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A terrain-based method for selecting potential mountain ridge protection areas in South Korea

Author

Listed:
  • Hee Han
  • Woodam Chung
  • Jungeun Song
  • Ara Seol
  • Joosang Chung

Abstract

Mountain ridges are valued by the Korean people as major and critical sources of natural resources and environment. Despite their recognised values, continuous exploitation and infrastructure development in forestlands have been causing large-scale degradation in mountains throughout the country. In response to this problem, our study supports recent efforts by the government to designate protection areas across the country. We build on the traditional classification of mountain ridges and apply a terrain-based spatial model to derive mountain ridge area boundaries. Based on the well-known mountain ridge system of the Korean peninsula, established in 1769, our approach was to select mountain ridgelines and boundaries using a terrain-based spatial model. The selected areas are generally located at high elevations with undulating terrain. They include a relatively large portion of ecologically important areas. A large portion of non-nationally owned forest is also found in the selected areas. Ecological importance and property rights would likely cause significant debate and conflicts among different social groups regarding designation of legally binding protection areas. Our model provides an explicit, scientific basis for the rigorous evaluation and area prioritisation as part of the protection area designation process. Application of our model can facilitate conversation on the country’s mountain ridge asset and public participation in the decision-making process.

Suggested Citation

  • Hee Han & Woodam Chung & Jungeun Song & Ara Seol & Joosang Chung, 2016. "A terrain-based method for selecting potential mountain ridge protection areas in South Korea," Landscape Research, Taylor & Francis Journals, vol. 41(8), pages 906-921, November.
  • Handle: RePEc:taf:clarxx:v:41:y:2016:i:8:p:906-921
    DOI: 10.1080/01426397.2016.1173657
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