• Korean Journal of Remote Sensing
• /
• v.38 no.6_1
• /
• pp.1371-1383
• /
• 2022

In this study, the amount of coal waste dump was calculated using six Digital Elevation Models (DEMs) produced between 2006 and 2018 in Jangseong-dong, Taebaek-si, Gangwon-do, and the subsidence was observed by applying the Persistent Scatterer Interferometric SAR (PSInSAR) technique on the Sentinel-1 SAR images. As a result of depositing activities using DEMs, a total of 1,668,980 m³ of coal waste was deposited over a period of about 12 years from 2006 to 2018. The observed subsidence rate from PSInSAR was -32.3 mm/yr and -40.2 mm/yr from the ascending and descending orbits, respectively. As the thickness of the waste pile increased, the rate of subsidence increased, and the more recent the completion of the deposit, the faster the subsidence tended to occur. The subsidence rates from the ascending and descending orbits were converted to vertical and horizontal east-west components, and 22 random reference points were set to compare the subsidence rate, the waste rock thickness, and the time of depositing completion. As a result, the subsidence rate of the reference point tended to increase as the thickness of the waste became thicker, similar to the PSInSAR results in relation to the waste thickness. On the other hand, there was no clear correlation between the completion time of the deposits and the rate Of subsidence at the reference points. This is because the time of completion of the deposits at all but 5 of the 22 reference points was too biased in 2010 and the correlation analysis was meaningless. As in this study, the use of DEM and PSInSAR is expected to be an effective alternative to compensate for the lack of field data in the safety management of coal waste deposits.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.8 no.2
• /
• pp.45-51
• /
• 1990

DEM must have a high accuracy against the actual topographic model. A model which can compute heights responding to random plane position by using of the topographic data and interpolation must be constructed. Interpolation affected by the accuraccy of the observations included noise, which affected by the slop and curvature weight. Data smoothing is a method to reduce the noise. Average declination and area ratio are variable which result similarity in according to slope. But in local area, area ratio well shows a local change. This study try to classify the terrain by the declination to analysis the effects of the declination and curvature weights, and then to represent the most probable model. The result are following : In terrain classification by the slop, p16 and p24 were fitted in the plane surface fit p16 and S in the varying surface, and S and p24 in the irregular surface in classification by curvature, p24 and S were fitted in the plane or varying surface, and p16 in the irregular surface In case of hybrid, p16, p24 and S are fitted in the plane, varying and irregular surface respectively. Smoothing is the most effective in case of slope of 50 persentage and of curvature weight of 0.0015.

• Journal of Korean Society for Geospatial Information Science
• /
• v.24 no.3
• /
• pp.49-58
• /
• 2016

Applications of drone in various fields have been increasing in recent years. Drone has great potential for forest management. Therefore this paper is using drone for forest damage areas. Forest damage areas is divided into caused by anthropogenic and occurs naturally, the possibility of disasters, such as slope sliding, slope failures and landslides, sediment runoff exists. Therefore, this research was to utilize the drone photogrammetry to perform the damage analysis of forest damage areas. Geometrical treatment processing results in Drone Photogrammetry, the plane position error RMSE was ${\pm}0.034m$, the elevation error RMSE was ${\pm}0.017m$. The plane position error of orthophoto RMSE was ${\pm}0.083m$, the elevation error of digital elevation model RMSE was ${\pm}0.085m$. In addition, It was possible to current state analysis of damage in forest damage areas of airborne LiDAR data of before forest damage and drone photogrammetry data of after forest damage. and application of drone photogrammetry for production base data for restoration and design in forest damage areas.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.23 no.2
• /
• pp.147-156
• /
• 2005

SAR interferometry (InSAR) is a technique to generate 3-Dimentional spatial information using complex data pairs observed by antennas at different locations. In case of the Two-pass differential SAR inteferometry (DInSAR), the topographic phase signature can be separated from the contribution of surface deformation in the interferometric phase. In this study, InSAR and DInSAR were implemented with ERS- l/2 tandem pair to produce DEM. The accuracy of the Resulting DEMs was analyzed.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2017.05a
• /
• pp.341-341
• /
• 2017

