• 한국측량학회:학술대회논문집
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• 한국측량학회 2004년도 추계학술발표회 논문집
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• pp.269-274
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• 2004

Recent adoption of the generalized sensor model to IKONOS and Quickbird satellite imagery have promoted various research activities concerning alternative sensor models which can replace conventional physical sensor models. For example, there are the Rational Function Model(RFM), the Direct Linear Transform(DLT) and the polynomial transform. In this paper, the DLT model which uses just a few number of GCPs was suggested. To evaluate the accuracy of the proposed DLT model, the RFM using 35 GCPs and the bias compensation method(Fraser et al., 2003) were compared with it. Quantitative evaluation of 3B positioning results were performed with independent check points and the digital elevation models(DEMs). In result, a 1.9- to 2.2-m positioning accuracy was achieved for modeling and DEM accuracy is similar to the accuracy of the other model methods.

• 대한원격탐사학회지
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• 제5권1호
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• pp.13-27
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• 1989

In recent years satellite data have been increasingly used for the analysis of floodprone areas. This study was carried out to demonstrate the usefulness of repetitive satellite imagery in monitoring flood levels of the Pyungchang watershed. Runoff characteristics parameters were analyzed by Soil Conservation Service(SCS) Runoff Curve Number(RCN) based on Landsat imagery and Digital Terrain Model data. The RCN average within the watershed was calculated from RCN estimates for all the pixels(picture elements) and adjusted by antecedent precipitation conditions. The direct runoff hydrograph was derived from the unit hydrograph using SCS dimensionless unit hydrograph and effective rainfalls estimated by the SCS method. In comparsion of the direct runoff hydrograph with the measured rating curve their peak times differ by one hour and peak discharges differ by 5.9 percents of the discharge from each other. It was shown that repetitive satellite image could be very useful in timely estimating watershed runoffs and evaluating ever-changing surface conditions of a river basin.

• 대한원격탐사학회지
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• 제23권5호
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• pp.455-464
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• 2007

Lee(2007) suggested the Point-Jacobian iteration MAP estimation(PJIMAP) for noise removal of the images that are corrupted by multiplicative speckle noise. It is to find a MAP estimation of noisy-free imagery based on a Bayesian model using the lognormal distribution for image intensity and an MRF for image texture. When the image intensity is logarithmically transformed, the speckle noise is approximately Gaussian additive noise, and it tends to a normal probability much faster than the intensity distribution. The MRF is incorporated into digital image analysis by viewing pixel types as states of molecules in a lattice-like physical system. In this study, the MAP estimation is computed by the Point-Jacobian iteration using adaptive parameters. At each iteration, the parameters related to the Bayesian model are adaptively estimated using the updated information. The results of the proposed scheme were compared to them of PJIMAP with SAR simulation data generated by the Monte Carlo method. The experiments demonstrated an improvement in relaxing speckle noise and estimating noise-free intensity by using the adaptive parameters for the Ponit-Jacobian iteration.

• 한국지리정보학회지
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• 제16권3호
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• pp.103-114
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• 2013

본 연구에서는 아리랑위성 2호 영상자료를 이용하여 한반도 전역에 대한 정사모자이크영상을 생성하고 정확도 평가를 실시하였다. Rational Polynomial Coefficient(RPC) 모델링 결과 지상기준점(Ground Control Point : GCP) 선점이 힘든 산악지역 등을 제외하고는 대부분 2화소 이내로 나타났다. 정사영상 제작에는 축척 1:5,000 수치지형도를 이용하여 제작한 수치고도모델(Digital Elevation Model : DEM)이 사용되었는데, 수치지형도가 존재하지 않는 접근불능지역의 경우 Shuttle Radar Topography Mission(SRTM) DEM이 사용되었다. 한편 한반도 정사모자이크영상은 정사영상 집성과 색상보정을 통해 생성되었으며, 모자이크영상에 대한 정확도 분석은 1m 칼라 합성영상에 대해 실시하였다. 위치정확도 검증을 위하여 남한지역에서 현지측량을 통해 확보한 813 검사점(Check Point)이 사용되었으며 Root Mean Square Error(RMSE) 계산을 통하여 최대 5m 이내의 오차가 확인되었다. 한편 접근불능지역 경우 참조영상(Reference Image) 에서 추출한 검사점을 이용하여 정확도 분석을 실시하였는데 3m(RMSE) 이내의 위치정확도를 가지는 영상이 약 69% 정도 되는 것으로 확인되었다. 또한 인접영상과의 접합정확도 육안평가에서는 일부 산악지역에서의 약 1~2 화소 이격을 제외하고는 잘 일치하고 있는 것으로 확인되었다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.667-670
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• 2005

