Sustainable Land-Use Planning to Improve the Coastal Resilience of the Social-Ecological Landscape

Abstract

The dynamics of land-use transitions decrease the coastal resilience of the social-ecological landscape (SEL), particularly in light of the fact that it is necessary to analyze the causal relationship between the two systems because operations of the social system and the ecological system are correlated. The purpose of this study is to analyze the dynamics of the coastal SEL and create a sustainable land-use planning (SLUP) strategy to enhance coastal resilience. The selected study site was Shindu-ri, South Korea, where land-use transitions are increasing and coastal resilience is therefore decreasing. Systems thinking was used to analyze the study, which was performed in four steps. First, the issues affecting the coastal area in Shindu-ri were defined as coastal landscape management, the agricultural structure, and the tourism industry structure. Second, the main variables for each issue were defined, and causal relationships between the main variables were created. Third, a holistic causal loop diagram was built based on both dynamic thinking and causal thinking. Fourth, five land-uses, including those of the coastal forest, the coastal grassland, the coastal dune, the agricultural area, and developed sites, were selected as leverage points for developing SLUP strategies to increase coastal resilience. The results show that "decrease in the size of the coastal forest", "decrease in the size of the coastal dune", and "increase in the size of the coastal grasslands" were considered parts of a land-use plan to enhance the resilience of the Shindu-ri SEL. This study developed integrated coastal land-use planning strategies that may provide effective solutions for complex and dynamic issues in the coastal SEL. Additionally, the results may be utilized as basic data to build and implement coastal land-use planning strategies.

Operationalization and Measurement of Social-Ecological Resilience: A Systematic Review

“…In general, papers using modelling are based on the exploitation of a resource stock by methods such as fishing [52], forest management [53], and agricultural production [54]. However, Kim et al (2017) [55] also assessed modelling by addressing three issues that they identified in their study area: coastal landscape management, agricultural structure, and tourism industry structure. This method provides a way to test the system for tipping points without putting the actual system at risk [56].…”

Integrated Multi-Criteria Decision-Making Methods for the Sustainability of Historical–Cultural Structures on the Trabzon Coastline

“…On the other hand, it has also decreased the quality of the coastal landscape. As a result, this deterioration of the landscape has reduced the structure of the tourism industry [27,63]. Although regional activities and festivals were assessed mostly in terms of economic factors in planning studies regarding festivals, visitors, and tourism, they are obviously important in terms of tourist use today [63].…”

“…This method was later developed by Nijkamp et al [63]. It is based on making a preference by comparing the alternatives in a systematic analysis [64,65].…”

Evolutionary Characteristics and Trade-Offs’ Development of Social–Ecological Production Landscapes in the Loess Plateau Region from a Resilience Point of View: A Case Study in Mizhi County, China

“…Resilience can be understood as the capacity of systems to maintain a basic structure and function after being disturbed, which emphasizes the adjustment and adaptation of human society in the context of environmental changes and provides a basic logical framework for the study of human-land relations [19][20][21]. The definition of SELPR is the capacity of SELPs to withstand disturbances without changing the system state [12,13,22]. Compared with traditional social-ecological resilience evaluation, the outstanding characteristics of SEPLR evaluation are represented by the spatial representation of landscape system elements and the quantitative characterization of resilience heterogeneity [23][24][25].…”