• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2006.04a
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• pp.229-234
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• 2006

On May 31, 2003. Landsat 7 experienced an anomaly causing the Scan Line Corrector(SLC) to stop functioning normally. The SLC-off causes individual scan lines to alternately overlap and then leave large gaps at the edge of the Image. A many scientists with ongoing experience using ETM+ data evaluated the scientific usability and validity of Landsat 7 products containing the SLC anomaly The best reference scene for gap-filling is the other SLC-on Landsat scene that provide same resolution, few changes, and similar data acquisition. But receiving of Landsat imagery is not stable in Korea. So SPOT image can be another alternative solution because it is a steady-state multispectral satellite image as Landsat image. In this study, we filled the SLC-off gap s of 2, 3, 4 bands using SPOT image by a local regression technique, and assigned the optimum spectral value to gaps of 1, 5, 7 bands based on a spectral adjacency. Through this process, we could restore Landsat SLC-off image and evaluated the accuracy of the results.

• Journal of Korean Society for Geospatial Information Science
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• v.14 no.4 s.38
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• pp.61-70
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• 2006

This paper presents photogrammetric processing to generate digital elevation models using SPOT-5 HRG stereo images and deals with the accuracy potential of HRG (High Resolution Geometry) supermode imagery for DEM generation. After bundle adjustment was preformed for sensor modelling, digital surface models were generated through the procedures of Epipolar image resampling and image matching. The DEM extracted from HRG imagery was compared along several test sections with the the refernce DEM which was obtained from the digital topographic maps of a scale of 1 to 5000. The ratio of the zone with DEM errors less than 5m to the whole zone was 53.8%, and about 2.5m RMSE was showed when assuming that the zones larger than 5m were affected by clouds, water bodies and buildings and excluding those zones from accuracy evaluation. In addition, the three-dimensional bird's eye view model and 3D building model were producted based on the DSM which was extracted from SPOT-5 HRG data.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.286-288
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• 2003

In this paper, we present our implementation of the direct camera model (image to ground) for SPOT5 and use it to assess the geometric accuracy of SPOT5 imagery. Our assessment confirms the location accuracy of SPOT5 imagery (without use of GCPs) is less than 50m. We further introduce a few attitude parameters to refine the camera model with GCPs. The model is applied to two SPOT5 supermode images, one near vertical, incidence angle of 3 degrees, and one far oblique, incidence angle of 27 degrees. The results show that accuracy (rms of check points) of about one pixel (2.5m) can be achieved with about 4 GCPs by using only 3 parameters to correct the yaw, pitch and roll of the satellite.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.357-360
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• 2005

Soil loss is widely recognized as a threat to farm livelihoods and ecosystem integrity worldwide. Soil loss prediction models can help address long-range land management planning under natural and agricultural conditions. Even though it is hard to find a model that considers all forms of erosion, some models were developed specifically to aid conservation planners in identifying areas where introducing soil conservation measures will have the most impact on reducing soil loss. Revised Universal Soil Loss Equation (RUSLE) computes the average annual erosion expected on hillslopes by multiplying several factors together: rainfall erosivity (R), soil erodibility (K), slope length and steepness (LS), cover management (C), and support practice (P). The value of these factors is determined from field and laboratory experiments. This study calculated soil erosion using GIS-based RUSLE model in Imha basin and examined soil erosion source area using SPOT 5 high-resolution satellite image and land cover map. As a result of analysis, dry field showed high-density soil erosion area and we could easily investigate source area using satellite image. Also we could examine the suitability of soil erosion area applying field survey method in common areas (dry field & orchard area) that are difficult to confirm soil erosion source area using satellite image.

• Korean Journal of Geomatics
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• v.1 no.1
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• pp.1-5
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• 2001

This paper presents an investigation into the operational comparison of SPOT triangulation to build GCP library by analytical plotter and DPW (digital photogrammetric workstation). GCP database derived from current SPOT images can be used to other image sensors of satellite, if any reasons, such as lack of topographic maps or GCPs. But, general formulation of a photogrammetric process for GCP measurement has to take care of the scene interpretation problem. There are two classical methods depending on whether an analytical plotter or DPW is being used. Regardless of the method used, the measurement of GCPs is the weakest point in the automation of photogrammetric orientation procedures. To make an operational comparison, five models of SPOT panchromatic images (level 1A) and negative films (level 1AP) were used. Ten images and film products were used for the five GRS areas. Photogrammetric measurements were carried out in a manual mode on P2 analytical plotter and LH Systems DPW770. We presented an approach for exterior orientation of SPOT images, which was based on the use of approximately eighty national geodetic control points as GCPs which located on the summit of the mountain. Using sixteen well-spaced geodetic control points per model, all segments consistently showed RMS error just below the pixel at the check points in analytical instrument. In the case of DPW, half of the ground controls could not found or distinguished exactly when we displayed the image on the computer monitor. Experiment results showed that the RMS errors with DPW test was fluctuated case by case. And the magnitudes of the errors were reached more than three pixels due to the lack of image interpretation capability. It showed that the geodetic control points is not suitable as the ground control points in DPW for modeling the SPOT image.

