한국환경복원기술학회지 (Journal of the Korean Society of Environmental Restoration Technology)

  • 제26권3호
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  • Pages.1-17
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  • 2023
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  • 1229-3032(pISSN)
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  • 2733-5011(eISSN)
한국환경복원기술학회 (The Korea Society of Environmental Restoration Technology)
권호 표지
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자연공원 용도지구 설정을 위한 환경공간정보와 SOM(Self-Organizing map)을 활용한 지역 특성 도출 - 태안해안국립공원을 대상으로 -

Deduction of regional characteristics using environmental spatial information and SOM (Self-Organizing map) for natural park zoning - Focused on Taeanhaean National Park -

  • 이성희 (서울대학교 환경대학원 협동과정조경학) ;
  • 손용훈 (서울대학교 환경대학원 환경설계학과 )
  • Lee, Sung-Hee (Interdisciplinary Program in Landscape Architecture, Seoul National University) ;
  • Son, Yong-Hoon (Graduate School of Environmental Studies, Seoul National University)
  • 투고 : 2023.02.27
  • 심사 : 2023.04.27
  • 발행 : 2023.06.30
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초록

Korea's natural parks are managed by dividing them into four use districts: nature preservation district, natural environment district, cultural heritage district, and park village district within the park under the goal of 'conservation and sustainable use of natural parks'. However, the use districts divided in this way are designated by reflecting the results derived from the simple drawing overlapping method, and there is a limit in that objective and scientific evidence for this is insufficient. In addition, in Taeanhaean National Park, the case of this study, only a very small area of less than 1% of the nature preservation district is designated, and the natural environment district that serves as a buffer space is designated on an excessively wide scale, making it difficult to efficiently manage the national park. Therefore, the use district is not fulfilling its role. In this study, the purpose of this study was to present a method for analyzing the spatial characteristics of natural parks using environmental indicators and unsupervised learning analysis methods to set the use districts of natural parks. In this study, evaluation indicators that can evaluate the natural and human environments were derived, and the distribution patterns for each indicator were analyzed. Afterwards, by applying Self-Organizing Map (SOM) analysis, one of the unsupervised learning analysis methods, districts with similar characteristics were derived in Taeanhaean National Park, and the characteristics of each district were analyzed. As a result of the study, 7 districts with different characteristics were derived in Taeanhaean National Park, and by examining the contribution of each indicator together, it was possible to reveal that each district had different representative characteristics even though it was an adjacent area. This study evaluated natural parks by comprehensively considering the indicators of the natural and human environments. In addition, the SOM method used in the study is meaningful in that it can provide scientific and objective grounds for the existing zoning and apply it to the management plan.

키워드

과제정보

본 논문은 정부(과학기술정보통신부)의 재원으로 한국연구재단의 중견연구사업(과제명 : 이용자 참여 데이터와 공간정보를 통합한 경관질 평가 모델 개발) 지원을 받아 수행되었습니다(2021R1A2C109486012).

