• Title/Summary/Keyword: mapping model

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Assessment of Flood Vulnerability to Climate Change Using Fuzzy Model and GIS in Seoul (퍼지모형과 GIS를 활용한 기후변화 홍수취약성 평가 - 서울시 사례를 중심으로 -)

  • Kang, Jung-Eun;Lee, Moung-Jin
    • Journal of the Korean Association of Geographic Information Studies
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    • v.15 no.3
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    • pp.119-136
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    • 2012
  • The goal of this study is to apply the IPCC(Intergovernmental Panel on Climate Change) concept of vulnerability to climate change and verify the use of a combination of vulnerability index and fuzzy logic to flood vulnerability analysis and mapping in Seoul using GIS. In order to achieve this goal, this study identified indicators influencing floods based on literature review. We include indicators of exposure to climate(daily max rainfall, days of 80mm over), sensitivity(slope, geological, average DEM, impermeability layer, topography and drainage), and adaptive capacity(retarding basin and green-infra). Also, this research used fuzzy model for aggregating indicators, and utilized frequency ratio to decide fuzzy membership values. Results show that the number of days of precipitation above 80mm, the distance from river and impervious surface have comparatively strong influence on flood damage. Furthermore, when precipitation is over 269mm, areas with scare flood mitigation capacities, industrial land use, elevation of 16~20m, within 50m distance from rivers are quite vulnerable to floods. Yeongdeungpo-gu, Yongsan-gu, Mapo-gu include comparatively large vulnerable areas. This study improved previous flood vulnerability assessment methodology by adopting fuzzy model. Also, vulnerability map provides meaningful information for decision makers regarding priority areas for implementing flood mitigation policies.

The Development of Major Tree Species Classification Model using Different Satellite Images and Machine Learning in Gwangneung Area (이종센서 위성영상과 머신 러닝을 활용한 광릉지역 주요 수종 분류 모델 개발)

  • Lim, Joongbin;Kim, Kyoung-Min;Kim, Myung-Kil
    • 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.

Random heterogeneous model with bimodal velocity distribution for Methane Hydrate exploration (바이모달 분포형태 랜덤 불균질 매질에 의한 메탄하이드레이트층 모델화)

  • Kamei Rie;Hato Masami;Matsuoka Toshifumi
    • Geophysics and Geophysical Exploration
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    • v.8 no.1
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    • pp.41-49
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    • 2005
  • We have developed a random heterogeneous velocity model with bimodal distribution in methane hydrate-bearing Bones. The P-wave well-log data have a von Karman type autocorrelation function and non-Gaussian distribution. The velocity histogram has two peaks separated by several hundred metres per second. A random heterogeneous medium with bimodal distribution is generated by mapping of a medium with a Gaussian probability distribution, yielded by the normal spectral-based generation method. By using an ellipsoidal autocorrelation function, the random medium also incorporates anisotropy of autocorrelation lengths. A simulated P-wave velocity log reproduces well the features of the field data. This model is applied to two simulations of elastic wane propagation. Synthetic reflection sections with source signals in two different frequency bands imply that the velocity fluctuation of the random model with bimodal distribution causes the frequency dependence of the Bottom Simulating Reflector (BSR) by affecting wave field scattering. A synthetic cross-well section suggests that the strong attenuation observed in field data might be caused by the extrinsic attenuation in scattering. We conclude that random heterogeneity with bimodal distribution is a key issue in modelling hydrate-bearing Bones, and that it can explain the frequency dependence and scattering observed in seismic sections in such areas.

Spatial Variation in Land Use and Topographic Effects on Water Quality at the Geum River Watershed (토지이용과 지형이 수질에 미치는 영향의 공간적 변동성에 관한 연구 - 금강 권역을 중심으로)

  • Park, Se-Rin;Choi, Kwan-Mo;Lee, Sang-Woo
    • Korean Journal of Ecology and Environment
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    • v.52 no.2
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    • pp.94-104
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    • 2019
  • In this study, we investigated the spatial variation in land use and topographic effects on water quality at the Geum river watershed in South Korea, using the ordinary least squares(OLS) and geographically weighted regression (GWR) models. Understanding the complex interactions between land use, slope, elevation, and water quality is essential for water pollution control and watershed management. We monitored four water quality indicators -total phosphorus, total nitrogen, biochemical oxygen demand, and dissolved oxygen levels - across three land use types (urban, agricultural, and forested) and two topographic features (elevation and mean slope). Results from GWR modeling revealed that land use and topography did not affect water quality consistently through space, but instead exhibited substantial spatial non-stationarity. The GWR model performed better than the OLS model as it produced a higher adjusted $R^2$ value. Spatial variation in interactions among variables could be visualized by mapping $R^2$ values from the GWR model at fine spatial resolution. Using the GWR model, we were able to identify local pollution sources, determine habitat status, and recommend appropriate land-use planning policies for watershed management.

