• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.11a
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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.

• Korean Journal of Remote Sensing
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• v.5 no.1
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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.

• Korean Journal of Remote Sensing
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• v.23 no.5
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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.

• Journal of the Korean Association of Geographic Information Studies
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• v.16 no.3
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• pp.103-114
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• 2013

In this study, we established the ortho mosaic imagery on the Korean Peninsula using KOMPSAT-2 images and conducted an accuracy assessment. Rational Polynomial Coefficient(RPC) modeling results were mostly less than 2 pixels except for mountainous regions which was difficult to select a Ground Control Point(GCP). Digital Elevation Model(DEM) which was made using the digital topographic map on the scale of 1:5,000 was used for generating an ortho image. In the case of inaccessible area, the Shuttle Radar Topography Mission(SRTM) DEM was used. Meanwhile, the ortho mosaic image of the Korean Peninsula was produced by each ortho image aggregation and color adjustment. An accuracy analysis for the mosaic image was conducted about a 1m color fusion image. In order to verify a geolocation accuracy, 813 check points which were acquired by field survey in South Korea were used. We found that the maximum error was not to exceed 5m(Root Mean Square Error : RMSE). On the other hand, in the case of inaccessible area, the extracted check points from a reference image were used for accuracy analysis. Approximately 69% of the image has a positional accuracy of less than 3m(RMSE). We found that the seam-line accuracy among neighboring image was very high through visual inspection. However, there were a discrepancy with 1 to 2 pixels at some mountainous regions.

• Proceedings of the KSRS Conference
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• 2005.10a
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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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• v.3 no.1
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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.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.4
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• pp.189-199
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• 2014

Floodplain is a flat plain between levees and rivers. This paper suggests a methodology for analyzing the land uses in the Nakdong River floodplain using the RapidEye imagery and the given LiDAR(LIght Detection And Ranging) DEM(Digital Elevation Models). First, the levee boundaries are generated using the LiDAR DEM, and the area of the floodplain is extracted from the given RapidEye imagery. The land uses in the floodplain are identified in the extracted RapidEye imagery by the ISODATA(Iterative Self-Organizing Data Analysis Technique Analysis) clustering. The overall accuracy of the identified land uses by the ISODATA clustering is 91%. Analysis of the identified land uses in the floodplain is implemented by counting the number of the pixels constituting the land cover clusters. The results of this research shows that the area of the river occupies 46%, the area of the bare soil occupies 36%, the area of the marsh occupies 11%, and the area of the grass occupies 7% in the identified floodplain.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.3
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• pp.219-225
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• 2008

There are many problems in monitering environmental change around of nuclear power station, because interesting area is coastal and relatively large. The ground resolution of Landsat ETM+ imagery is high (30 m), but this imagery does not have enough informations for conducting atmospheric correction in evaluating sea surface temperatures. On the other hand, while it is possible to conduct atmospheric correction using MODIS imagery with it's two infrared bands, it's resolution is relatively low (1 km). Therefore, atmospheric corrected high resolution temperature information can be obtained from these two satellite images. In this study, digital numbers of Landsat ETM+ data in interesting area are georeferenced, converted to effective temperatures based on radiance value, and then the atmospheric correction is conducted using MODIS data. As a result, about $3.5^{\circ}C$ temperature differences were detected in comparing sea surface temperature of the surrounding area of Uljin nuclear power station with it of the same area located 5km far east.

• Korean Journal of Remote Sensing
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• v.26 no.3
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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.

• Proceedings of the KSRS Conference
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• 2008.10a
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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.