참고문헌

  1. Bacao, F., Lobo, V. and Painho, M.(2005) Self-organizing maps as substitutes for k-means clustering. In Computational Science-ICCS 2005: 5th International Conference, Atlanta, GA, USA, May 22-25, 2005, Proceedings, Part III 5 (pp. 476-483). Springer Berlin Heidelberg.
  2. Bagan, H., Takeuchi, W., Kinoshita, T., Bao, Y. and Yamagata, Y. (2010). Land cover classification and change analysis in the Horqin Sandy Land from 1975 to 2007. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 3(2), 168-177. https://doi.org/10.1109/JSTARS.2010.2046627
  3. Borhidi, A.(1995) Social behaviour types, the naturalness and relative ecological indicator values of the higher plants in the Hungarian flora. Acta Bot Hung 39: 97-181.
  4. Bruner, A. G., R. E. Gullison, R. E. Rice and G. A. Da Fonseca(2001) Effectiveness of parks in protecting tropical biodiversity. science 291(5501): 125-128. https://doi.org/10.1126/science.291.5501.125
  5. Clark, S., Sisson, S. A. and A. Sharma(2020) Tools for enhancing the application of self-organizing maps in water resources research and engineering. Advances in Water Resources 143: 103676.
  6. Das, S., P. P. Adhikary, P. K. Shit and B. Bera(2021) Urban wetland fragmentation and ecosystem service assessment using integrated machine learning algorithm and spatial landscape analysis. Geocarto International 1-19.
  7. Dittrich, A., R. Seppelt, T. Vaclavik and A.F. Cord(2017) Integrating ecosystem service bundles and socio-environmental conditions-A national scale analysis from Germany. Ecosystem Services 28: 273-282. https://doi.org/10.1016/j.ecoser.2017.08.007
  8. Dramstad, W.E., M.S. Tveit, W.J. Fjellstad and G.L.A. Fry(2006) Relationships between visual landscape preferences and map-based indicators of landscape structure. Landscape and urban planning 78(4): 465-474. https://doi.org/10.1016/j.landurbplan.2005.12.006
  9. Frank, S., C. Furst, L. Koschke, A. Witt and F. Makeschin(2013) Assessment of landscape aesthetics-Validation of a landscape metrics-based assessment by visual estimation of the scenic beauty. Ecological indicators 32: 222-231. https://doi.org/10.1016/j.ecolind.2013.03.026
  10. Fu, M., J. Tian, Y. Ren, J. Li, W. Liu and Y. Zhu(2019). Functional zoning and space management of three-river-source national park. Journal of Geographical Sciences 29(12): 2069-2084. https://doi.org/10.1007/s11442-019-1705-z
  11. Geneletti, D. and I. van Duren(2008) Protected area zoning for conservation and use: A combination of spatial multicriteria and multiobjective evaluation. Landscape and urban planning 85(2): 97-110. https://doi.org/10.1016/j.landurbplan.2007.10.004
  12. Ge, G., Z. Shi, Y. Zhu, X. Yang and Y. Hao(2020) Land use/cover classification in an arid desert-oasis mosaic landscape of China using remote sensed imagery: Performance assessment of four machine learning algorithms. Global Ecology and Conservation 22: e00971.
  13. Gosal, A. S., I. R. Geijzendorffer, T. Vaclavik, B. Poulin, and G. Ziv(2019) Using social media, machine learning and natural language processing to map multiple recreational beneficiaries. Ecosystem Services 38: 100958.
  14. Gosal, A. S., and G. Ziv(2020) Landscape aesthetics: Spatial modelling and mapping using social media images and machine learning. Ecological Indicators 117: 106638.
  15. Grantham, H. S., A. Duncan, T. D. Evans, K. R. Jones, H. L. Beyer, R. Schuster, J. Walston, J. C. Ray, J. G. Robinson, M. Callow, T. Clements, H. M. Costa, A. DeGemmis, P. R. Elsen, J. Ervin, P. Franco, E. Goldman, S. Goetz, A. Hansen, E. Hofsvang, P. Jantz, S. Jupiter, A. Kang, P. Langhammer, W. F. Laurance, S. Lieberman, M. Linkie, Y. Malhi, S. Maxwell, M. Mendez, R. Mittermeier, N. J. Murray, H. Possingham, J. Radachowsky, S. Saatchi, C. Samper, J. Silverman, A. Shapiro, B. Strassburg, T. Stevens, E. Stokes, R. Taylor, T. Tear, R. Tizard, O. Venter, P. Visconti, S. Wang and J. E. M. Watson(2020) Anthropogenic modification of forests means only 40% of remaining forests have high ecosystem integrity. Nature communications 11(1): 1-10. https://doi.org/10.1038/s41467-019-13993-7
  16. Gu, Q., H. Hu, L. Ma, L. Sheng, S. Yang, X. Zhang, M. Zhang, K. Zheng and L. Chen(2019) Characterizing the spatial variations of the relationship between land use and surface water quality using self-organizing map approach. Ecological Indicators 102: 633-643. https://doi.org/10.1016/j.ecolind.2019.03.017
