• 한국지형공간정보학회:학술대회논문집
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• 2004.10a
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• pp.141-146
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• 2004

최근 들어 국내에서도 홍수에 의한 재산과 인명피해를 최소화하기 위해 지역특성에 알맞은 홍수지도를 제작 중에 있으며, 주로 LiDAR를 이용하여 홍수지도 지형자료를 구축하고 있다. 그러나 이에 많은 시간과 비용이 소요되기 때문에 이미 전국적으로 구축된 수치지형도를 이용한 홍수지도 지형자료 구축의 가능성과 타당성을 검증의 필요성이 제기되고 있다. 이에 따라 본 연구에서는 수치지형도를 이용한 홍수지도제작시 가장 핵심이 되는 정확한 지형자료구축을 위해서 Breakline처리기법과 하천종횡단자료 연계방안을 중심으로 구리시 일부지역을 대상으로 DEM을 시범제작 하였다. 수치지형도와 LiDAR를 이용하여 구축한 DEM을 검수점을 통한 RMSE오차를 이용하여 수직위치정확도를 비교분석하였다. 분석을 위하여 선행연구(홍수지도제작, 2002)에서 검수점으로 사용한 9점과 제방부분의 실측한 9점을 본 연구의 검수점으로 사용하였다. 비교 결과 RMSE가 수치지형도 DEM의 경우 ${\pm}2.658m$이고, LiDAR DEM의 경우 ${\pm}3.430m$로 나타났다. 두 자료 모두 알려진 오차범위보다 훨씬 높은 오차가 발생함을 알 수 있었다. 향후 수치지형도를 이용한 효율적인 홍수지도 지형자료 구축을 위해서는 수치지형도의 신속하고 지속적인 갱신이 필요할 것이며, 현재 도시지역에만 구축되어 있는 1:1,000 수치지형도를 주변 하천지역까지 확대해서 구축해야 할 필요성이 있을 것으로 사료된다. 아울러 도입초기단계의 LiDAR 측량기술의 보급과 관련모델의 기술의 발달로 인하여 정확도 높은 DEM이 요구된다면 고밀도의 방대한 양의 LiDAR 자료로 DEM을 구축하는 것이 바람직하다고 사료된다.및 이용대책을 수립하는 데 활용될 수 있다., $1,000-2,000{\mu}g\;g^{-1}$), 나머지 177종 식물은 살초활성을 나타내지 않았다. 높은 살초활성을 나타낸 식물로부터 분리되는 천연활성물질들은 향후 새로운 제초제 개발을 위한 모화합물 제공, 상호대립억제 작용성을 갖는 작물 품종 개발 혹은 개량에의 활용, 그리고 친환경 유기농업용 잡초방제에의 활용이 기대된다.내(皮膚上皮組織內)의 Langerhans cell내(內)의 Birbeck granule에 비(比)해 수적(數的)으로 현저히 감소(減少)되어 있었다. 그러나 Thy-1 양성(陽性) dendritic cell에서 볼 수 있는 dense-core 과립(顆粒)은 별변화(別變化)없이 쉽게 관찰(觀察)될 수 있었다. 조직배양(組織培養)을 한 견(犬)의 keratinocyte에 대(對)해 사람 pemphigus vulgaris의 항체(抗體)로 반응(反應)시킨 후 protein-A gold(15 nm)로 표식(標識)시킨 바 제일 바깥 상층(上層)의 keratinocyte에 있어서 세포막표면(細胞膜表面)을 따라 표식(標識)되어 세포막항원(細胞膜抗元)을 나타내었으며, 이와 같은 소견(所見)으로 미루어 정상피부(正常皮膚) 중층편평상피세포(重層扁平上皮細胞)에서도 동일(同一)한 소견(所見)을 관찰(觀察)할 수 있다고 본다.al remnants, Resorption of fetus로 관찰된 것이다. Fetal death는 수정후 $14{\sim}18$일까지의 사망으로써 Maceration of fetus로 관찰되는 것이다. 통계학적 분석은 각 Group의 착상 을과 자궁 내 사망 율을 산출할 때에는 각 임신마우스에 따라 발생빈도가 크

• Journal of Korean Society on Water Environment
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• v.28 no.5
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• pp.743-753
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• 2012