토석류는 기본적으로 강우에 기인하는 산지재해이다. 따라서 국토의 64%가 산지인 동시에 여름철 강우가 집중되는 우리나라의 특성상 토석류가 발생할 가능성이 상당히 크다. 또한 최근 높은 인구밀도로 인하여 불가피하게 토석류 발생 시 큰 인명피해마저 우려되고 있는 실정이다. 토석류저감을 위해서 FLO-2D, RAMMS, DEBRIS-2D 등의 다양한 수치해석 프로그램들이 개발되어왔다. 이러한 프로그램들을 통해 토석류를 해석하려면 조사하려는 지역의 지형자료를 습득하는 것이 선행되어져야 한다. 하지만 토석류 재해지역의 접근성 및 위험성을 감안할 때 해당 지역으로의 접근이 곤란하여 지형자료를 직접 얻는 것은 어려운 경우가 대부분이다. 본 연구에서는 토석류 재해 위험지역에서 드론촬영을 실시하여 후처리 프로그램을 통해 해당 지역의 DEM을 생성하였다. 생성한 DEM이 효용가치를 지니려면 실제 지형과의 차이를 최소한으로 가져야 한다. 따라서 드론촬영으로 생성한 DEM을 수치지도를 통해 생성한 DEM과 비교하여 좌표의 편차, 고도의 편차 등을 계산하였다. 또한 각각의 DEM 자료에 FLO-2D를 적용하여 토석류 재해 위험지역에 설치된 사방시설의 저감능력을 확인해보았다. 두 DEM의 비교분석을 통해 드론촬영으로 생성한 DEM이 충분한 실용성을 지니고 있음을 확인하였고, 또한 해당 지점에 설치된 사방시설의 저감능력을 다방면으로 확인할 수 있었다. 연구결과, 현재 급부상하고 있는 드론을 통해 사방사업을 효율적으로 진행할 수 있음을 확인하였다. 이는 토석류 저감 부문에서 큰 효과를 발휘할 것으로 기대된다.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2019.05a
• /
• pp.115-115
• /
• 2019

하천수 흐름예측에 대한 연구는 대부분 WRF-Hydro와 같은 과정기반 모델링 시스템을 이용한다. 과정기반 모델링 시스템은 물리적 현상을 일반화한 수식으로 구성되어있다. 일반화된 수식은 불확실성을 내포하고 있으며 지역적 특성도 반영하지 못한다. 특히 수식에 사용되는 입력자료는 측정값으로 오차가 존재한다. 따라서 과정기반 모델링 시스템 예측결과는 계통오차와 우연오차가 존재한다. 현재 매개변수 보정을 통해 예측결과를 개선하는 방법을 사용하고 있으나 한계가 있다. 본 연구는 이러한 한계를 극복하기 위해 상호보완적인 Data-driven 모델을 구축하여 과정기반 모델링 시스템 결과를 개선하고자 하였다. Data-driven 모델 구축을 위해 머신러닝 기법인 instance-based weighting(IBW)과 support vector regression(SVR)을 사용하였다. 구축된 Data-driven 모델은 한반도 지역 주요 저수지 및 호수의 하천수 흐름예측을 통해 검증하였다. 검증을 위해 과정기반 모델링 시스템으로 WRF-Hydro를 구동하였다. 입력자료는 기상청의 국지수치예측모델자료(LDAPS), HydroSHEDS의 수치표고모델자료(DEM), 국가지리정보원의 저수지 및 호수 연속수치지형도를 사용하였다. 본 연구를 통해 구축된 Data-driven모델은 기존 과정기반 모델링 시스템의 오류수정 한계를 머신러닝을 이용하여 개선할 수 있는 가능성을 제시하였다.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2023.05a
• /
• pp.140-140
• /
• 2023