  17. Hermes, J., C. Albert and C. von Haaren(2018) Assessing the aesthetic quality of landscapes in Germany. Ecosystem services 31: 296-307. https://doi.org/10.1016/j.ecoser.2018.02.015
  18. Hilker, T., M. A. Wulder, N. C. Coops, J. Linke, G. McDermid, J. G. Masek, F. Gao and J. C. White(2009) A new data fusion model for high spatial-and temporal -resolution mapping of forest disturbance based on Landsat and MODIS. Remote Sensing of Environment 113(8): 1613-1627. https://doi.org/10.1016/j.rse.2009.03.007
  19. Hull, V., W. Xu, W. Liu, S. Zhou, A. Vina, J. Zhang, M. Tuanmu, J. Huang, M. Linderman, X. Chen, Y. Huang, Z. Ouyang and J. Liu(2011) Evaluating the efficacy of zoning designations for protected area management. Biological Conservation 144(12): 3028-3037. https://doi.org/10.1016/j.biocon.2011.09.007
  20. Huang, F., K. Yin, J. Huang, L. Gui and P. Wang(2017) Landslide susceptibility mapping based on self-organizing-map network and extreme learning machine. Engineering Geology 223: 11-22. https://doi.org/10.1016/j.enggeo.2017.04.013
  21. Hunziker, M. and F. Kienast(1999) Potential impacts of changing agricultural activities on scenic beauty - a prototypical technique for automated rapid assessment. Landscape ecology 14(2): 161-176. https://doi.org/10.1023/A:1008079715913
  22. IUCN and World Commission on Protected Areas(WCPA)(2017) IUCN Green List of Protected and Conserved Areas: Standard, Version 1.1. Gland, Switzerland.
  23. Jalas, J.(1955) Hemerobe und hemerochore Pflanzenarten: Ein terminologischer Reformversuch. Acta Soc. Pro Fauna Flora Fenn 72: 1-15.
  24. Ji, C. Y.(2000) Land-use classification of remotely sensed data using Kohonen self-organizing feature map neural networks. Photogrammetric engineering and remote sensing 66(12): 1451-1460.
  25. Kalteh, A. M., P. Hjorth and R. Berndtsson(2008) Review of the self-organizing map (SOM) approach in water resources: Analysis, modelling and application. Environmental Modelling & Software, 23(7): 835-845.
  26. Kim, D. E. and Y. H. Son(2021) Evaluation of Perceived Naturalness of Urban Parks Using Hemeroby Index. Journal of the Korean Institute of Landscape Architecture 49(2): 89-100. https://doi.org/10.9715/KILA.2021.49.2.089
  27. Kim, Y. M., S. Zerbe, and I. Kowarik(2002) Human impact on flora and habitats in Korean rural settlements. Preslia 409-419.
  28. Kohonen, T.(1998). The self-organizing map. Neurocomputing 21(1-3): 1-6. https://doi.org/10.1016/S0925-2312(98)00030-7
  29. Koo, K.(2020) Application of an ecological engineering approach in evaluating protected area at local scales. Journal of Environmental Impact Assessment 29(2): 144-155.
  30. Koo, K.A. and S.U. Park(2020) Prioritizing ecologically important areas under land-use changes in Jeju Island, Jeju, Korea. Journal of the Korean Geographical Society 55(3): 253-264.
  31. Koo, K.A., C.M. Im and B.Y. Yang(2022) Advancement on an Ecosystem-based Assessment System to Determine a New Special-purpose District in Terms of National Park Management. The Geographical Journal of Korea 56(4): 353-366. https://doi.org/10.22905/kaopqj.2022.56.4.4
  32. Kowarik, I.(1988) Zum Einfluss des Menschen auf Flora undVegetation. Theoretische Konzepte und ein Quantifizierungsansatz amBeispiel von Berlin (West). Berlin. Schriftenreihe des Fachbereichs. Landschaftsentwicklung der TU Berlin Berlin 56(1): 280.
  33. Krajter Ostoic, S., A. M. Marin, M. Kicic and D. Vuletic, D(2020) Qualitative exploration of perception and use of cultural ecosystem services from tree-based urban green space in the city of Zagreb (Croatia). Forests 11(8): 876.
  34. Krausman, P.R.(1999) Some basic principles of habitat use. Grazing behavior of livestock and wildlife 70: 85-90.
  35. Liu, X. and J. Li(2008) Scientific solutions for the functional zoning of nature reserves in China. Ecological Modelling 215(1-3): 237-246. https://doi.org/10.1016/j.ecolmodel.2008.02.015
  36. Ministry of Environment(2007) Study on objectification of ecosystem protection area designation standards.
  37. Ministry of Environment(2008) 2nd National Park Feasibility Study Criteria and Natural Park System Improvement Research Report.
  38. Ministry of Environment(2019) 3rd National Park Feasibility Study Criteria and Natural Park System Improvement Research Report.
  39. Nagendra, H.(2002) Opposite trends in response for the Shannon and Simpson indices of landscape diversity. Applied geography 22(2): 175-186. https://doi.org/10.1016/S0143-6228(02)00002-4
