Unplanned and rapid urban growth requires the reckless expansion of infrastructure including water, sewage, energy, and transportation facilities, and thus causes environmental problems such as deterioration of old towns, reduction of open spaces, and air pollution. To alleviate and prevent such problems induced by urban growth, the accurate prediction and management of urban expansion is crucial. In this context, this study aims at modeling and predicting urban expansion in Seoul metropolitan area (SMA), Korea, using GIS and XAI techniques. To this end, we examined the effects of land-cover, socio-economic, and environmental features in 2007 and 2019, within the optimal radius from a certain raster cell. Then, this study combined the extreme gradient boosting (XGBoost) model and Shapley additive explanations (SHAP) in analyzing urban expansion. The findings of this study suggest urban growth is dominantly affected by land-cover characteristics, followed by topographic attributes. In addition, the existence of water body and high ECVAM grades tend to significantly reduce the possibility of urban expansion. The findings of this study are expected to provide several policy implications in urban and environmental planning fields, particularly for effective and sustainable management of lands.

This study attempts to identify the direction of urban regeneration projects in declining areas by using the concept of urban resilience to cope with climate change and disaster. To this end, urban resilience was classified into a Green Resilient Infrastructure (GRI) and an Interactive Safety System (ISS), through a review of previous studies, and categorized into vulnerability, adaptability, and transformability. A total of 12 detailed indicators were derived and indexed using Euclidean distance. Using the indicators, three Korean urban regeneration targets, in Daegu, Mokpo, and Seosan, were selected to evaluate resilience before and after the urban regeneration plan. Consequently, the postplanning resilience index improved in all three target sites, compared to before the regeneration plan. Additionally, previously the regeneration plan showed lower index values in comparison to places not designated as urban regeneration areas. These results suggest that urban resilience needs to be considered in future urban regeneration projects, and that resilience indicators can be used as a means to set the direction of urban regeneration projects. To improve the overall resilience of a region, these indices can help local government establish a reference point for urban resilience in its region.