The hydrologic models, capable of simulating groundwater recharge for long-term period and effects on it of crops management in the agricultural areas, have been used to compute groundwater recharge in the agricultural fields. Among these models, the Soil and Water Assessment Tool (SWAT) has been widely used because it could interpret hydrologic conditions for the long time considering effects of weather condition, land uses, and soil. However the SWAT model couldn't represent the spatial information of Hydrologic Response Unit (HRU), the SWAT HRU mapping module was developed in 2010. With this capability, it is possible to assume and analyze spatio-temporal groundwater recharge. In this study, groundwater recharge of rate for various crops in the Mandae stream watershed was estimated using SWAT HRU Mapping module, which can simulate spato-temporal recharge rate. As a result of this study, Coefficient of determination ($R^2$) and Nash-Sutcliffe model efficiency (NSE) for flow calibration were 0.80 and 0.72, respectively, and monthly groundwater recharge of Mandae watershed in Haean-myeon was 381.24 mm/year. It was 28% of total precipitation in 2009. Groundwater recharge rate was 73.54 mm/month and 73.58 mm/month for July and August 2009, which is approximately 18 times of groundwater recharge rate for December 2009. The groundwater recharges for each month through the year were varying. The groundwater recharge was smaller in the spring and winter seasons, relatively. So, it is necessary to enforce proper management of groundwater recharge during droughty season. Also, the SWAT HRU Mapping module could show the result of groundwater recharge as a GIS map and analyze spatio-temporal groundwater recharge. So, this method, proposed in this study, would be quite useful to make groundwater management plans at agriculture-dominant watershed.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2004.03a
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• pp.435-440
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• 2004

연안침수지도는 태풍이나 해일에 의한 연안침수 발생 시 방조제의 월류 및 붕괴로 인한 예상 침수구역을 강우빈도(200년)별로 나타내고, 침수면적과 깊이를 표현한 지도로서 국외 선진국에서 방재형 국토관리 정책결정과 침수피해에 대한 대민 홍보의 수단으로 활용되고 있다. 국내에서도 연안침수에 의한 피해가 나날이 커지고 국토의 개발에 따른 자연 재해가 많아짐에 따라 보다 방재형 국토개발로 국민의 안전과 복리를 증진하고, 연안침수에 의한 피해를 최소화하기 위한 노력의 일환으로 연안침수지도의 제작 필요성이 증대되고 있다. 본 연구의 시범지역인 대부도 남부지역의 GIS 데이터베이스 구축은 문헌조사 및 기구축 데이터 확보, 지역의 특성에 맞는 신규 GIS 데이터베이스 구축 방법을 제시하였다. 침수구역을 예측하기 위한 모델링을 지원하기 위한 정확도와 경제성, 객관성, 현실성이 높은 지형공간자료의 효율적인 구축이 강조되었다. 구축한 데이터베이스의 세부 유형은 침수위험구역, 침수경계구역, 침수량 화살표이며, 기존에 구축된 데이터를 활용한 레이어는 해안선, 도로, 건물, 등고선, 등심선, 연안 표고점 측량데이터이다. 연안침수지도는 효율적인 재난관리를 위하여 다양하게 활용될 수 있을 것으로 사료되며 나아가 주민의 침수에 대한 경각심 고취와 사전 교육, 지방자치단체의 침수위험 관리업무의 활용이 가능할 것으로 사료된다. 본 연구에서 제작된 연안침수지도는 지자체 주민들을 위해 보기 쉽고 다양한 정보를 얻을 수 있도록 제작되었으며, 이를 위해 사진과 삽화를 추가하여 주민들에게 침수피해에 대한 경각심과 이해를 높이는데 중점을 두었다. 유지관리 후 활용체계 정비의 중요성’을 점검하고, ‘변동자료 발생원인의 분석’, ‘명확한 변동자료 입력 근거의 확보’, ‘갱신주체별 역할의 정의 및 유지관리 기준의 설정’, ‘분야별업무 특성을 고려한 관련 기준의 마련 및 타 시스템과 연계되는 항목을 고려한 절차 정의’ 등에 대한 다양한 접근을 시도하였다. 본 연구에서 제시하는 유지관리 모델을 기반으로 각 지자체별로 적절한 컨설팅이 진행되고 이에 따라 담당자의 실천이 이루어진다면 지자체 GIS의 투자대비 효과에 대한 기대는 이상이 아닌 현실로 다가오게 될 것이다.가오게 될 것이다. 동일하게 25%의 소유권을 가지고 있다. ？스굴 시추사업은 2008년까지 수행될 계획이며, 시추작업은 2005년까지 완료될 계획이다. 연구 진행과 관련하여, 공동연구의 명분을 높이고 분석의 효율성을 높이기 위해서 시료채취 및 기초자료 획득은 4개국의 연구원이 모여 공동으로 수행한 후의 결과물을 서로 공유하고, 자세한 전문분야 연구는 각 국의 대표기관이 독립적으로 수행하는 방식을 택하였다 ？스굴에 대한 제1차 시추작업은 2004년 3월 말에 실시하였다. 시추작업 결과, 약 80m의 시추 코아가 성공적으로 회수되어 현재 러시아 이르쿠츠크 지구화학연구소에 보관중이다. 이 시추코아는 2004년 8월 중순경에 4개국 연구팀원들에 의해 공동으로 기재된 후에 분할될 계획이다. 분할된 시료는 국내로 운반되어 다양한 전문분야별 연구에 이용될 것이다. 한편, 제2차 시추작업은 2004년 12월에서 2005년 2월 사이에 실시될 계획이다. 수백만년에 이르는 장기간에 걸쳐 지구환경변화 기록이 보존되어 있는

