• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.727-731
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• 2003

ASTER image has some advantages for classification such as 15 spectral bands and 15m ${\sim}$ 90m spatial resolution. However, in the classification using general remote sensing image, shadow areas are often classified into water area. It is very difficult to divide shadow and water. Because reflectance characteristics of water is similar to characteristics of shadow. Many land cover items are consisted in one pixel which is 15m spatial resolution. Nowadays, very high resolution satellite image (IKONOS, Quick Bird) and Digital Surface Model (DSM) by air borne laser scanner can also be used. In this study, mixed pixel analysis of ASTER image has carried out using IKONOS image and DSM. For mixed pixel analysis, high accurated geometric correction was required. Image matching method was applied for generating GCP datasets. IKONOS image was rectified by affine transform. After that, one pixel in ASTER image should be compared with corresponded 15×15 pixel in IKONOS image. Then, training dataset were generated for mixed pixel analysis using visual interpretation of IKONOS image. Finally, classification will be carried out based on Linear Mixture Model. Shadow extraction might be succeeded by the classification. The extracted shadow area was validated using shadow image which generated from 1m${\sim}$2m spatial resolution DSM. The result showed 17.2% error was occurred in mixed pixel. It might be limitation of ASTER image for shadow extraction because of 8bit quantization data.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.5
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• pp.555-560
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• 2010

The geoscientists are very interested in a volcanic reactivity of Mt. Baekdu. Periodical observation and monitoring are thus needed to detect the topographic and environmental changes of Mt. Baekdu. It is, however, very restrictive to survey with difficulty of observer's accessibility in the field due to political problems. This study therefore is to produce digital elevation model (DEM) of Mt. Baekdu using SPOT-5 stereo images. The produced DEM is very not accurate because of using without ground control points (GCP). To correct the previously generated DEM, scale-invariant feature transform(SIFT) matching method is adopted with shuttle radar topography mission(SRTM) DEM of NASA Jet Propulsion Laboratory(JPL). The results of the produced DEM to SRTM DEM matching indicate that the corrected DEM from SPOT-5 stereo images has more detail topographic structures. In addition, difference of spatial distances between the corrected DEM and SRTM DEM are much smaller than non-corrected DEM.

• Korean Journal of Remote Sensing
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• v.20 no.2
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• pp.125-137
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• 2004

In case of using image sequence taken from a moving camera along a road in an urban area, general video mosaicing technique based on a single baseline cannot create 2-D image mosaics. To solve the drawback, this paper proposed a new image mosaicing technique through 3-D multi-baselines that can create image mosaics in 3-D space. The core of the proposed method is that each image frame has a dependent baseline, an equation of first order, calculated by using ground control point (GCP) of optical flows. The proposed algorithm consists of 4 steps: calculation of optical flows using hierarchical strategy, calculation of camera exterior orientation, determination of multi-baselines, and seamless image mosaics. This paper realized and showed the proposed algorithm that can create efficient image mosaics in 3-D space from real image sequence.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.1
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• pp.239-246
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• 2019

The drone photogrammetry is actively utilized for obtaining highly accurate spatial information and other various monitoring purposes. It is general to plan the drone photogrammetry by referring to previous experiences or cases in order to obtain the required accuracy, but the drone photogrammetry is often carried out again due to poor accuracy. Since the required spatial accuracy of the drone photogrammetry process result becomes the means of objective evaluation regardless of the type of result, it should be determined carefully. Therefore, it is necessary to determine flight height, overlap, number and arrangement of ground control point, and exterior orientation factor acquisition method in order to meet the required 3D positional accuracy for the design of drone photogrammetry project. In this study, previous study cases for the analysis of drone photogrammetry accuracy were carefully analyzed and verified by applying such cases to testing area, and design guideline of drone photogrammetry project for a small area was prepared based on the analysis result. The presented project design guideline is expected to be a great help to business practice although it is not perfect, and if the design guideline is prepared through comprehensive analysis in future, it would be possible to provide a perfect manual.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.2
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• pp.247-254
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• 2010

In this paper, a new approach has been studied correcting the geometric distortion of SPOT 4 imagery. Two new equations were induced by the relationship between satellite and the Earth in the space. line-of-sight (LOS) vector adjustment model for SPOT 4 imagery was implemented in this study. This model is to adjust LOS vector under the assumption that the orbital information of satellite provided by receiving station is uncertain and this uncertainty makes a constant error over the image. This model is verified using SPOT 4 satellite image with high look angle and thirty five ground points, which include 10 GCPs(Ground Control Points) and 25 check points, measured by the GPS. In total thirty five points, the geometry of satellite image calculated by given satellite information(such as satellite position, velocity, attitude and look angles, etc) from SPOT 4 satellite image was distorted with a constant error. Through out the study, it was confirmed that the LOS vector adjustment model was able to be applied to SPOT4 satellite image. Using this model, RMSEs (Root Mean Square Errors) of twenty five check points taken by increasing the number of GCPs from two to ten were less than one pixel. As a result, LOS vector adjustment model could efficiently correct the geometry of SPOT4 images with only two GCPs. This method also is expected to get good results for the different satellite images that are similar to the geometry of SPOT images.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.4_1
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• pp.319-326
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• 2014