Ground control points(GCPs) can be extracted from SAR data given precise orbit for DTM generation using optic images and other SAR data. In this study, we extract GCPs from ERS SAR data and SRTM DEM. Although it is very difficult to identify GCPs in ERS SAR image, the geometry of optic image and other SAR data are able to be corrected and more precise DTM can be constructed from stereo optic images. Twenty GCPs were obtained from the ERS SAR data with precise Delft orbit information. After the correction was applied, the mean values of planimetric distance errors of the GCPs were 3.7m, 12.1 and -0.8m with standard deviations of 19.9m, 18.1, and 7.8m in geocentric X, Y, and Z coordinates, respectively. The geometries of SPOT stereo pair were corrected by 13 GCPs, and r.m.s. errors were 405m, 705m and 8.6m in northing, easting and height direction, respectively. And the geometries of RADARS AT stereo pair were corrected by 12 GCPs, and r.m.s. errors were 804m, 7.9m and 6.9m in northing, easting and height direction, respectively. DTMs, through a method of area based matching with pyramid images, were generated by SPOT stereo images and RADARS AT stereo images. Comparison between points of the obtained DTMs and points estimated from a national 1 :5,000 digital map was performed. For DTM by SPOT stereo images, the mean values of distance errors in northing, easting and height direction were respectively -7.6m, 9.6m and -3.1m with standard deviations of 9.1m, 12.0m and 9.1m. For DTM by RADARSAT stereo images, the mean values of distance errors in northing, easting and height direction were respectively -7.6m, 9.6m and -3.1m with standard deviations of 9.1m, 12.0m and 9.1m. These results met the accuracy of DTED level 2

• Korean Journal of Geomatics
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• 제3권1호
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• pp.33-41
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• 2003

Every year, several typhoons hit the Korean peninsula and cause severe damage. For the prevention and accurate estimation of these damages, real time or almost real time flood information is essential. Because of weather conditions, images taken by optic sensors or LIDAR are sometimes not appropriate for an accurate estimation of water areas during typhoon. In this case SAR (Synthetic Aperture Radar) images which are independent of weather condition can be useful for the estimation of flood areas. To get detailed information about floods from satellite imagery, accurate classification of water areas is the most important step. A commonly- and widely-used classification methods is the ML(Maximum Likelihood) method which assumes that the distribution of brightness values of the images follows a Gaussian distribution. The distribution of brightness values of the SAR image, however, usually does not follow a Gaussian distribution. For this reason, in this study the ANN (Artificial Neural Networks) method independent of the statistical characteristics of images is applied to the SAR imagery. RADARS A TSAR images are primarily used for extraction of water areas, and DEM (Digital Elevation Model) is used as supplementary data to evaluate the ground undulation effect. Water areas are also extracted from KOMPSAT image achieved by optic sensors for comparison purpose. Both ANN and ML methods are applied to flat and mountainous areas to extract water areas. The estimated areas from satellite imagery are compared with those of manually extracted results. As a result, the ANN classifier performs better than the ML method when only the SAR image was used as input data, except for mountainous areas. When DEM was used as supplementary data for classification of SAR images, there was a 5.64% accuracy improvement for mountainous area, and a similar result of 0.24% accuracy improvement for flat areas using artificial neural networks.

