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Suh, Jangwon,Choi, Yosoon Springer 2017 Environmental Earth Sciences Vol.76 No.4
<P>Accurate subsidence inventory data, based on an understanding of local topography, are a crucial first step toward reliable subsidence prediction and mapping future subsidence hazards. However, conventional, human-based methods of surveying and mapping subsidence suffer from data omissions and errors due to problems regarding accessibility, safety, and manual digitization. This study employed unmanned aerial vehicle photogrammetry to compile an accurate subsidence inventory map of abandoned mine areas. A Phantom 2 Vision? drone was used, which is inexpensive yet appropriate for detailed topographic surveying of small-sized mine sites with a history of subsidence. An autonomous flight plan was designed, taking into account the extent of target mapping areas. A series of 29 aerial photographs were obtained within 2 min; digitally georeferenced orthoimage and digital terrain model (DTM) with 5 cm resolution could be obtained by processing with coordinate information of pre-installed ground control points (GCPs) within 30 min. sinkhole-type subsidence, including locational information, was identified from the geocoded high-resolution orthoimage and the DTM, and its area and volume were calculated to be 427 m(2) and 2323 m(3) (length 25 m, width 23 m, depth 9.1 m), respectively, from its modeled shape. Contour lines (10 cm interval), slope, and curvature were produced using the DTM. Validation using the GCP locations showed an error of approximately 14 cm in the generated DTM, which was considered acceptable for subsidence mapping purposes. The proposed approach enables accurate, rapid, low-cost, and safe surveying and mapping, which complements conventional surveying methods at sites of mining subsidence.</P>
SUH, Jangwon,Hyung KIM, Jin Institute of Electronics, Information and Communic 2007 IEICE transactions on information and systems Vol.90 No.8
<P>We propose, in this article, the Hierarchical Behavior-Knowledge Space as an extension of Behavior-Knowledge Space. Hierarchical BKS utilizes ranked level individual classifiers, and automatically expands its behavioral knowledge in order to satisfy given reliability requirement. From the statistical view point, its decisions are as optimal as those of original BKS, and the reliability threshold is a lower bound of estimated reliability. Several comparisons with original BKS and unanimous voting are shown with some experiments.</P>
Suh, Jangwon,Choi, Yosoon,Park, Hyeong-Dong Springer-Verlag 2016 Environmental Earth Sciences Vol.75 No.10
<P>This paper presents a case study of subsidence hazard mapping in the vicinity of an abandoned coal mine within geographic information system (GIS) environment. A geospatial database was constructed using mine drift maps, topographic maps, land use maps, road maps, building maps, borehole data, and subsidence inventory maps showing occurrences of past subsidence events. Six raster-type factor layers (i.e., an influential area instability (IAI) layer calculated using multiple mine drifts and estimated mined panels, land use, distance from nearest railroad, distance from nearest road, and slope gradient) were generated and extracted from the database to identify relationships between past subsidence occurrences and the factors. Two IAI factors incorporate the complex effects of ground IAI and are calculated using the depths of each underground cavity and its angle of draw. A weight of evidence model was used to establish optimal correlations, expressed as contrast values (CVs) for subsidence inventory data, and inputs of all factors. Six CV layers (one for each factor) were linearly combined to generate a subsidence hazard map representing the relative vulnerability to subsidence in the study area. The area under the cumulative frequency diagram technique was then used to verify predicted subsidence hazards by comparing estimated susceptibility rankings over the entire range of grid cells with actual subsidence occurrences; the proposed GIS analysis model showed an accuracy of 91.09 % in the prediction of subsidence occurrences. Moreover, field surveys showed buildings with severe subsidence-related damage (damage level 4 or 5, according to the National Coal Board) in regions with very high subsidence hazard indices. Finally, a factor negatively correlated with subsidence prediction (slope angle) was determined from the sensitivity analysis.</P>
토립자 유실을 고려한 로지스틱 회귀분석 및 GIS 기반 도시 지반함몰 취약성 평가
서장원(Jangwon Suh),류동우(Dong-Woo Ryu),염병우(Byoung-Woo Yum) 한국암반공학회 2020 터널과지하공간 Vol.30 No.2
본 연구에서는 지리정보시스템 환경에서 지하매설물 정보를 이용하여 토립자 유실을 고려한 도시 지반함몰 취약성을 평가하였다. 지하 환경에서 물의 흐름이나 지하수위 변화에 의한 토립자 유실은 지하공동의 발생과 확장을 유도하고, 이는 지반함몰 발생에 직접적인 원인이 된다. 토립자 유실은 지하 환경에 따라 그 정도가 달라질 수 있기 때문에 본 연구에서는 지하매설물 2종(상수도 관망, 하수관로)과 지하철 선로 권역별로 지반함몰에 영향을 주는 인자를 각각 4개씩 선정하였다. 로지스틱 회귀분석 기법을 이용하여 지하매설물 및 지하철 선로 권역 별로 지반함몰 이력과 영향인자 간의 상관성을 분석하고 회귀식을 도출하였으며, 이를 토대로 3개의 지반함몰 취약성 지도를 작성하였다. 본 연구 결과는 도시 지반함몰 위험 예・경보 시스템 구축을 위한 지반함몰 고위험지역 및 지반 안전 상시 모니터링 지역 선정 근거에 대한 기초 자료를 제공할 수 있을 것으로 기대한다. This paper presents a logistic regression and GIS based urban ground sink susceptibility assessment using underground facility information considering soil particle loss. In the underground environment, the particle loss due to water flow or groundwater level change leads to the occurrence and expansion of cavities, which directly affect the ground sink. Four different contributory factors were selected according to the two underground facility domains (water pipeline area, sewer pipeline area) and subway line area. The logistic regression method was used to analyze the correlation and to derive the regression equation between the ground sink inventory and the contributory factors. Based on these results, three ground sink susceptibility maps were generated. The results obtained from this study are expected to provide basic data on the area susceptible to ground sink and needed to safety monitoring.
서장원,Suh, Jangwon 항공우주시스템공학회 2014 항공우주시스템공학회지 Vol.8 No.4
This paper examines the statistical process that should be performed with caution in the composite material qualification and equivalency process, and describes statistically significant considerations on outlier finding and handling process, data pooling through normalization process, review for data distributions and design allowables determination process for structural analysis. Based on these considerations, the need for guidance on statistical process for aircraft manufacturers who use the composite material properties database are proposed.