• 대한원격탐사학회지
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• 제35권4호
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• pp.573-587
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• 2019

A multi-temporal approach using remotely sensed time series data obtained over multiple years is a very useful method for monitoring land covers and land-cover changes. While spectral-based methods at any particular time limits the application utility due to instability of the quality of data obtained at that time, the approach based on the temporal profile can produce more accurate results since data is analyzed from a long-term perspective rather than on one point in time. In this study, a multi-temporal approach applying a multi-periodic harmonic model is proposed for classification of remotely sensed data. A harmonic model characterizes the seasonal variation of a time series by four parameters: average level, frequency, phase, and amplitude. The availability of high-quality data is very important for multi-temporal analysis.An satellite image usually have many unobserved data and bad-quality data due to the influence of observation environment and sensing system, which impede the analysis and might possibly produce inaccurate results. Harmonic analysis is also very useful for real-time data reconstruction. Multi-periodic harmonic model is applied to the reconstructed data to classify land covers and monitor land-cover change by tracking the temporal profiles. The proposed method is tested with the MODIS and GOCI NDVI time series over the Korean Peninsula for 5 years from 2012 to 2016. The results show that the multi-periodic harmonic model has a great potential for classification of land-cover types and monitoring of land-cover changes through characterizing annual temporal dynamics.

• 한국지반환경공학회 논문집
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• 제6권1호
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• pp.15-21
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• 2005

본 연구에서는 증발산 원리를 이용한 최종복토층 공법의 재료로서 석탄회와 인산석고의 활용성에 대해서 고려하였다. 복토재료는 일반 화강암질 풍화토에 석탄회와 인산석고를 혼합하는 것으로 하고 이에 따른 환경적 영향을 예측하기 위해서 실내용출시험, 컬럼실험, 현장 모형실험을 순서적으로 실시하였다. 용출실험 결과에서 각 혼합물의 중금속 함유량은 규정값 이하로 나타났으며, 관계규정과 컬럼실험의 결과를 컴토하여 재료간 최적 배합비율은 토양(4):석탄재(1):인산석회(1)로 결정하여 현장모형실험에 적용하였다. 환경적 평가를 위한 현장모형실험은 2004년 2월에서 6월까지 진행하였는데, 실험기간 중 혼합 복토재와 우수에 의해 발생되는 침출수의 관찰결과에서는 본 연구에서 고려한 혼합재료가 환경적으로 안전하게 사용될 수 있는 것으로 나타났다.

• 한국관개배수논문집
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• 제14권2호
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• pp.225-235
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• 2007

The shape of streamflow hydrograph during the early period of spring is very much controlled by the area and depth of snow cover especially in mountainous area. When we simulate the streamfolw of a watershed snowmelt, we need some information for snow cover extent and depth distribution as parameters and input data in the hydrological models. The purpose of this study is to suggest an extraction method of snow cover area and snow depth distribution using Terra MODIS image. Snow cover extent for South Korea was extracted for the period of December 2000 and April 2006. For the snow cover area, the snow depth was interpolated using the snow depth data from 69 meteorological observation stations. With these data, it is necessary to run a hydrological model considering the snow-related data and compare the simulated streamflow with the observed data and check the applicability for the snowmelt simulation.

• 산업기술연구
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• 제24권A호
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• pp.227-238
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• 2004

This paper is results of experimental and nunerical works on the behavior of the cut-and-cover tunnel. Centrifuge model tests were performed to simulate the behavior of the cut-and-cover tunnels having cross sections of national road and subway tunnels. Model experiments were carried out with changing the cut slope and the slope of filling ground surface. Displacements of tunnel lining resulted from artificially accelerated gravitational force up to 40g of covered material used in model tests, were measured during centrifuge model tests. In model tests, Jumunjin Standard Sand with the relative density of 80 % and the zinc plates were used for the covered material and the flexible tunnel lining, respectively. Basic soil property tests were performed to obtain it's the property of Jumumjin Standard Sand. Shear strength parameters of Jumunjin Standard Sand were obtained by performing the triaxial compression tests. Direct shear tests were also carried out to find the mechanical properties of the interface between the lining and the covered material. Numerical analysis with the commercially available program of FLAC were performed to compare with results of centrifuge model experiment In numerical modelling. Mohr-Coulomb elasto-plastic constitutive model was used to simulaye the behavoor of Jumunjin Standard Sand and the interface element between the lining and the covered material was implemented to simulate the interaction between them. Compared results between model tests and numerical estimation with respect to displacement of the lining showed in good agreements.

