[논문]충남 부여군 문화재의 산사태 민감성 평가

김준우; 김호걸

doi:10.13087/kosert.2022.25.5.1

충남 부여군 문화재의 산사태 민감성 평가
Assessing the Landslide Susceptibility of Cultural Heritages of Buyeo-gun, Chungcheongnam-do 원문보기

環境復元綠化 = Journal of the Korean Society of Environmental Restoration Technology, v.25 no.5, 2022년, pp.1 - 13

김준우 (청주대학교 대학원 환경조경학과) , 김호걸 (청주대학교 휴먼환경디자인학부 조경도시계획전공)

Abstract ▼ AI-Helper

The damages caused by landslides are increasing worldwide due to climate change. In Korea, damages from landslides occur frequently, making it necessary to develop the effective response strategies. In particular, there is a lack of countermeasures against landslides in cultural heritage areas. The purpose of this study was to spatially analyze the relationship between Buyeo-gun's cultural heritage and landslide susceptible areas in Buyeo-gun, Chungcheongnam-do, which has a long history. Nine spatial distribution models were used to evaluate the landslide susceptibility, and the ensemble method was applied to reduce the uncertainty of individual model. There were 17 cultural heritages belonging to the landslide susceptible area. As a result of calculating the area ratio of the landslide susceptible area for cultural heritages, the cultural heritages with 100% of the area included in the landslide susceptible area were "Standing statue of Maae in Hongsan Sangcheon-ri" and "Statue of King Seonjo." More than 35% of "Jeungsanseong", "Garimseong", and "Standing stone statue of Maitreya Bodhisattva in Daejosa Temple" belonged to landslide susceptible areas. In order to effectively prevent landslide damage, the application of landslide prevention measures should be prioritized according to the proportion belonging to the landslide susceptible area. Since it is very difficult to restore cultural properties once destroyed, preventive measures are required before landslide damage occurs. The approach and results of this study provide basic data and guidelines for disaster response plans to prevent landslides in Buyeo-gun.

주제어

표/그림 (12)

그림 Figure 1. Study area(Buyeo-gun)
그림 Figure 2. Landslide occurrence points.
그림 Figure 3. Environmental variables.
표 Table 1. List of environmental variables.
그림 Figure 4. Flowchart of the study.
표 Table 2. Selected environmental variables.
표 Table 3. Variable contribution of environmental variables.
표 Table 4. The AUC value of each model.
그림 Figure 5. Landslide susceptible areas of each model and cultural heritages.
그림 Figure 6. Landslide susceptible areas of ensemble model (PME) and cultural heritages.
표 Table 5. Area ratio of landslide susceptible area and cultural property.
그림 Figure 7. Photos of cultural heritages with 100% area belonging to landslide susceptible area (National Heritage Portal, 1992; National Heritage Portal, 1984).

참고문헌 (36)

Arabameri A.Pradhan B.Rezaei K.Sohrabi M and Kalantari Z. 2019. GIS-based landslide susceptibility mapping using numerical risk factor bivariate model and its ensemble with linear multivariate regression and boosted regression tree algorithms. Journal of Mountain Science 16(3):595-618.

상세보기
Baekje Cultural Foundation. 2018. Buyeo Traditional Building Investigation Report
Chen W.Peng J.Hong H.Shahabi H.Pradhan B.Liu J.Zhu AX.Pei X and Duan Z. 2018a. Landslide susceptibility modelling using GIS-based machine learning techniques for Chongren County Jiangxi Province China. Science of the total environment 626: 1121-1135.

상세보기
Chen W.Xie X.Wang J.Pradhan B.Hong H.Bui DT.Duan Z and Ma J. 2017. A comparative study of logistic model tree random forest and classification and regression tree models for spatial prediction of landslide susceptibility. Catena 151: 147-160.

상세보기
Chen W.Zhang S.Li R and Shahabi H. 2018b. Performance evaluation of the GIS-based data mining techniques of best-first decision tree random forest and naive Bayes tree for landslide susceptibility modeling. Science of the total environment 644:1006-1018.

상세보기
Dai FC and Lee CF. 2002. Landslide characteristics and slope instability modeling using GIS Lantau Island Hong Kong. Geomorphology 42(3-4):213-228.

상세보기
Dhakal AS and Sidle RC. 2004. Distributed simulations of landslides for different rainfall conditions. Hydrological Processes 18(4):757-776.

상세보기
Di Napoli M.Di Martire D.Bausilio G.Calcaterra D.Confuorto P.Firpo M.Pepe G and Cevasco A. 2021. Rainfall-induced shallow landslide detachment transit and runout susceptibility mapping by integrating machine learning techniques and GIS-based approaches. Water 13(4) : 488.
Floris M and Bozzano F. 2008. Evaluation of landslide reactivation: a modified rainfall threshold model based on historical records of rainfall and landslides. Geomorphology 94(1-2):40-57.

상세보기
Hamza T and Raghuvanshi TK. 2017. GIS based landslide hazard evaluation and zonation-A case from Jeldu District Central Ethiopia. Journal of King Saud University-Science 29(2):151-165.