The accurate geo-referencing processes that apply ground control points is prerequisite for effective end use of HRSI (High-resolution satellite imagery). Since the conventional control point acquisition by human operator takes long time, demands for the automated matching to existing reference data has been increasing its popularity. Among many options of reference data, the airborne LiDAR (Light Detection And Ranging) data shows high potential due to its high spatial resolution and vertical accuracy. Additionally, it is in the form of 3-dimensional point cloud free from the relief displacement. Recently, a new matching method between LiDAR data and HRSI was proposed that is based on the image projection of whole LiDAR data into HRSI domain, however, importing and processing the large amount of LiDAR data considered as time-consuming. Therefore, we wmotivated to ere propose a local LiDAR chip generation for the HRSI geo-referencing. In the procedure, a LiDAR point cloud was rasterized into an ortho image with the digital elevation model. After then, we selected local areas, which of containing meaningful amount of edge information to create LiDAR chips of small data size. We tested the LiDAR chips for fully-automated geo-referencing with Kompsat-2 and Kompsat-3 data. Finally, the experimental results showed one-pixel level of mean accuracy.

• Korean Journal of Remote Sensing
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• v.35 no.5_1
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• pp.705-714
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• 2019

Precision positioning is necessary for various use of high-resolution UAV images. Basically, GCP is used for this purpose, but in case of emergency situations or difficulty in selecting GCPs, the data shall be obtained without GCPs. This study proposed a method of improving positional accuracy for x, y coordinate of UAV based 3 dimensional point cloud data generated without GCPs. Road vector file by the public data (Open Data Portal) was used as reference data for improving location accuracy. The geometric correction of the 2 dimensional ortho-mosaic image was first performed and the transform matrix produced in this process was adopted to apply to the 3 dimensional point cloud data. The straight distance difference of 34.54 m before the correction was reduced to 1.21 m after the correction. By confirming that it is possible to improve the location accuracy of UAV images acquired without GCPs, it is expected to expand the scope of use of 3 dimensional spatial objects generated from point cloud by enabling connection and compatibility with other spatial information data.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.158-174
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• 2018

The leaf area index (LAI) is a major factor explaining the photosynthesis of vegetation, evapotranspiration, and energy exchange between the earth surface and atmosphere, and there have been studies on accurate and applicable LAI estimation methods. This study aimed to investigate the relationship between the actual LAI data, UAV image-based vegetation index, canopy height and satellite image (Sentinel-2) LAI and to present an effective LAI estimation method using UAV. As a result, among the six vegetation indices in this study, NDRE ($R^2=0.496$) and CIRE ($R^2=0.443$), which contained red-edge band, showed a high correlation. The application of the canopy height model data to the vegetation index improved the explanatory power of the LAI. In addition, in the case of NDVI, the saturation problem caused by the linear relationship with LAI was addressed. In this study, it was possible to estimate high resolution LAI using UAV images. It is expected that the applicability of such data will be improved if calibration and correction steps are carried out for various vegetation and seasonal images.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.4_1
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• pp.299-309
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• 2014

This paper evaluated the possibility for 1/5,000 digital topographic mapping by using PLEIADES images of 0.5m GSD(Ground Sampling Distance) resolution that has recently launched. Those results of check points by applying the initial RPC(Rational Polynomial Coefficient) of PLEIADES images came out as; RMSE of those were $X={\pm}1.806m$, $Y={\pm}2.132m$, $Z={\pm}1.973m$. Also, if we corrected geometric correction using 16 GCP(Ground Control Point)s, the results of RMSE became $X={\pm}0.104m$, $Y={\pm}0.171m$, $Z={\pm}0.036m$, and t he RMSE of check points were $X={\pm}0.357m$, $Y={\pm}0.239m$, $Z={\pm}0.188m$; which of those results indicated the accuracy of standard adjustment complied in error tolerances of the 1/5,000 scale. Additionally, we converted coordinates of points, obtained by TerraSAR. for comparing with measurements from GPS(Global Positioning System) surveying. The RMSE of comparing converted and GPS points were $X={\pm}0.818m$, $Y={\pm}0.200m$, $Z={\pm}0.265m$, which confirmed the possibility for 1/5,000 digital topographic mapping with PLEIADES images and GCPs. As method of obtaining GCPs in unaccessible area, however, the outcome evaluation of GCPs extracted from TerraSAR images was not acceptable for 1/5,000 digital topographic mapping. Therefore, we considered that further researches are needed on applicability of GCPs extracted from TerraSAR images for future alternative method.