• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.5
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• pp.927-940
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• 2017

Landslide has been a major disaster in Indonesia, and recent climate change and indiscriminate urban development around the mountains have increased landslide risks. Java Island, Indonesia, where more than half of Indonesia's population lives, is experiencing a great deal of damage due to frequent landslides. However, even in such a dangerous situation, the number of inhabitants residing in the landslide-prone area increases year by year, and it is necessary to develop a technique for analyzing landslide-hazardous and vulnerable areas. In this regard, this study aims to evaluate landslide susceptibility of Java, an island of Indonesia, by using GIS-based spatial prediction models. We constructed the geospatial database such as landslide locations, topography, hydrology, soil type, and land cover over the study area and created spatial prediction models by applying Weight of Evidence (WoE), decision trees algorithm and artificial neural network. The three models showed prediction accuracy of 66.95%, 67.04%, and 69.67%, respectively. The results of the study are expected to be useful for prevention of landslide damage for the future and landslide disaster management policies in Indonesia.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.1
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• pp.29-38
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• 2012

The noise generated in the process of obtaining the medical image acts as the element obstructing the image interpretation and diagnosis. To restore the true image from the image polluted from the noise, the total variation optimization algorithm was proposed by the R.O. F (L.Rudin, S Osher, E. Fatemi). This method removes the noise by fitting the balance of the regularity and fidelity. However, the blurring phenomenon of the border area generated in the process of performing the iterative operation cannot be avoided. In this paper, we propose the adaptive total variation method by mapping the control parameter to the proposed transfer function for minimizing boundary error. The proposed transfer function is determined by the noise variance and the local property of the image. The proposed method was applied to 464 tooth images. To evaluate proposed method performance, PSNR which is a indicator of signal and noise's signal power ratio was used. The experimental results show that the proposed method has better performance than other methods.

• The KIPS Transactions:PartD
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• v.17D no.2
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• pp.129-146
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• 2010

Nowadays, XML has been favored by many companies internally and externally as a means of sharing and distributing data. there are many researches and systems for modeling and storing XML documents by an object-oriented method as for the method of saving and managing web-based multimedia document more easily. The representative tool for the object-oriented modeling of XML documents is UML (Unified Modeling Language). UML at the beginning was used as the integrated methodology for software development, but now it is used more frequently as the modeling language of various objects. Currently, UML supports various diagrams for object-oriented analysis and design like class diagram and is widely used as a tool of creating various database schema and object-oriented codes from them. This paper proposes an Efficinet Query Modelling of XML-GL using the UML class diagram and OCL for searching XML document which its application scope is widely extended due to the increased use of WWW and its flexible and open nature. In order to accomplish this, we propose the modeling rules and algorithm that map XML-GL. which has the modeling function for XML document and DTD and the graphical query function about that. In order to describe precisely about the constraint of model component, it is defined by OCL (Object Constraint Language). By using proposed technique creates a query for the XML document of holding various properties of object-oriented model by modeling the XML-GL query from XML document, XML DTD, and XML query while using the class diagram of UML. By converting, saving and managing XML document visually into the object-oriented graphic data model, user can prepare the base that can express the search and query on XML document intuitively and visually. As compared to existing XML-based query languages, it has various object-oriented characteristics and uses the UML notation that is widely used as object modeling tool. Hence, user can construct graphical and intuitive queries on XML-based web document without learning a new query language. By using the same modeling tool, UML class diagram on XML document content, query syntax and semantics, it allows consistently performing all the processes such as searching and saving XML document from/to object-oriented database.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.4
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• pp.10-16
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• 2012

For high speed visual inspection in semiconductor industries, it is essential to acquire two-dimensional images on regions of interests with a large field of view (FOV) and a high resolution simultaneously. In this paper, an imaging system is newly proposed to achieve high quality image in terms of precision and FOV, which is composed of single lens, a beam splitter, two camera sensors, and stereo image grabbing board. For simultaneously acquired object images from two camera sensors, Zhang's camera calibration method is applied to calibrate each camera first of all. Secondly, to find a mathematical mapping function between two images acquired from different view cameras, the matching matrix from multiview camera geometry is calculated based on their image homography. Through the image homography, two images are finally registered to secure a large inspection FOV. Here the inspection system of using multiple images from multiple cameras need very fast processing unit for real-time image matching. For this purpose, parallel processing hardware and software are utilized, such as Compute Unified Device Architecture (CUDA). As a result, we can obtain a matched image from two separated images in real-time. Finally, the acquired homography is evaluated in term of accuracy through a series of experiments, and the obtained results shows the effectiveness of the proposed system and method.