  40. Park, Y., H. Lee, K. Kim, G. Lee, J. Choi, S. Heo and G. Seo(2008) Development of designation criteria for ecological protected areas and its application methodology. Journal of Environmental Impact Assessment 17(3): 177-188.
  41. Park, Y. S., Y. S. Kwon, S. J. Hwang and S. Park(2014) Characterizing effects of landscape and morphometric factors on water quality of reservoirs using a self-organizing map. Environmental Modelling & Software 55: 214-221.
  42. Peng, J., X. Chen, Y. Liu, H. Lu and X. Hu(2016) Spatial identification of multifunctional landscapes and associated influencing factors in the Beijing-Tianjin-Hebei region, China. Applied Geography 74: 170-181. https://doi.org/10.1016/j.apgeog.2016.07.007
  43. Peng, J., X. Hu, S. Qiu, J. Meersmans and Y. Liu(2019) Multifunctional landscapes identification and associated development zoning in mountainous area. Science of the Total Environment 660: 765-775. https://doi.org/10.1016/j.scitotenv.2019.01.023
  44. Plexida, S.G., A.I. Sfougaris, I.P. Ispikoudis and V.P. Papanastasis(2014) Selecting landscape metrics as indicators of spatial heterogeneity-a comparison among Greek landscapes. International Journal of Applied Earth Observation and Geoinformation 26: 26-35. https://doi.org/10.1016/j.jag.2013.05.001
  45. Polasky, S., E. Nelson, D. Pennington and K.A. Johnson(2011) The impact of land-use change on ecosystem services, biodiversity and returns to landowners: a case study in the state of Minnesota. Environmental and Resource Economics 48(2): 219-242. https://doi.org/10.1007/s10640-010-9407-0
  46. Sengl, P., M. Magnes, L. Erdos and C. Berg(2017) A test of naturalness indicator values to evaluate success in grassland restoration. Community Ecology 18(2): 184-192. https://doi.org/10.1556/168.2017.18.2.8
  47. Sharp, R., H.T. Tallis, T. Ricketts, A.D. Guerry, S.A. Wood, R.C. Kramer and K. Vigersto(2014) InVEST user's guide. The Natural Capital Project: Stanford, CA, USA.
  48. Slater, S. J., R. W. Christiana and J. Gustat(2020) Peer Reviewed: Recommendations for keeping parks and green space accessible for mental and physical health during COVID-19 and other pandemics. Preventing chronic disease 17.
  49. Song, S., Z. Liu, C. He and W. Lu(2020) Evaluating the effects of urban expansion on natural habitat quality by coupling localized shared socioeconomic pathways and the land use scenario dynamics-urban model. Ecological Indicators 112: 106071.
  50. Sun, X., Z. Jiang, F. Liu and D. Zhang(2019) Monitoring spatio-temporal dynamics of habitat quality in Nansihu Lake basin, eastern China, from 1980 to 2015. Ecological Indicators 102: 716-723. https://doi.org/10.1016/j.ecolind.2019.03.041
  51. Terrado, M., S. Sabater, B. Chaplin-Kramer, L. Mandle, G. Ziv and V. Acuna(2016) Model development for the assessment of terrestrial and aquatic habitat quality in conservation planning. Science of the total environment 540: 63-70. https://doi.org/10.1016/j.scitotenv.2015.03.064
  52. Ahn, T.M., Heo, H.Y., Lee, J.Y., Yoon, M.H., Shin, M.J. and J.K. Choi(2009) The Study on the Management Suggestion and Current Conditions of Marine and Coastal National Park in Korea. Journal of National Park Research 1(1):13-28.
  53. Visconti, P., S. Butchart, T. Brooks, P. Langhammer, D. Marnewick, S. Vergara, A. Yanosky and J. Watson(2019) Protected area targets post-2020. Science 364(6437): 239-241. https://doi.org/10.1126/science.aav6886
  54. Walz, U. and C. Stein(2014) Indicators of hemeroby for the monitoringof landscapes in Germany. Journal for Nature Conservation 22(3):279-289. https://doi.org/10.1016/j.jnc.2014.01.007
  55. Winter, S.(2012) Forest naturalness assessment as a component of biodiversity monitoring and conservation management. Forestry 85(2): 293-304. https://doi.org/10.1093/forestry/cps004
  56. Xu, W., X. Li, S. L. Pimm, V. Hull, J. Zhang, L. Zhang, Y. Xiao, H. Zheng and Z. Ouyang(2016) The effectiveness of the zoning of China's protected areas. Biological Conservation 204: 231-236. https://doi.org/10.1016/j.biocon.2016.10.028
  57. Yutian, L. U., X. U. Sun, L. I. U. Songxue, and W. U. Jiayu(2022) An approach to urban landscape character assessment: Linking urban big data and machine learning. Sustainable Cities and Society 103983.
  58. Zhou, Y., Shen, Y., Yang, X., Wang, Z., & Xu, L. (2021). Where to Revitalize, and How? A Rural Typology Zoning for China. Land, 10(12), 1336.
  59. Natural Capital Project (2020) https://naturalcapitalproject.stanford.edu/https://www.korea.kr/news/policyNewsView.do?newsId=148830206