전 세계적인 기후변화로 인해 태풍과 집중호우의 발생빈도와 규모가 지속적으로 증가하고 있다. 이러한 태풍과 집중호우는 국토의 64%가 산지로 이루어져 있는 우리나라에서 토석류 재해를 발생시켜 하류부에 많은 피해를 입힌다. 토석류는 계곡을 따라 흐르는 특성을 가지고 있어 콘크리트 사방댐, 슬릿트형 사방댐과 같은 횡단구조물과 기슭막이와 같은 종단구조물의 설치는 토석류피해 저감에 매우 유효하게 작용하고 있다. 따라서 토석류 재해의 발생 위험이 높은 유역에서의 토사유출량의 예측과 재해저감시설의 규모와 형상, 위치 설정은 토석류 피해를 예방하기 위한 중요한 요소이다. 본 연구에서는 2019년 10월 토석류 재해가 발생한 지역의 피해를 분석하기 위해 2차원 수치모형인 Hyper KANAKO 모형을 이용하였으며, 해당 지역의 수치지형도를 이용하여 수치표고모델(DEM)과 토석류 피해를 저감하기 위한 배수시설을 고려한 지형자료를 제작하였다. 그리고 모형의 주요 입력변수인 첨두유량은 토석류 피해가 발생하였을 때의 강우 자료와 현장조사 자료를 이용하여 산정하였다. Hyper KANAKO 모형의 결과로 나타나는 확산범위, 퇴적량 등을 분석하여 배수시설의 유무에 따른 토석류 피해 저감효과를 분석하였다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.27 no.3
• /
• pp.393-400
• /
• 2009

Recently demand for the 3D modeling technology to reconstruct real world is getting increasing. However, existing geospatial data are mainly based on the 2D space. In addition, most of the geospatial data provide geometric information only. In consequence, there are limits in various applications to utilize information from those data and to reconstruct the real world in 3D space. Therefore, it is required to develop efficient 3D mapping methodology and data for- mat to establish geospatial database. Especially digital elevation model(DEM) is one of the essential geospatial data, however, DEM provides only spatially distributed 3D coordinates of the natural and artificial surfaces. Moreover, most of DEMs are generated without considering terrain properties such as surface roughness, terrain type, spatial resolution, feature and so on. This paper suggests adaptive and flexible geospatial data format that has possibility to include various information such as terrain characteristics, multiple resolutions, interpolation methods, break line information, model keypoints, and other physical property. The study area was categorized into mountainous area, gently rolling area, and flat area by taking the terrain characteristics into account with respect to terrain roughness. Different resolutions and interpolation methods were applied to each area. Finally, a 3D digital map derived from aerial photographs was integrated with the geospatial data and visualized.

• Korean Journal of Environment and Ecology
• /
• v.10 no.1
• /
• pp.58-65
• /
• 1996

The environment in urban are becoming worse and forest is being recognized the major part of city by the increase of population and facilities. This study was carried out to analyze topographic environment as the basis for reasonable management and utility of forest situated in Taejon city and its vicinities using Sandst-5 TM and digital terrain elevation data(DTED). Forest area was extracted by Landsat-5 TM data. Distribution of elevation, slope and aspect was derived from digital terrain elevation data. The research area to analyze ropographic environment for urban forest were Bomumsan, Bongsan, Kabhasan, Sikchangsan, and Kyechoksan. Forest, the largest area in Taejon covers 55.1% of totaf area. This is more 5 times than urban area. 70.8% of forest area in Taejon city is located in elevation of lower than 200m and 4.8% of that is located in elevation of upper than 400m. Distribution of elevation is 45.7% of total area for 100m to 200m in Kyechoksan and is 92.4% of total area for lower than 300m in Bomumsan. Elevation of upper than 300m is 20.4% of total area in Kabhasan and is 46.6% of total area in Sikchangsan. The slope of more 20 digree is over 50% of total area in every area except for Bonsan and 35.2% of total area in Sikchangsan and Kahasan than in Bomumsan and Kyechoksan.

• Journal of Korean Society for Geospatial Information Science
• /
• v.19 no.1
• /
• pp.79-86
• /
• 2011

Recently, aerial laser scanning technology has received full attention in constructing DEM(Digital Elevation Model). It is well known that the quality of DEM is mostly influenced by the accuracy of DTD(Digital Terrain Data) extracted from LiDAR(Light Detection And Ranging) raw data. However, there are always misclassified data in the DTD generated by automatic filtering process due to the limitation of automatic filtering algorithm and intrinsic property of LiDAR raw data. In order to eliminate the misclassified data, a manual filtering process is performed right after automatic filtering process. In this study, an algorithm that detects automatically possible misclassified data included in the DTD from automatic filtering process is proposed, which will reduce the load of manual filtering process. The algorithm runs on 2D grid data structure and makes use of several parameters such as 'Slope Angle', 'Slope DeltaH' and 'NNMaxDH(Nearest Neighbor Max Delta Height)'. The experimental results show that the proposed algorithm quite well detected the misclassified data regardless of the terrain type and LiDAR point density.