• 한국지리정보학회지
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• 제16권3호
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• pp.25-39
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• 2013

본 연구에서는 금강유역 내 용담댐 및 대청댐을 대상으로 SWAT 모형을 이용하여 미래 유출량 전망에 지배적인 인자로 작용하는 토지피복 변화에 따른 유출량 변화를 분석하였다. Landsat TM 위성영상을 이용하여 과거 1990년 및 1995년 토지피복 자료를 관측 자료로 사용하여 CA-Markov 연쇄기법에 의한 2000년 토지피복도를 모의하여 비교 검증을 한 후 향후 2050년과 2100년의 토지피복변화를 모의하였다. 이를 SWAT모형의 입력 자료로 이용하여 A1B 시나리오하에서 토지피복 변화 전 후의 유출량을 비교 분석 하였다. 금강유역에 대한 토지피복에 대한 경년별 추세 분석결과 산림과 논은 꾸준히 감소하고 주거지, 나지, 초지 등은 증가하는 경향을 나타내었다. 미래 토지피복의 변화를 고려한 유출 변화 분석결과, 토지피복의 변화를 고려한 유출량이 토지피복의 변화를 고려하지 않았을 때보다 전체적으로 1.83~2.87%로 소폭 증가하는 것으로 나타났다.

• 대기
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• 제15권2호
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• pp.75-90
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• 2005

이 연구에서는 지면-대기 모수화 방안 (BATS1e)이 접합된 미국 국립기상연구센터 (NCAR)에서 개발한 지역기후모델(RegCM2)을 이용하여 지면피복의 변화가 동아시아 여름몬순에 미치는 영향에 대해서 조사하였다. 지면피복 변화의 영향을 분석하기 위하여 두 종류의 지면피복 자료를 이용하였다. 하나는 NCAR에서 제공하는 지면피복 자료 (CTL 실험)이고 다른 하나는 최근의 기상위성자료로부터 직접 분류한 고해상도 지면피복분류 자료(LCV 실험)이다. CTL 실험에서는 중국 중부지역과 몽고지역의 지면온도가 각각 약 $1-3^{\circ}C$ 높고 낮게 모의되었다. 또한 모의 영역 북부지역에서는 강수가 과다하게 모의된 반면 모의영역 남부 바다지역의 강수는 과소하게 모의되었다. 지면피복 변화에 의한 알베도, 거칠기 길이 및 최소기공저항계수와 같은 지면의 생물리적 요소들의 변화는 지면-대기 상호작용을 변경시켰다. 즉, 지면피복이 낙엽활엽수림에서 농지와 관계농지로 변경된 LCV 실험의 중국 중부지역에서는 잠열 속과 풍속이 현저하게 증가되었다. 그 결과 CTL 실험에서 나타났던 중국 중부지역에서의 온난편차가 LCV 실험에서는 대부분 완화되었다. 중국 중부지역에서의 강한 기온 하강은 태평양과 대륙사이의 기압 차를 약화시키고 있다. 남동에서 북서방향으로의 기압경도력이 약화됨에 따라 중국 남부와 남중국해로부터 북동쪽으로의 수증기 수송도 약화되었다. 이러한 수증기 수송의 변화는 모의 영역 북부지역에서의 과다한 강수 모의와 남중국해에서의 과소한 강수모의를 동시에 크게 완화시켰다. 그러나 지면피복의 변화는 특히 7월과 8월에 한반도와 일본 열도 지역에서의 강수를 크게 증기시키고 있다.

• Structural Engineering and Mechanics
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• 제30권6호
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• pp.713-732
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• 2008

Serviceability and durability of the concrete members can be seriously affected by the corrosion of steel rebar. Carbonation front and or chloride ingress can destroy the passive film on rebar and may set the corrosion (oxidation process). Depending on the level of oxidation (expansive corrosion products/rust) damage to the cover concrete takes place in the form of expansion, cracking and spalling or delamination. This makes the concrete unable to develop forces through bond and also become unprotected against further degradation from corrosion; and thus marks the end of service life for corrosion-affected structures. This paper presents an analytical model that predicts the weight loss of steel rebar and the corresponding time from onset of corrosion for the known corrosion rate and thus can be used for the determination of time to cover cracking in corrosion affected RC member. This model uses fully the thick-walled cylinder approach. The gradual crack propagation in radial directions (from inside) is considered when the circumferential tensile stresses at the inner surface of intact concrete have reached the tensile strength of concrete. The analysis is done separately with and without considering the stiffness of reinforcing steel and rust combine along with the assumption of zero residual strength of cracked concrete. The model accounts for the time required for corrosion products to fill a porous zone before they start inducing expansive pressure on the concrete surrounding the steel rebar. The capability of the model to produce the experimental trends is demonstrated by comparing the model's predictions with the results of experimental data published in the literature. The effect of considering the corroded reinforcing steel bar stiffness is demonstrated. A sensitivity analysis has also been carried out to show the influence of the various parameters. It has been found that material properties and their inter-relations significantly influence weight loss of rebar. Time to cover cracking from onset of corrosion for the same weight loss is influenced by corrosion rate and state of oxidation of corrosion product formed. Time to cover cracking from onset of corrosion is useful in making certain decisions pertaining to inspection, repair, rehabilitation, replacement and demolition of RC member/structure in corrosive environment.