• Korean Journal of Remote Sensing
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• v.35 no.6_2
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• pp.1037-1052
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• 2019

We had developed in preceding study a classification model for the Korean pine and Larch with an accuracy of 98 percent using Hyperion and Sentinel-2 satellite images, texture information, and geometric information as the first step for tree species mapping in the inaccessible North Korea. Considering a share of major tree species in North Korea, the classification model needs to be expanded as it has a large share of Oak(29.5%), Pine (12.7%), Fir (8.2%), and as well as Larch (17.5%) and Korean pine (5.8%). In order to classify 5 major tree species, national forest type map of South Korea was used to build 11,039 training and 2,330 validation data. Sentinel-2 data was used to derive spectral information, and PlanetScope data was used to generate texture information. Geometric information was built from SRTM DEM data. As a machine learning algorithm, Random forest was used. As a result, the overall accuracy of classification was 80% with 0.80 kappa statistics. Based on the training data and the classification model constructed through this study, we will extend the application to Mt. Baekdu and North and South Goseong areas to confirm the applicability of tree species classification on the Korean Peninsula.

• 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.311-318
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• 2014

The data of buildings and structures take over large portions of the mapping database with large numbers. Furthermore, those shapes and attributes of building data continuously change over time. Due to those factors, the efficient methodology of updating database for following the most recent data become necessarily. This study has purposed on extracting needed data, which has been changed, by using overlaying analysis of new and old dataset, during updating processes. Following to procedures, we firstly searched for matching pairs of objects from each dataset, and defined the classification algorithm for building updating cases by comparing; those of shape updating cases are divided into 8 cases, while those of attribute updating cases are divided into 4 cases. Also, two updated dataset are set to be automatically saved. For the study, we selected few guidelines; the layer of digital topographic map 1:5000 for the targeted updating data, the building layer of Korea Address Information System map for the reference data, as well as build-up areas in Gwanak-gu, Seoul for the test area. The result of study updated 82.1% in shape and 34.5% in attribute building objects among all.

• Journal of Korea Multimedia Society
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• v.9 no.5
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• pp.649-657
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• 2006

Reinforcement Learning is a computational approach to learning whereby an agent take an action which maximize the total amount of reward it receives among possible actions within current state when interacting with a uncertain environment. Q-learning, one of the most active algorithm in Reinforcement Learning, is consist of rewards which is obtained when an agent take an action. But it has the problem with mapping real world to discrete states. When state spaces are very large, Q-learning suffers from time for learning. In constant, when the state space is reduced, many state spaces map to single state space. Because an agent only learns single action within many states, an agent takes an action monotonously. In this paper, to reduce time for learning and complement simple action, we propose the Q-learning using influence map(QIM). By using influence map and adjacent state space's learning result, an agent could choose proper action within uncertain state where an agent does not learn. When this paper compares simulation results of QIM and Q-learning, we show that QIM effects as same as Q-learning even thought QIM uses 4.6% of the Q-learning's state spaces. This is because QIM learns faster than Q-learning about 2.77 times and the state spaces which is needed to learn is reduced, so the occurred problem is complemented by the influence map.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.1
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• pp.48-63
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• 2015

In this study, we introduce various hyperspectral data processing techniques for the monitoring of shallow and coastal waters to enlarge the application range and to improve the accuracy of the end results in Korea. Unlike land, more accurate atmospheric correction is needed in coastal region showing relatively low reflectance in visible wavelengths. Sun-glint which occurs due to a geometry of sun-sea surface-sensor is another issue for the data processing in the ocean application of hyperspectal imagery. After the preprocessing of the hyperspectral data, a semi-analytical algorithm based on a radiative transfer model and a spectral library can be used for bathymetry mapping in coastal area, type classification and status monitoring of benthos or substrate classification. In general, semi-analytical algorithms using spectral information obtained from hyperspectral imagey shows higher accuracy than an empirical method using multispectral data. The water depth and quality are constraint factors in the ocean application of optical data. Although a radiative transfer model suggests the theoretical limit of about 25m in depth for bathymetry and bottom classification, hyperspectral data have been used practically at depths of up to 10 m in shallow and coastal waters. It means we have to focus on the maximum depth of water and water quality conditions that affect the coastal applicability of hyperspectral data, and to define the spectral library of coastal waters to classify the types of benthos and substrates.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.634-634
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• 2015