• 한국지리정보학회지
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• 제17권4호
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• pp.189-199
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• 2014

범람원(floodplain)은 제방과 하천 사이에 존재하는 평탄하고 낮은 지역을 의미하며, 범람원 내 토지 이용 현황 분석은 하천유역의 효과적인 자원관리를 위해서 반드시 필요하다. 본 논문에서는 공간정보 자료인 LiDAR DEM 자료와 RapidEye 영상을 이용하여 낙동강 하천 범람원 내 토지 이용 현황 분석에 관한 연구를 진행하였다. 우선, DEM으로부터 제방 경계선을 추출하여 RapidEye 영상에서 연구대상지역 내 범람원의 범위를 설정하였다. 범람원의 범위를 설정한 뒤, RapidEye 영상에 ISODATA 클러스터링 및 post-classification 과정을 적용하여 범람원 내 토지피복 분류 작업을 진행하였다. ISODATA 클러스터링을 적용하여 분류된 범람원 내 토지피복은 91%의 분류 정확도를 가진다. 분류된 토지피복 클러스터들을 구성하는 픽셀들의 개수를 계산하여, 낙동강 범람원 내 토지 이용 현황에 관한 분석을 수행하였다. 본 연구를 통하여, 연구대상지역 범람원 내 하천의 면적은 46%, 나지의 면적은 36%, 습지의 면적은 11%, 그리고 초지의 면적은 7%라는 사실을 알 수 있었다.

• 한국측량학회지
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• 제26권3호
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• pp.219-225
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• 2008

원자력 발전소의 주변 지역은 해안지역이고 비교적 광범위하므로, 환경 변화를 감시하는데 많은 어려움이 있다. Landsat ETM+영상은 해상도가 30m 급이나 온도정보 추출에 있어 대기보정을 못하는 문제를 가지고 있다. MODIS 영상의 경우 2개의 적외선 밴드를 이용하여 대기보정된 비교적 적확한 온도를 추출할 수 있으나 해상도가 1km이다. 따라서, 두 위성영상의 자료를 이용한다면 대기보정된 고해상도의 온도자료를 추출할 수 있다. 본 연구에서는 대상지역의 Landsat ETM+영상에 대하여 기하보정을 수행하고, 방사휘도 및 온도를 산정한 후 MODIS영상을 이용하여 대기보정을 수행하였다. 그 결과 울진 원자력발전소 주변 연근해 지역과 온배수의 영향을 받지 않는 동쪽으로 5km 떨어진 동일 면적의 지역과 비교하여 보았을 때 약 $3.5^{\circ}C$ 높은 것을 알 수 있었다.

• 대한원격탐사학회지
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• 제26권3호
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• pp.347-359
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• 2010

Ortho-photos provide valuable spatial and spectral information for various Geographic Information System (GIS) and mapping applications. The absence of relief displacement and the uniform scale in ortho-photos enable interested users to measure distances, compute areas, derive geographic locations, and quantify changes. Differential rectification has traditionally been used for ortho-photo generation. However, differential rectification produces serious problems (in the form of ghost images) when dealing with large scale imagery over urban areas. To avoid these artifacts, true ortho-photo generation techniques have been devised to remove ghost images through visibility analysis and occlusion detection. So far, the Z-buffer method has been one of the most popular methods for true ortho-photo generation. However, it is quite sensitive to the relationship between the cell size of the Digital Surface Model (DSM) and the Ground Sampling Distance (GSD) of the imaging sensor. Another critical issue of true ortho-photo generation using high resolution satellite imagery is the scan line search. In other words, the perspective center corresponding to each ground point should be identified since we are dealing with a line camera. This paper introduces alternative methodology for true ortho-photo generation that circumvents the drawbacks of the Z-buffer technique and the existing scan line search methods. The experiments using real data are carried out while comparing the performance of the proposed and the existing methods through qualitative and quantitative evaluations and computational efficiency. The experimental analysis proved that the proposed method provided the best success ratio of the occlusion detection and had reasonable processing time compared to all other true ortho-photo generation methods tested in this paper.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
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• pp.11-13
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• 2008

This study proposes the method to use existing digital maps as one of the technologies to exclude individual differences that occur in the process of manually determining GCP for the geometric correction of KOMPSAT images and applying it to the images and to automate the generation of ortho-images. It is known that, in case high-resolution satellite images are corrected geometrically by using RPC, first order polynomials are generally applied as the correction formula in order to obtain good results. In this study, we matched the corresponding objects between 1:25,000 digital map and a KOMPSAT image to obtain the coefficients of the zero order polynomial and showed the differences in the pixel locations obtained through the matching. We performed proximity corrections using the Boolean operation between the point data of the surface linear objects and the point data of the edge objects of the image. The surface linear objects are road, water, building from topographic map.