• Korean Journal of Remote Sensing
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• v.35 no.6_2
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• pp.1107-1115
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• 2019

Satellite data play a major role in supporting knowledge about forest fire by delivering rapid information to map areas damaged. This study, we used 7 Sentinel-2A images to detect change area in forests of Sokcho on April 4, 2019. The process of classify forest fire severity used 7 levels from Sentinel-2A dNBR(differenced Normalized Burn Ratio). In the process of classifying forest fire damage areas, the study selected three areas with high regrowth of vegetation level and conducted a detailed spatial analysis of the areas concerned. The results of dNBR analysis, regrowth of coniferous forest was greater than broad-leaf forest, but NDVI showed the lowest level of vegetation. This is the error of dNBR classification of dNBR. The results of dNBR time series, an area of forest fire damage decreased to a large extent between April 20th and May 3rd. This is an example of the regrowth by developing rare-plants and recovering broad-leaf plants vegetation. The results showed that change area was detected through the change detection of danage area by forest category and the classification errors of the coniferous forest were reached through the comparison of NDVI and dNBR. Therefore, the need to improve the precision Korean forest fire damage rating table accompanied by field investigations was suggested during the image classification process through dNBR.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.4
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• pp.327-336
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• 2007

The 3D building modeling is one of crucial components in building 3D geospatial information. The existing methods for 3D building modeling depend mainly on manual photogrammetric processes by stereoplotter compiler, which indeed take great amount of time and efforts. In addition, some automatic methods that were proposed in research papers and experimental trials have limitations of describing the details of buildings with lack of geometric accuracy. It is essential in automatic fashion that the boundary and shape of buildings should be drawn effortlessly by a sophisticated algorithm. In recent years, airborne LiDAR data representing earth surface in 3D has been utilized in many different fields. However, it is still in technical difficulties for clean and correct boundary extraction without human intervention. The usage of airborne LiDAR data will be much feasible to reconstruct the roof tops of buildings whose boundary lines could be taken out from existing digital maps. The paper proposed a method to reconstruct the roof tops of buildings using airborne LiDAR data with building boundary lines from digital map. The primary process is to perform octree-based segmentation to airborne LiDAR data recursively in 3D space till there are no more airborne LiDAR points to be segmented. Once the octree-based segmentation has been completed, each segmented patch is thereafter merged based on geometric spatial characteristics. The experimental results showed that the proposed method were capable of extracting various building roof components such as plane, gable, polyhedric and curved surface.

• Korean Journal of Remote Sensing
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• v.24 no.2
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• pp.141-152
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• 2008

The 3D building modeling is one of crucial components in constructing 3D geospatial information. The existing methods for 3D building modeling depend mainly on manual photogrammetric processes, which indeed take great amount of time and efforts. In recent years, many researches on 3D building modeling using aerial LiDAR data have been actively performed to aim at overcoming the limitations of existing 3D building modeling methods. Either techniques with interpolated grid data or data fusion with digital map and images have been investigated in most of existing researches on 3D building modeling with aerial LiDAR data. The paper proposed a method of 3D building modeling with LiDAR data only. Firstly, octree-based segmentation is applied recursively to LiDAR data classified as buildings in 3D space until there are no more LiDAR points to be segmented. Once octree-based segmentation is completed, each segmented patch is thereafter merged together based on its geometric spatial characteristics. Secondly, building model components are created with merged patches. Finally, a 3D building model is generated and composed with building model components. The experimental results with real LiDAR data showed that the proposed method was capable of modeling various types of 3D buildings.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.597-608
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• 2022

Remotely sensed data have been used in various fields, such as disasters, agriculture, urban planning, and the military. Recently, the demand for the multitemporal dataset with the high-spatial-resolution has increased. This manuscript proposed an automatic image matching algorithm using a deep learning technique to utilize a multitemporal remotely sensed dataset. The proposed deep learning model was based on High Resolution Net (HRNet), widely used in image segmentation. In this manuscript, denseblock was added to calculate the correlation map between images effectively and to increase learning efficiency. The training of the proposed model was performed using the multitemporal orthophotos of the National Geographic Information Institute (NGII). In order to evaluate the performance of image matching using a deep learning model, a comparative evaluation was performed. As a result of the experiment, the average horizontal error of the proposed algorithm based on 80% of the image matching rate was 3 pixels. At the same time, that of the Zero Normalized Cross-Correlation (ZNCC) was 25 pixels. In particular, it was confirmed that the proposed method is effective even in mountainous and farmland areas where the image changes according to vegetation growth. Therefore, it is expected that the proposed deep learning algorithm can perform relative image registration and image matching of a multitemporal remote sensed dataset.