최근 국지성 호우와 잦은 태풍으로 인한 돌발홍수가 빈번하게 발생하여 도심지에서의 호안유실과 범람으로 많은 외수침수의 피해가 발생하고 있다. 또한 기후변화에 따른 강우량의 증가와 집중호우로 인한 홍수 피해는 지속적으로 증가할 것으로 예상됨에 따라 대하천 유역을 중심으로 홍수범람예측 연구가 활발히 진행되고 있지만 대하천을 제외한 지방 중소하천의 연구가 미비한 실정이다. 이에 본 연구에서는 지방 중소하천 중 태풍과 집중호우의 영향이 많은 제주지역의 주요 하천 중의 하나인 한천 유역을 테스트베드로 선정하여 연구를 진행하였다. 한천은 강우 시에만 유출이 발생하는 건천으로, 집중호우 시 암반하상 조건, 복개, 교각 등으로 수위가 국부적으로 급격히 상승하는 경우가 있었다. 그리고 한천 하류부에는 도심이 위치하고 있어 돌발홍수 발생 시 막대한 피해가 발생한다. 이에 따라 홍수 피해를 줄이기 위한 제도화, 정책결정 등의 구조적 해결방안과 홍수 피해의 규모와 원인을 분석하는 비구조적 해결방안에 대한 연구가 시급하다. 따라서 본 연구에서는 홍수범람 등으로 인한 홍수 피해규모를 산정하여 각 정부부처 및 유관기관, 지자체에서 빠른 정책결정을 내릴 수 있는 자료를 제공하는 목적으로 제주도의 특성을 고려한 홍수범람위험도 산정 알고리즘을 개발하고자 한다. 본 연구에서는 제주 한천유역의 단면 자료와 빈도별 홍수량 자료를 이용하여 HEC-RAS 모형으로 수리학적 흐름특성 모의를 실사하였다. 모의된 결과를 바탕으로 ArcGIS 소프트웨어인 ESRI사의 ArcMap을 이용하여 빈도별 홍수위 자료와 제주지역 수치표고모형 자료를 활용한 빈도별 홍수범람지도를 산정하고, 좌안과 우안의 제방고로부터 위험도를 산정하여 홍수범람위험도를 각각 구축하였다. 구축된 결과를 이용하여 분석하고자하는 해당 빈도의 홍수위와 홍수량이 발생할 때의 피해지역을 예측하였으며, 예측된 지역과 제주시의 공시지가 자료를 중첩하여 피해지역에 대한 피해액을 산정하였다. 본 연구의 알고리즘을 적용한 2007년 태풍 '나리' 사상의 경우와 비교한 결과, '나리' 사상의 침수 흔적도와 유사한 홍수범람지도를 획득 할 수 있었으며, 모의된 유역의 하천 복개구간을 중심으로 홍수범람이 발생한다는 점과 우안보다 좌안에서의 홍수범람위험도와 피해액이 더 크게 나타난 점 등의 홍수범람 특성을 파악할 수 있었다. 본 연구에서 제시된 기법을 이용할 경우, 홍수에 의한 취약지에 대한 제방 설계 강화, 하천의 보수 정비 등 정책적 결정에 사용될 수 있을 것이며, 실시간 자료제공, 재해정보시스템 등에 적용하여 홍수범람 피해를 줄일 수 있는 기반기술이 될 것으로 사료된다.

• Journal of Soil and Groundwater Environment
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• v.13 no.3
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• pp.37-44
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• 2008

Soil ecology has important roles in global ecosystems. However, soil ecological quality information is being ignored when assessing ecological impact of construction actions. And methods for classifying and assessing soil ecological quality have been very little established in comparison to those for animal and plant ecosystems. In this study, it was examined whether soil ecological quality information has influence on determining an eco-friendly route for a road construction project. For this, sensitivity analysis was systematically performed by varying the relative significance (weights) of soil ecological quality information among natural environmental and ecological factors. When the weight of soil ecological quality was greater than just 14%, the soil ecological quality information significantly influenced the determination of the eco-friendly routes for a specific road construction project. This demonstrates that soil ecological quality information has to be considered for more reliable environmental impact assessment, and also supports the validity of use of soil ecological quality information and its mapping technique in planning and siting of eco-friendly construction projects.