상세보기
Helen K. 2015. Tracing UNGEGN's evolving interest in geographical names as cultural heritage. Geographical Names as Cultural Heritage Proceedings of the International Symposium on Toponymy Seoul Kyung Hee University Press.
KEREKES AH.POSZET SL and Andrea GAL. 2018. Landslide susceptibility assessment using the maximum entropy model in a sector of the Cluj-Napoca Municipality Romania. Revista de Geomorfologie 20(1):130-146.
Kim HG.Lee DK and Park C. 2018a. Assessing the cost of damage and effect of adaptation to landslides considering climate change. Sustainability 10(5):1628.

상세보기
Kim HG. 2018 Analysis of Potential Landslide Risk Areas to Support Local Government's Response to Climate Change Disaster: Targeting Chungcheong Area. Urban Studies (14):93-118.
Kim HG and Park CY. 2021a. Landslide susceptibility analysis of photovoltaic power stations in Gangwon-do Republic of Korea. Geomatics Natural Hazards and Risk 12(1):2328-2351.

상세보기
Kim MS.Onda Y.Uchida T.and Kim JK. 2016. Effects of soil depth and subsurface flow along the subsurface topography on shallow landslide predictions at the site of a small granitic hillslope. Geomorphology 271:40-54.

상세보기
Kim JW and Kim HG. 2021b. Landslide Susceptibility Analysis by Type of Cultural Heritage Site Using Ensemble Model: Case Study of the Chungcheong Region of South Korea. Sensors and Materials 33(11): 3819-3833.

상세보기
Kornejady A.Ownegh M and Bahremand A. 2017. Landslide susceptibility assessment using maximum entropy model with two different data sampling methods. Catena 152:144-162.

상세보기
Lazzari M.Gioia D.and Anzidei B. 2018. Landslide inventory of the Basilicata region (Southern Italy). Journal of Maps 14(2): 348-356.

상세보기
Liberata Ullo S.Mohan A.Sebastianelli A.Ejaz Ahamed S.Kumar B.Dwivedi R and Sinha GR. 2020. A New Mask R-CNN Based Method for Improved Landslide Detection. arXiv e-prints pp.arXiv-2010.
Lollino G.Giordan D.Crosta GB.Corominas J.Azzam R.Wasowski J and Sciarra N. eds. 2014. Engineering geology for society and territory-Volume 2: Landslide processes (Vol. 2). Springer.
Lombardo L.Bachofer F.Cama M.Marker M and Rotigliano E. 2016. Exploiting Maximum Entropy method and ASTER data for assessing debris flow and debris slide susceptibility for the Giampilieri catchment (north-eastern Sicily Italy). Earth Surface Processes and Landforms 41(12): 1776-1789.

상세보기
National Heritage Portal. 1984. Cultural Heritage Image. Cultural Heritage Administration. https://www.heritage.go.kr/main/?v1666682807467/. (accessed Dec. 2021)
National Heritage Portal. 1992. Cultural Heritage Image. Cultural Heritage Administration. https://www.heritage.go.kr/main/?v1666682807467/. (accessed Dec. 2021)
NSDIP(National Spatial Data Infrastructure Potal). 2022. Forestry Statistical Yearbook. Korea fores servicehttps. https://www.data.go.kr/data/15087207/fileData.do/.(accessed Jul. 2022)
Poudel KR.Hamal R and Paudel N. 2020. Landslide susceptibility assessment: identification and hazard mapping of Gandaki Province Nepal. Prithvi Academic Journal 3:11-21.
Ridgeway G. 2007. Generalized Boosted Models: A guide to the gbm package. Update 1(1)
Rossi M.Guzzetti F.Reichenbach P.Mondini AC and Peruccacci S. 2010. Optimal landslide susceptibility zonation based on multiple forecasts. Geomorphology 114(3):129-142.

상세보기
Sabbioni C.Cassar M.Brimblecombe P and Lefevre RA. 2008. Vulnerability of cultural heritage to climate change. European and Mediterranean Major Hazards Agreement: 1-24.
Taalab K.Cheng T and Zhang Y. 2018. Mapping landslide susceptibility and types using Random Forest. Big Earth Data 2(2): 159-178.

상세보기
Tang H.Wasowski J and Juang CH. 2019. Geohazards in the three Gorges Reservoir Area China-Lessons learned from decades of research. Engineering Geology 261: 105267.

상세보기
Vorpahl P.Elsenbeer H.Marker M and Schroder B. 2012. How can statistical models help to determine driving factors of landslides?. Ecological Modelling 239:27-39.

상세보기
Wang Y.Fang Z and Hong H. 2019. Comparison of convolutional neural networks for landslide susceptibility mapping in Yanshan County China. Science of the total environment 666: 975-993.

상세보기
Wu Y.Ke Y.Chen Z.Liang S.Zhao H and Hong H. 2020. Application of alternating decision tree with AdaBoost and bagging ensembles for landslide susceptibility mapping. Catena 187:104396.

상세보기
Yang IT.Chun KS and Park JH. 2006. The effect of landslide factor and determination of landslide vulnerable area using GIS and AHP. Journal of Korean Society for Geospatial Information Science 14(1):3-12.
Yi Y.Zhang Z.Zhang W.Xu Q.Deng C and Li Q. 2019. GIS-based earthquaketriggered-landslide susceptibility mapping with an integrated weighted index model in Jiuzhaigou region of Sichuan Province China. Natural Hazards and Earth System Sciences 19(9):1973-1988.

상세보기

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