Spatial planning is at the core of national land and urban development. Many countries and cities seek sustainable development through various means such as coordinated environmental planning, environmental assessment, and internalization of environmental analysis and planning. A Planning Support System (PSS) is a GIS (Geographic Information System)-based, spatial decision-making support system that incorporates a variety of theories and pertinent models. This study adopted the “What if?” model to design an alternative spatial plan that includes generation of predictive scenarios and is relatively easy to use. In the cities studied, we identified a total of six scenarios based on the main drivers of development—namely, population and spatial policies. Subsequently, we assessed the alternatives for their environmental impact, preparing sensitivity maps for each major environmental issue in the target area (natural ecosystem, air and microclimate, natural disasters). One projected advantage of the “What if?” model is that its digital visualization of proposed plans may improve public awareness and involvement. Furthermore, the tool is expected to be highly useful in ensuring the objectivity of quantitative analyses. However, it is necessary to develop a PSS that is both standardized and tailored to the particular needs of each area. Finally, the development of an e-governance system will be beneficial in ensuring public access to the decision making process.

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.

Since the 2000s, there has been a rapid increase in studies related to resilience in various fields, including natural sciences and engineering, social sciences, culture/arts/sports, and medical sciences/psychology. To analyze the trend in domestic research on resilience, this study conducted a frequency analysis on 6,590 studies, including 371 studies related to climate change and urban disasters, and a keyword & network analysis of 301 studies with abstracts. The frequency of domestic research on urban climate change and disasters has been increasing since 2011. Frequency and keyword analysis showed that “region” and “disaster” drew the maximum attention from researchers in the fields of climate change and urban disasters, and such studies have focused on keywords such as “management,” “impact,” and “assessment.” The LDA(Latent Dirichlet Allocation) and network analysis showed that the key topics of related studies in Korea could be summarized as 1) impact of disasters, 2) management plans for response, and 3) establishment of an assessment framework. The objectives of this study are to determine the trend in domestic research on resilience in the fields of climate change and urban disasters, to set the direction for further research, and to provide a knowledge base for future investigations. The result of this study are also expected to provide a basis for consideration in setting the space and the extent of disasters to deal with resilience.

This study used Landsat 8 satellite imagery to identify land surface temperature (LST) and to create a normalized difference vegetation index (NDVI) for Daegu City for analysis of different land cover types. LST for Daegu showed distinctive patterns depending on the NDVI and land cover had negative correlations with LST and NDVI. In addition, urban and industrial areas accounted for the top 20% of LSTs while forests and waters accounted for the bottom 20%. Forest areas had a high NDVI value of 0.447, average NDVI values were highest for deciduous and lowest for coniferous forests. The results of this study provide a better understanding of the role of vegetative cover in the thermal environment in urban areas which has deteriorated due to climate change. This information will help validate urban planning policies that protect green spaces.

With the increase in disasters and damage caused by climate change, the global population and infrastructure are gradually being concentrated in urban areas as a result of rapid urbanization, and concerns for disasters in urban areas are increasing. Vulnerability to and risks of disasters are particularly serious issues in declining areas with poor physical and social environment. The improvement of urban resilience is necessary to prevent disasters in these areas, and an index for evaluating the current resilience level in these areas is necessary. To determine the suitability of evaluation index application for disaster resilience in declining areas, this study generated a list of 24 evaluation indices by reviewing published studies on this topic and examined the applicability of these indices in a survey conducted with 30 experts. The independence of each index was assessed through policy network analysis. In addition, the relevance and applicability of the indices were determined, and their effectiveness was assessed using the fuzzy multiple-criteria decision making method. Lastly, the priorities of the evaluation indices were suggested by combining the two analysis methods mentioned above. The results of this study will likely contribute to the development of an evaluation index for effective evaluation of urban resilience in declining areas.