• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.1
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• pp.31-37
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• 2007

Since the government-owned land is the national property, the country is responsible for the management. Although one can see the recent activities of government to efficiently manage and maintain the government-owned land, its characteristics are not well reflected on the current managing methods. Obviously, efficient and prefer methods for the field survey is necessary for efficient management. In this study, the current management methods focused on the site srvey are analyzed and problems are deduced. Basically the current methods depending on the graphic information and cadastral survey results are compared with real illegal occupancy case. The investigation clearly shows the necessity of the cadastral survey and proved the current method is not sufficient to detect illegal occupancy on government-owned land. It is expected that this study contributes on establishing an efficient management methods for the government-owned land.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.4
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• pp.421-430
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• 2010

Image segmentation technique is becoming increasingly important in the field of remote sensing image analysis in areas such as object oriented image classification to extract object regions of interest within images. This paper presents a new method for image segmentation in High Resolution Remote Sensing Image based on Improved Seeded Region Growing (ISRG) and Region merging. Firstly, multi-spectral edge detection was done using an entropy operator in pan-sharpened QuickBird imagery. Then, the initial seeds were automatically selected from the obtained multi-spectral edge map. After automatic selection of significant seeds, an initial segmentation was achieved by applying ISRG to consider spectral and edge information. Finally the region merging process, integrating region texture and spectral information, was carried out to get the final segmentation result. The accuracy assesment was done using the unsupervised objective evaluation method for evaluating the effectiveness of the proposed method. Experimental results demonstrated that the proposed method has good potential for application in the segmentation of high resolution satellite images.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.4
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• pp.205-211
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• 2018

Remote estimation of water quality via radiometric instruments provides a convenient means for monitoring environmental changes in water bodies in wide areas. Combined with platforms such as satellite, manned/unmanned vehicles, it reduces the measurement cost and time for acquiring water quality information on the interested target areas. To develop accurate retrieval algorithms, however, acquisition of in-situ measurements from various optical environment is critical. In this study, hyperspectral radiometric measurements, the coincident water quality variables, and its optical properties were obtained to analyze the optical environment of the study area. Field data collected around the Tongyeong area showed that the area has optically complex environment, with occasional outbreak of red tide in summer seasons. Effect of water constituents on the optical variables (remote sensing reflectance and absorption coefficients) were qualitatively analyzed.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.277-282
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• 2006

It is well known that Kalman filtering is an optimal real-time data fusion method for GPS/INS integration. However, it has some limitations in terms of stability, adaptability and observability. A Kalman filter can perform optimally only when its dynamic model is correctly defined and the noise statistics for the measurement and process are completely known. It is found that estimated Kalman filter states could be influenced by several factors, including vehicle dynamic variations, filter tuning results, and environment changes, etc., which are difficult to model. Neural networks can map input-output relationships without apriori knowledge about them; hence a proper designed neural network is capable of learning and extracting these complex relationships with enough training. This paper presents a GPS/INS integrated system that combines Kalman filtering and neural network algorithms to improve navigation solutions during GPS outages. An Extended Kalman filter estimates INS measurement errors, plus position, velocity and attitude errors etc. Kalman filter states, and gives precise navigation solutions while GPS signals are available. At the same time, a multi-layer neural network is trained to map the vehicle dynamics with corresponding Kalman filter states, at the same rate of measurement update. After the output of the neural network meets a similarity threshold, it can be used to correct INS measurements when no GPS measurements are available. Selecting suitable inputs and outputs of the neural network is critical for this hybrid method. Detailed analysis unveils that some Kalman filter states are highly correlated with vehicle dynamic variations. The filter states that heavily impact system navigation solutions are selected as the neural network outputs. The principle of this hybrid method and the neural network design are presented. Field test data are processed to evaluate the performance of the proposed method.