• Journal of The Geomorphological Association of Korea
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• v.27 no.1
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• pp.61-89
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• 2020

The objective of this study is to characterize landslide susceptibility depending on various geo-environmental variables as well as to compare the Frequency Ratio (FR) and Evidential Belief Function (EBF) methods for landslide susceptibility analysis of rainfall-induced landslides. In 2013, a total of 259 landslides occurred in Chuncheon, Gangwon Province, South Korea, due to heavy rainfall events with a total cumulative rainfall of 296~721mm in 106~231 hours duration. Landslides data were mapped with better accuracy using the geographic information system (ArcGIS 10.6 version) based on the historic landslide records in Chuncheon from the National Disaster Management System (NDMS), the 2013 landslide investigation report, orthographic images, and aerial photographs. Then the landslides were randomly split into a testing dataset (70%; 181 landslides) and validation dataset (30%; 78 landslides). First, geo-environmental variables were analyzed by using FR and EBF functions for the full data. The most significant factors related to landslides were altitude (100~200m), slope (15~25°), concave plan curvature, high SPI, young timber age, loose timber density, small timber diameter, artificial forests, coniferous forests, soil depth (50~100cm), very well-drained area, sandy loam soil and so on. Second, the landslide susceptibility index was calculated by using selected geo-environmental variables. The model fit and prediction performance were evaluated using the Receiver Operating Characteristic (ROC) curve and the Area Under Curve (AUC) methods. The AUC values of both model fit and prediction performance were 80.5% and 76.3% for FR and 76.6% and 74.9% for EBF respectively. However, the landslide susceptibility index, with classes of 'very high' and 'high', was detected by 73.1% of landslides in the EBF model rather than the FR model (66.7%). Therefore, the EBF can be a promising method for spatial prediction of landslide occurrence, while the FR is still a powerful method for the landslide susceptibility mapping.

• Journal of Korean Society of Water and Wastewater
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• v.37 no.5
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• pp.261-269
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• 2023

In light of recent social concerns related to issues such as water supply pipe deterioration leading to problems like leaks and degraded water quality, the significance of maintenance efforts to enhance water source quality and ensure a stable water supply has grown substantially. In this study, scan statistic was applied to analyze water quality complaints and water leakage accidents from 2015 to 2021 to present a reasonable method to identify areas requiring improvement in water management. SaTScan, a spatio-temporal statistical analysis program, and ArcGIS were used for spatial information analysis, and clusters with high relative risk (RR) were determined using the maximum log-likelihood ratio, relative risk, and Monte Carlo hypothesis test for I city, the target area. Specifically, in the case of water quality complaints, the analysis results were compared by distinguishing cases occurring before and after the onset of "red water." The period between 2015 and 2019 revealed that preceding the occurrence of red water, the leak cluster at location L2 posed a significantly higher risk (RR: 2.45) than other regions. As for water quality complaints, cluster C2 exhibited a notably elevated RR (RR: 2.21) and appeared concentrated in areas D and S, respectively. On the other hand, post-red water incidents of water quality complaints were predominantly concentrated in area S. The analysis found that the locations of complaint clusters were similar to those of red water incidents. Of these, cluster C7 exhibited a substantial RR of 4.58, signifying more than a twofold increase compared to pre-incident levels. A kernel density map analysis was performed using GIS to identify priority areas for waterworks management based on the central location of clusters and complaint cluster RR data.

• Korean Journal of Soil Science and Fertilizer
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• v.42 no.1
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• pp.21-28
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• 2009

Detailed information on soil characteristics is of great importance for the use and conservation of soil resources that are essential for human welfare and ecosystem sustainability. This paper introduces soil inventory of Korea focusing on national soil database establishment, information systems, use, and future direction for natural resources management. Different scales of soil maps surveyed and soil test data collected by RDA (Rural Development Administration) were computerized to construct digital soil maps and database. Soil chemical properties and heavy metal concentrations in agricultural soils including vulnerable agricultural soils were investigated regularly at fixed sampling points. Internet-based information systems for soil and agro-environmental resources were developed based on 'National Soil Survey Projects' for managing soil resources and for providing soil information to the public, and 'Agroenvironmental Change Monitoring Project' to monitor spatial and temporal changes of agricultural environment will be opened soon. Soils data has a great potential of further application in estimation of soil carbon storage, water capacity, and soil loss. Digital mapping of soil and environment using state-of-the-art and emerging technologies with a pedometrics concept will lead to future direction.