• Journal of Biomedical Engineering Research
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• v.28 no.5
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• pp.601-608
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• 2007

2 Dimensional Gel Electrophoresis(2DGE) is an essentialmethodology for analysis on the expression of various proteins. For example, information for the location, mass, expression, size and shape of the proteins obtained by 2DGE can be used for diagnosis, prognosis and biological progress by comparison of patients with the normal persons. Protein spot matching for this purpose is comparative analysis of protein expression pattern for the 2DGE images generated under different conditions. However, visual analysis of protein spots which are more than several hundreds included in a 2DGE image requires long time and heavy effort. Furthermore, geometrical distortion makes the spot matching for the same protein harder. In this paper, an iterative algorithm is introduced for more efficient spot matching. Proposed method is first performing global matching step, which reduces the geometrical difference between the landmarks and the spot to be matched. Thus, movement for a spot is defined by a weighted sum of the movement of the landmark spots. Weight for the summation is defined by the inverse of the distance from the spots to the landmarks. This movement is iteratively performed until the total sum of the difference between the corresponding landmarks is larger than a pre-selected value. Due to local distortion generally occurred in 2DGE images, there are many regions in whichmany spot pairs are miss-matched. In the second stage, the same spot matching algorithm is applied to such local regions with the additional landmarks for those regions. In other words, the same method is applied with the expanded landmark set to which additional landmarks are added. Our proposed algorithm for spot matching empirically proved reliable analysis of protein separation image by producing higher accuracy.

• Journal of Korea Water Resources Association
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• v.38 no.11
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• pp.927-935
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• 2005

Soil erosion by rainfall is important factor for basin management because it reduces reservoir capacity and breaks out the contamination of water caused by turbid water. Recently, soil erosion study with GIS is in progress but does not consider soil erosion source area. This study calculated soil erosion amount using GIS-based soil erosion model in Imha basin and examined soil erosion source area using SPOT 5 High-resolution satellite image and land cover map. As a result of analysis, dry field showed high-density soil erosion area and we could easily investigate source area using satellite image. Also we could examine the suitability of soil erosion area by applying field survey method in common areas such as dry field and orchard area those are difficult to confirm soil erosion source area using satellite image.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1165-1167
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• 2003

Geometric corrections are required to compensate skew effects, earth rotation effects and so on. Parameters for geometric modeling can be acquired from the metadata information. These parameters allow to locate on ground every pixel of acquired images. In this paper, we tested the precision of geometric modeling of linear pushbroom images, acquired by SPOT 3 and 5 using the satellite orbit information itself without additional external data. The result acquired from examination to recovery the geometry of image using 30 GCPs have about 650m RMSE in SPOT 3 and about 170m RMSE in SPOT 5.

• Journal of the Korean Association of Geographic Information Studies
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• v.2 no.1
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• pp.32-44
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• 1999

Texture features can be incorporated in classification procedure to resolve class confusions. However, there have been few application-oriented studies made to evaluate the relative powers of texture analysis methods in a particular environment. This study evaluates the increases in the land-cover classification accuracy of the SPOT HRV multispectral data of Pusan Metropolitan area from texture processing. Twenty-four texture measures were derived from the SPOT HRV band 3 image. Each of these features were used in combination with the three spectral images in the classification of 10 land-cover classes. Supervised training and a Gaussian maximum likelihood classifier were used in the classification. It was found that while entropy produces the best empirical results in terms of the overall classification, other texture features can also largely improve the classification accuracies obtained by the use of the spectral images only. With the inclusion of texture, the classification for each category improves. Specially, urban built-up areas had much increase in accuracy. The results indicate that texture size 5 by 5 and 7 by 7 may be suitable at land cover classification of Pusan Metropolitan area.

• Proceedings of the Korea Contents Association Conference
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• 2005.11a
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• pp.335-339
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• 2005

Digital elevation models(DEM) were generated from SPOT-5 HRG supermode imagery through photogrammetric processing. The reference DEMs were obtained from digital topographic maps of 1/5000 scaleas for analyzing the accuracy of the generated DEMs. The DEMs extracted from HRG stereo image data were compared with digital topograpic map DEMs on several test sections. And digital surface models(DSM) and 3D building model was produced.