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2026 Vol.27, Issue 8 Preview Page
Analysis of the Relationship Between Underground Building Characteristics and Ground Subsidence Considering Spatial Autocorrelation

공간 자기상관을 고려한 지하 건축물 특성과 지반함몰 발생 관계 분석

Sungyeol Lee1
,
Jaemo Kang2*
,
Myeongsik Kong3
,
Jinyoung Kim4
,
Eomzi Yang5
이 성열1
,
강 재모2*
,
공 명식3
,
김 진영4
,
양 엄지5
1Postdoctoral Researcher, Department of Geotechnical Engineering Research, Korea Institute of Civil Engineering and Building Technology
2Research Fellow, Department of Geotechnical Engineering Research, Korea Institute of Civil Engineering and Building Technology
3Researcher, Department of Geotechnical Engineering Research, Korea Institute of Civil Engineering and Building Technology
4Research Fellow, Department of Research Planning Division, Korea Institute of Civil Engineering and Building Technology
5Senior Researcher, Department of Geotechnical Engineering Research, Korea Institute of Civil Engineering and Building Technology
*Corresponding Author
1 August 2026. pp. 35-42
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Abstract

Ground subsidence mainly occurs in densely populated urban areas, and it is necessary to analyze its occurrence characteristics and establish preventive management strategies because such accidents may cause human casualties and property damage. Studies analyzing the occurrence characteristics of ground subsidence have mainly focused on underground utility information. However, ground subsidence is a phenomenon caused by the complex interaction of multiple factors, and therefore various influencing factors should be considered. Accordingly, this study analyzed the occurrence characteristics of ground subsidence using underground building factors that can indirectly reflect the structure of urban underground spaces. For this purpose, underground building data and ground subsidence accident records from 2008 to 2016 were collected for a metropolitan urban area in the Republic of Korea, and the study area was divided into 500 m × 500 m grids using QGIS. Subsequently, datasets were constructed by extracting the number of underground buildings, the ratio of aged underground buildings, and the number of ground subsidence occurrences within each grid. In addition, Negative Binomial regression analysis and Moran’s I analysis were performed to consider the over-dispersion characteristics and spatial autocorrelation characteristics of ground subsidence occurrences. The results showed that Moran’s I for ground subsidence occurrences was 0.441 (p < 0.001), indicating the presence of spatial clustering characteristics. Furthermore, the results of the Negative Binomial regression analysis showed that the number of underground buildings, mean building age, and the ratio of underground buildings older than 20 years had statistically significant positive (+) relationships with the number of ground subsidence occurrences. In the model including the spatial autocorrelation variable, the residual Moran’s I decreased and the AIC decreased from 6213 to 5669. Therefore, it is expected that more effective analysis and management of ground subsidence risk areas can be achieved by jointly considering the distribution and aging characteristics of underground buildings together with spatial autocorrelation characteristics.

Keywords
Ground subsidence
Underground building
Spatial analysis
Negative binomial regression

지반함몰은 인구 밀도가 높은 도심지에서 주로 발생하며, 사고 발생 시 인명 및 재산피해를 야기하기 때문에 사고 발생 특성을 분석하고 사전에 대응할 필요가 있다. 지반함몰 발생 특성을 분석하기 위한 연구는 주로 지하매설물 정보를 중심으로 수행되어 왔으나, 지반함몰은 다양한 원인이 복합적인 작용에 의해 발생하는 현상이므로 다양한 인자를 고려할 필요가 있다. 따라서 본 연구에서는 도시 지하공간 구조를 간접적으로 반영할 수 있는 지하 건축물 인자를 활용하여 지반함몰 발생 특성을 분석하였다. 이를 위하여 대한민국 대도시를 대상으로 지하 건축물 데이터와 2008~2016년 지반함몰 사고이력 데이터를 수집하였으며, QGIS를 활용하여 500 m × 500 m 크기의 grid로 구분하였다. 이후 grid 내부에 포함된 지하 건축물 개수, 노후 건축물 비율 및 지반함몰 발생횟수를 추출하여 데이터셋을 구축하였다. 또한 지반함몰 발생횟수의 과분산 특성과 공간적 자기상관 특성을 고려하기 위하여 Negative Binomial 회귀분석과 Moran’s I 분석을 수행하였다. 분석 결과, 지반함몰 발생횟수에 대한 Moran’s I는 0.441(p < 0.001)로 나타나 공간적 군집 특성이 존재하는 것으로 확인되었다. 또한 Negative Binomial 회귀분석 결과, 지하 건축물 개수와 평균 활용년수, 20년 이상 노후 건축물 비율 변수는 지반함몰 발생횟수와 통계적으로 유의한 양(+)의 관계를 나타내는 것으로 확인되었다. 공간 자기상관 변수를 추가한 모델에서는 잔차 Moran’s I가 감소하고 AIC가 6213에서 5669로 감소하는 것으로 나타났다. 따라서 지하 건축물의 분포 및 노후 특성과 공간 자기상관 특성을 함께 반영할 경우 보다 효과적인 지반함몰 위험지역 분석 및 관리가 가능할 것으로 기대된다.

키워드
지반함몰
지하 건축물
공간분석
Negative binomial 회귀분석
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Information
  • Publisher :Korean Geo-Environmental Society
  • Publisher(Ko) :한국지반환경공학회
  • Journal Title :Journal of the Korean Geo-Environmental Society
  • Journal Title(Ko) :한국지반환경공학회 논문집
  • Volume : 27
  • No :8
  • Pages :35-42
  • Received Date : 2026-07-02
  • Revised Date : 2026-07-06
  • Accepted Date : 2026-07-20
  • DOI :https://doi.org/10.14481/jkges.2026.27.8.35
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