• Journal of Korean Society on Water Environment
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• v.25 no.2
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• pp.193-204
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• 2009

The study was conducted investigation on land of D-dong in N city which is an urban area and D myeon of N city which is a suburban area, based on high resolution satellite image, to find out actual land usage. As for D-dong in N city, different rate between actual usage and official land information was 0.5~4.8% in terms of 5 major land types (paddy field, farm, ground, forest, and others). D myeon in N city posted 1.4~8.4%, which is higher than that of its counterpart. As for unit load, "land" which is large in terms of load presented a big difference between official information and actual usage. On the other hand, the levels of paddy, field, forest and others posted only small changes in load. In case of T-P, in particular, unit of each land type is lower than BOD and T-N, showing almost no changes in pollution loads.

• Journal of Korea Water Resources Association
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• v.36 no.6
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• pp.999-1012
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• 2003

The objective of this study is to test the applicability of CN values suggested using land cover and treatment classification of satellite image. Applicability test is based on the comparison of observed effective rainfall and computed one. The 3 case study areas, where are the upstream of Gyeongan stage station, the upstream of Baekokpo stage station Pyungchang River basin, and the upstream of Koesan Dam, are selected to test the proposed CN values and the hydrologic and meteorologic data, Landsat-7 ETM of 2000, soil map of 1:50,000 are collected for the selected areas. The results show that the computed CN values for three study cases are 71, 63, 66, respectively, and the errors between observed and computed effective rainfall are within about 30%. It can be concluded that the proposed CN values from this study for land cover and treatment classification of satellite image not only provides more accurate results for the computation of effective rainfall, but also suggest the objective CN values and effective rainfall.

• 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.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.220-223
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• 2004

Automatic image registration is an essential element of remote sensing because remote sensing system generates enormous amount of data, which are multiple observations of the same features at different times and by different sensor. The general process of automatic image registration includes three steps: 1) The extraction of features to be used in the matching process, 2) the feature matching strategy and accurate matching process, 3) the resampling of the data based on the correspondence computed from matched feature. For step 2) and 3), we have developed an algorithms for automated registration of satellite images with RANSAC(Random Sample Consensus) in success. However, for step 1), There still remains human operation to generate GCP Chips, which is time consuming, laborious and expensive process. The main idea of this research is that we are able to automatically generate GCP chips with comer detection algorithms without GPS survey and human interventions if we have systematic corrected satellite image within adaptable positional accuracy. In this research, we use SUSAN(Smallest Univalue Segment Assimilating Nucleus) algorithm in order to detect the comer. SUSAN algorithm is known as the best robust algorithms for comer detection in the field of compute vision. However, there are so many comers in high-resolution images so that we need to reduce the comer points from SUSAN algorithms to overcome redundancy. In experiment, we automatically generate GCP chips from IKONOS images with geo level using SUSAN algorithms. Then we extract reference coordinate from IKONOS images and DEM data and filter the comer points using texture analysis. At last, we apply automatically collected GCP chips by proposed method and the GCP by operator to in-house automatic precision correction algorithms. The compared result will be presented to show the GCP quality.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.11
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• pp.988-995
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• 2014

Two axis gimbal type X-band antenna system has been widely used to effectively transmit the real time image data from the observation satellite to the ground station. The micro-vibration generated by stepping motor actuation and imperfect intermeshed gear configuration of the antenna is one of the sources to degrade the image quality. To guarantee a high quality image of high resolution observation satellite, micro-vibration isolation of X-band antenna is required. In this paper, the X-band antenna vibration isolation system using pseudoelastic SMA(Shape Memory Alloy) mesh washer has been newly suggested. The basic characteristics of the SMA mesh washer isolator proposed in this study has been measured through static load tests and its effectiveness has been demonstrated by the micro-vibration isolation test of the X-band antenna.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.25 no.5
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• pp.313-320
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• 2015

A 2-axis gimbal-type X-band antenna has been widely used to effectively transmit the high resolution image data from the observation satellite to the desired ground station. However, a discontinuous stepper motor activation for rotating the pointing mechanism in azimuth and elevation directions induces undesirable micro-vibration disturbances which can result in the image quality degradation of a high-resolution observation satellite. To enhance the image quality of the observation satellite, attenuating the micro-vibration induced by an activation of the stepper motor for rotational movements of the antenna is important task. In this study, we proposed a low-rotational-stiffness blade gear applied to the output shaft of the stepper motor to obtain the micro-vibration isolation performance. The design of the blade gear was performed through the structure analysis such that this gear is satisfied with the margin of safety rule under the derived torque budget. In addition, the micro-vibration isolation performance of the blade gear was verified through the micro-vibration measurement test using the dedicated micro-vibration measurement device proposed in this study.