• Journal of Korean society of Dental Hygiene
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• v.11 no.3
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• pp.363-372
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• 2011

Objectives : The purpose of this study was to pursue an efficient operating plan by surveying the cognition and demand level for major deepening course. Methods : Questionnaire survey was carried out targeting 135 dental hygienists who work in Cheonan and neighboring region. The collected data was performed frequency & percentage, T-test and ANOVA analysis. Results : 1. As for dental hygienists' acquiring academic degree, 77.0% of them responded to have interest. As for a desired route of acquiring academic degree, the major deepening course or Credit Bank System was the highest with 62.2%. 2. As a result of surveying cognition on major deepening course, 73.3% responded to know. A route of having come to know was the largest in senior or friend with 34.8%. Necessity of major deepening course was responded to be necessary with 89.7%. 89.1% of them clarified to have intention of acquiring. 3. The curricular subject, which is desired to be learnt for a plan of operating major deepening course, was the highest in the major field with 63.0%. 4. As a result of comparing an interest, necessity, and intention of acquisition on major deepening course depending on general characteristics, the statistically significant difference wasn't shown. Conclusions : These results suggest that major deepening of course through active public should be aware that many dental hygienists will be subject to a variety of programs and development of clinical course and a practical hands-on education is expected to be strengthened.

• 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.

• Journal of Korean Society of Forest Science
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• v.76 no.4
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• pp.348-356
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• 1987

A new simple method to estimate the earth quantity which is basic data for making the plan of mountain forest road is tried to develop as one of ways to reduce time cost of plan making. The zero-line surveying method, the concept of 2/3 road width in cut-away part and of same quantity between cut-away and fill-up earth which are the backgrounds to develop this method is introduced and explaned also it's theoritical propriety. Under the precondition which have to apply above concepts for constructing the mountain forest road the exchange table for estimating the earth quantity is made like table 3 and 4 through being calculated by a trigonometric function. Table 3 can be used to estimate the earth quantity on the cut-away road-width according to slope of terrain and different road-width, and table 4 can be applied to calculate the quantity of cut-away earth when to know the road-width of cut-away. When using these tables the performance of field surveying and office work for road plan will be highly increased.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.1
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• pp.23-28
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• 2021

Data analysis research using deep learning has recently been studied in various field. In this paper, we conduct a GNSS (Global Navigation Satellite System)-based meteorological study applying deep learning by estimating the ZWD (Zenith tropospheric Wet Delay) through MLP (Multi-Layer Perceptron) and LSTM (Long Short-Term Memory) models. Deep learning models were trained with meteorological data and ZWD which is estimated using zenith tropospheric total delay and dry delay. We apply meteorological data not used for learning to the learned model to estimate ZWD with centimeter-level RMSE (Root Mean Square Error) in both models. It is necessary to analyze the GNSS data from coastal areas together and increase time resolution in order to estimate ZWD in various situations.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.707-716
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• 2020

Spectroradiometers have recently been drawing great attention in earth observing communities for its capability for obtaining target's quantitative properties. In particular, light-weighted multispectral cameras are gaining popularity in many field domains, as being utilized on UAV's. Despite the importance of the radiometric accuracy, studies are scarce on the performance of the inexpensive multispectral camera sensors that have various applications in agricultural, vegetation, and water quality analysis. This study conducted assessment of radiometric accuracy for MicaSense RedEdge-MX multispectral camera, by comparing the radiometric data with an independent hyperspectral sensor having NIST-traceable calibration quality. The comaprison showed that radiance from RedEdge-MX is lower than that of TriOS RAMSES by 5 to 16% depending on the bands, and the irradiance from RedEdge-MX is also lower than RAMSES by 1~20%. The correction coefficients for RedEdge-MX alculated through the 1-st and the 3-rd order regression analysis were presented as a result of the study.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.2
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• pp.109-118
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• 2022

GPR (Ground Penetrating Radar), developed as a technology for geotechnical investigations such as sinkhole exploration, was used limitedly as a method to resolve undetectable lines in underground facility exploration. To improve the accuracy of underground facility data, the government made it possible to explore underground facilities using a non-metallic pipeline probe from July 2022. However, GPR has a problem in that the exploration rate is lowered in the soil with high moisture content, such as soft soil, such as clay layer, and there is a lot of variation in long-term accuracy. In this study, as a way to improve the accuracy of exploration considering the characteristics of GPR and the environment of underground facilities, we propose a GPR exploration method for underground facilities using permittivity constant correction and pattern analysis of GPR image data. Through this study, the accuracy of underground facility exploration and high reproducibility were derived as a result of field verification applying GPR frequency band and heterogeneous GPR.