk assessment. Results demonstrate the application of multi-hazard risk assessment to a coastal megacity and show that spatial hotspots of multi-hazard risk affect similar local residential communities along the coastlines. Analyses suggest that New York City should prioritize adaptation in coastal zones and consider possible synergies and/or tradeoffs to maximize impacts of adaptation and resilience interventions in the spatially overlapping areas at risk of impacts from multiple hazards.