• 대한원격탐사학회지
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• 제38권6_4호
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• pp.1911-1923
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• 2022

The availability of high-resolution satellite images provides precise information without direct observation of the research target. Korea Multi-Purpose Satellite (KOMPSAT), also known as the Arirang satellite, has been developed and utilized for earth observation. The machine learning model was continuously proven as a good classifier in classifying remotely sensed images. This study aimed to compare the performance of the support vector machine (SVM) model in classifying the land cover of the Delaware River port area on high and medium-resolution images. Three optical images, which are KOMPSAT-2, KOMPSAT-3A, and Sentinel-2B, were classified into six land cover classes, including water, road, vegetation, building, vacant, and shadow. The KOMPSAT images are provided by Korea Aerospace Research Institute (KARI), and the Sentinel-2B image was provided by the European Space Agency (ESA). The training samples were manually digitized for each land cover class and considered the reference image. The predicted images were compared to the actual data to obtain the accuracy assessment using a confusion matrix analysis. In addition, the time-consuming training and classifying were recorded to evaluate the model performance. The results showed that the KOMPSAT-3A image has the highest overall accuracy and followed by KOMPSAT-2 and Sentinel-2B results. On the contrary, the model took a long time to classify the higher-resolution image compared to the lower resolution. For that reason, we can conclude that the SVM model performed better in the higher resolution image with the consequence of the longer time-consuming training and classifying data. Thus, this finding might provide consideration for related researchers when selecting satellite imagery for effective and accurate image classification.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.1470-1472
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• 2003

Hyperion, as hyperspectral data, is carried on NASA’s EO-1 satellite, can be used in more subtle discrimination on forest cover, with 224 band in 360 ?2580 nm (10nm interval). In this study, Hyperion image is used to investigate the effects of topography on the classification of forest cover, and to assess whether the topographic correction improves the discrimination of species units for practical forest mapping. A publicly available Digital Elevation Model (DEM), at a scale of 1:25,000, is used to model the radiance variation on forest, considering MSR(Mean Spectral Ratio) on antithesis aspects. Hyperion, as hyperspectral data, is corrected on a pixel-by-pixel basis to normalize the scene to a uniform solar illumination and viewing geometry. As a result, the approach on topographic effect normalization in hyperspectral data can effectively reduce the variation in detected radiance due to changes in forest illumination, progress the classification of forest cover.

• 대한원격탐사학회지
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• 제39권3호
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• pp.269-282
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• 2023

본 연구는 딥러닝 모델(deep learning model)을 활용하여 토지피복분류를 수행하였으며 입력 이미지의 크기, Stride 적용 등 데이터세트(dataset)의 조절을 통해 토지피복분류를 위한 최적의 딥러닝 모델 선정을 목적으로 하였다. 적용한 딥러닝 모델은 3종류로 Encoder-Decoder 구조를 가진 U-net과 DeeplabV3+, 두 가지 모델을 결합한 앙상블(Ensemble) 모델을 활용하였다. 데이터세트는 RapidEye 위성영상을 입력영상으로, 라벨(label) 이미지는 Intergovernmental Panel on Climate Change 토지이용의 6가지 범주에 따라 구축한 Raster 이미지를 참값으로 활용하였다. 딥러닝 모델의 정확도 향상을 위해 데이터세트의 질적 향상 문제에 대해 주목하였으며 딥러닝 모델(U-net, DeeplabV3+, Ensemble), 입력 이미지 크기(64 × 64 pixel, 256 × 256 pixel), Stride 적용(50%, 100%) 조합을 통해 12가지 토지피복도를 구축하였다. 라벨 이미지와 딥러닝 모델 기반의 토지피복도의 정합성 평가결과, U-net과 DeeplabV3+ 모델의 전체 정확도는 각각 최대 약 87.9%와 89.8%, kappa 계수는 모두 약 72% 이상으로 높은 정확도를 보였으며, 64 × 64 pixel 크기의 데이터세트를 활용한 U-net 모델의 정확도가 가장 높았다. 또한 딥러닝 모델에 앙상블 및 Stride를 적용한 결과, 최대 약 3% 정확도가 상승하였으며 Semantic Segmentation 기반 딥러닝 모델의 단점인 경계간의 불일치가 개선됨을 확인하였다.