Increases in particulate matter in cities threaten both public health and ecosystems. Street trees, which are a corridor-type green infrastructure capable of absorbing particulate matter, have been promoted as one possible solution to this problem. However, planting selected trees solely with the goal of reducing particulate matter may adversely affect street tree ecosystem resilience by inhibiting species diversity. This study aims to investigate urban street tree planting strategies that reduce particulate matter while maintaining ecosystem resilience. To this end, a study site in Suwon, South Korea was selected, and street tree planting scenarios were developed based on the selected site information. A scenario analysis was conducted using a system dynamics model. The model simulated the long-term trends under each scenario regarding the amount of particulate matter absorbed by the trees and the changes in species diversity. The analysis results clearly show that strategic planting of street trees while focusing on only a specific purpose—reducing particulate matter—can adversely affect ecosystem resilience. The scenario analysis also revealed that increasing the number of street trees while maintaining a balance among various species is the best option for reducing particulate matter without degrading species diversity. Additionally, the results support the need to plant evergreen species to consider the winter season.

Floods in coastal areas are caused by a range of complex factors such as typhoons and heavy rainfall, and this issue has become increasingly serious as interference has occurred in the social-ecological system in recent years. Given the structural limitations and high maintenance costs of the existing gray infrastructure, the need for a nature-based restoration plan utilizing green infrastructure has been raised. The purpose of this study is to simulate the restoration process through the quantification of green infrastructure effects along with resilience in disaster-prone coastal areas, and to present it as nature-based restoration planning. For this purpose, first, a disaster-prone area was derived from Haeundae-gu, Busan, Republic of Korea, which was affected by typhoons. In order to simulate the runoff from typhoon “Chaba” in the target area and the effects of reducing the runoff of green infrastructure, relevant data was collected and a model constructed. Finally, the effects of the green infrastructure as applied to the disaster-prone area were quantified by means of resilience and a nature-based restoration plan was presented. As a result of this study, first, the runoff reduction effect was greatest when the maximum biotope area ratio of 30% was applied to the artificial ground. In the case of the green roof, the effect was the greatest 6 h following the typhoon passing through, and the effects of the infiltration storage facility was greater 9 h following the same. Porous pavement exhibited the lowest runoff reduction effect. In terms of resilience, it was found that the system was restored to its original state after the biotope area ratio of 20% was applied. This study is significant in that it analyzes the effects of green infrastructure based upon the concept of resilience and connects them to nature-based restoration planning. Based on this, it will be provided as an important tool for planning policy management to effectively respond to future coastal disasters.

Urban areas face increasing environmental challenges, including fine dust pollution and climate change, which significantly impact public health and urban resilience. To address these issues, this study explores the integration of Nature-based Solutions (NbSs) and landscape architecture processes to develop a systematic approach for enhancing urban environmental outcomes. Through a comprehensive review of prior studies, the strengths and weaknesses of NbSs and landscape architecture processes were analyzed, leading to the development of the Nature-based Landscape Process (NLP), which synthesizes the key principles of both approaches. The Dongmyeong Elementary School Fine Dust Mitigation Forest Project was analyzed as a case study to evaluate the applicability of the NLP. This project, implemented using traditional landscape processes, was critically reviewed to identify areas where NbS principles could enhance ecological, social, and functional outcomes. The findings highlight how the integration of NbS principles into landscape architecture processes can address existing gaps and improve project sustainability and precision. This study provides practical insights into the application of the NLP in urban landscape projects, contributing to the development of strategies that align with long-term sustainability and climate adaptation goals.