Key coastal landscape patterns for reducing flood vulnerability
- Authors
- Kim, Min; Song, Kihwan; Chon, Jinhyung
- Issue Date
- 10-Mar-2021
- Publisher
- ELSEVIER
- Keywords
- Resilience; Coastal green infrastructure; Fuzzy overlay analysis; Spatial statistics; Landscape metrics
- Citation
- SCIENCE OF THE TOTAL ENVIRONMENT, v.759
- Indexed
- SCIE
SCOPUS
- Journal Title
- SCIENCE OF THE TOTAL ENVIRONMENT
- Volume
- 759
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/49477
- DOI
- 10.1016/j.scitotenv.2020.143454
- ISSN
- 0048-9697
- Abstract
- The purpose of the present study was to examine key coastal landscape patterns related to flood vulnerability to support resilience strategies for coastal green infrastructure. To this end, we assessed the flood vulnerability of coastal landscapes based on three indicators: exposure, including precipitation; sensitivity, including elevation, slope, soil, drainage, and density; and adaptability, including urban land-use. Subsequently, we investigated whether landscape patterns, including the shape index and subdivision index, would affect flood vulnerability through a multivariate regression analysis, which allowed us to determine key coastal landscape patterns. At the regional scale, including the overall study site, we suggested strategies for green infrastructure planning, focusing on patch shapes of forest, grassland, and water. At each local scale, a variety of landscape patterns were selected: the contiguity index of used area for the central subregion: the division index of forests, the contiguity of water, and the fractal dimension index of used area for the northeast subregion; the circumscribing circle index of barren and wetlands for the northwest subregion; the division and fractal index of forests for the southwest subregion; and the division index of forests and the fractal index of water for the southeast subregion. Based on the derived landscape patterns of each subregion, we propose coastal green infrastructure planning with resilience strategies. (C) 2020 Elsevier B.V. All rights reserved.
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Collections - College of Life Sciences and Biotechnology > Division of Environmental Science and Ecological Engineering > 1. Journal Articles
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