• Journal of Environmental Impact Assessment
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• v.15 no.2
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• pp.121-127
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• 2006

The conventional water quality measurements by point sampling provide only site specific temporal water quality information but not the synoptic geographic coverage of water quality distribution. To circumvent these limitations in temporal and spatial measurements, the use of remote sensing is increasingly involved in the water quality monitoring research. In other to assess a trophic state of Yongdam reservoir using satellite imagery data, I obtained Landsat ETM data and water quality data on 16th September and 18th October 2001. The approach involved acquisition of water quality samples from boats at 33 sites on 16th September and 30 sites on 18th October 2001, simultaneous with Landsat-7 satellite overpass. The correlation coefficients between the DN values of the imagery and the concentrations of chlorophyll-a were analyzed. The visible bands(band 1,2,3) and near infrared band(band 4) data of September image showed the correlation coefficient values higher than 0.9. The October image showed the correlation coefficient values about 0.7 due to the atmospheric effect and low variation of chlorophyll-a concentration. Regression models between the chrophyll-a concentration and DN values of the Landsat imagery data have been developed for each image. The regression model was determined based on the spectral characteristics of chlorophyll, so the green band(band 2) and near infrared band(band 4) were selected to generate a trophic state map. The coefficient of determination(R2) of the regression model for 16th September was 0.95 and that of the regression model for 18th October was 0.55. According to the trophic state map made based on Aizaki's TSI and chlorophyll-a concentration, the trophic state of Yongdam reservoir was mostly eutrophic state during this study.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.13 no.2
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• pp.141-151
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• 1995

In generating DTM as basic data to GIS, the use of existing map is difficult to aquire current data and the method using airphotos needs cost for stereoplotting and ground control surveying. So, the method of DTM generation by satellite imagery is promising because satellite is able to observe wide area at once. In this study the program for SPOT bundle adjustment and image matching based on Coarse to Fine method is developed and various image enhancement algorithm is used for more accurate DTM generation and also evaluation of accuracy was carried out. Further more, orthophoto, a bird's eye-view, contour map producing, net-work analysis and terrain analysis were performed for GIS applications using generated DTM in this study. Generated DTM using SPOT stereo imagery is useful for GIS applications such as automated mapping, facility management, national geographic information system. Moreover developed automatic DTM generation pro-gram is studied, tested and verified more to be applicable to all the area.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.4
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• pp.359-365
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• 2008

This paper focused on generation of more accurate DEM and analysis of accuracy. For this, we applied suitable sensor modeling technique for each satellite image and automatic pyramid matching using image pyramid was applied. Matching algorithm based on epipolarity and scene geometry also was applied for stereo matching. IKONOS, Quickbird, SPOT-5, Kompsat-2 were used for experiments. In particular, we applied orbit-attitude sensor modeling technique for Kompsat-2 and performed DEM generation successfully. All DEM generated show good quality. Assessment was carried out using USGS DTED and we also compared between DEM generated in this research and DEM generated from common software. All DEM had $9m{\sim}12m$ Mean Absolute Error and $13m{\sim}16m$ RMS Error. Experimental results show that the DEMs of good performance which is similar to or better than result of DEMs generated from common software.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.2
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• pp.163-171
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• 2012

High resolution satellite images have been used for building and road system analysis, landscape analysis, and ecological assessment for several years. However, in high resolution satellite images, shadows are necessarily cast by manmade objects such as buildings and over-pass bridges. This paper develops the shadow extraction procedures in urban area including various land-use classes, and the extracted shadow areas are evaluated by a manually digitized shadow map. For the shadow extraction, the Canny edge operator and the dilation filter are applied to make building edge buffer area. Also, the object-based segmentation was performed using Gram-Schmitt fusion image, and spectral and spatial parameters are calculated from the segmentation results. Finally, we proposed appropriate parameters and extraction rules for the shadow extraction. The accuracy of the shadow extraction results from the various assessment indices is 80% to 90%.