Study on the Selection and Application of a Spatial Analysis Model Appropriate for Selecting the Radon Priority Management Target Area (라돈 우선관리 대상 지역 선정에 적합한 공간분석모형의 선정 및 활용에 관한 연구)

  • Nam Goung, Sun Ju;Choi, Kil Yong;Hong, Hyung Jin;Yoon, Dan Ki;Kim, Yoon Shin;Park, Si Hyun;Kim, Yoon Kwan;Lee, Cheol Min
    • Journal of Environmental Health Sciences
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    • v.45 no.1
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    • pp.82-96
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    • 2019
  • Objective: The aims of this study were to provide the basic data for establishing a precautionary management policy and to develop a methodology for selecting a radon management priority target area suitable for the Korean domestic environment. Methods: A suitable mapping method for the domestic environment was derived by conducting a quantitative comparison of predicted values and measured values that were calculated through implementation of two models such as IDW and RBF methods. And a qualitative comparison including the clarity of information transmission of the written radon map was carried out. Results: The predicted and measured values were obtained through the implementation of the spatial analysis models. The IDW method showed the lowest in the calculated mean square error and had a higher correlation coefficient than the other methods. As results of comparing the uncertainty using the jackknife concept and the concept of error distance for comparison of the differences according to the model interpolation method, the sum of the error distances showed a modest increase compared with the RBF method. As a result of qualitatively comparing the information transfer clarity between the radon maps prepared with the predicted values through the model implementation, it was found that the maps plotted using the predicted values by the implementation of the IDW method had greater clarity in terms of highness and lowness of radon concentration per area compared with the maps plotted by other methods. Conclusions: The radon management priority area suggests selecting a metropolitan city including an area with a high radon concentration.

Development of 3D Addressing Data Model Based on the IndoorGML (IndoorGML 기반 입체주소 데이터 모델 개발)

  • Kim, JI Young
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.38 no.6
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    • pp.591-598
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    • 2020
  • The all revision of the Road Name Address Act, which contains the contents to be used by expanding the road name address as a means of indicationg the location, has been resloved by the National Assembly. Addresses will be assigned to large-sized facilities (3D mixed-use complex spaces). Here, the 3D (Three-dimensional) address is assigned an indoor path section in the inner passage, dividing the section at intervals. The 3D address will be built on the address information map. For 3D address, data should be built and managed for a 3D complex space(indoor space). Therefore, in this study, the object of the 3D address is defined based on the address conceptual model defined in the international standard, and the 3D address data model is proposed based on IndoorGML. To this, it is proposed as a method of mapping the Core and Navigation module of IndoorGML so that the entity of the 3D address can be expressed in IndoorGML. This study has a limitation in designing a 3D address data model only, but it is meaningful that it suggested a standard for constructing 3D address data in the future.

Implementation of a citizen-driven smart city living lab community platform to improve pedestrian environment of school zone (스쿨존 보행환경 개선을 위한 시민참여형 스마트시티 리빙랩 커뮤니티 플랫폼 구현)

  • Jang, Sun-Young;Kim, Dusik
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.1
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    • pp.415-423
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    • 2021
  • Citizen participation and Living Lab are attracting interest as one of the major strategies for the success of smart cities. In a Living Lab, citizens, who are the end-users of technology, participate in the search for alternatives to define and solve problems and repeat experiments to verify alternatives in a circular process. The purpose of this research was to present an operating model of a citizen-participating online community platform to improve urban problems, implement and test it, and show its applicability. To this end, an operation model of a citizen-participating online community platform was proposed to improve urban problems. An online platform was designed and implemented to reflect the functions pursued by the operation model. Finally, a pilot test for the function was performed using the Oma Elementary School case located in Ilsan, Goyang-si, Gyeonggi-do. The operating model was designed with the city's pedestrian environment and children. As a result, the sharing and communicating process of urban issues among community members worked appropriately according to the designed intention. The Living Lab coordinator could visualize and view urban issues posted by users on a map based on location information. Visualizing the urban problem as a heat map confirmed that urban problems were concentrated in a specific area.

Risk Analysis for the Rotorcraft Landing System Using Comparative Models Based on Fuzzy (퍼지 기반 다양한 모델을 이용한 회전익 항공기 착륙장치의 위험 우선순위 평가)

  • Na, Seong Hyeon;Lee, Gwang Eun;Koo, Jeong Mo
    • Journal of the Korean Society of Safety
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    • v.36 no.2
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    • pp.49-57
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    • 2021
  • In the case of military supplies, any potential failure and causes of failures must be considered. This study is aimed at examining the failure modes of a rotorcraft landing system to identify the priority items. Failure mode and effects analysis (FMEA) is applied to the rotorcraft landing system. In general, the FMEA is used to evaluate the reliability in engineering fields. Three elements, specifically, the severity, occurrence, and detectability are used to evaluate the failure modes. The risk priority number (RPN) can be obtained by multiplying the scores or the risk levels pertaining to severity, occurrence, and detectability. In this study, different weights of the three elements are considered for the RPN assessment to implement the FMEA. Furthermore, the FMEA is implemented using a fuzzy rule base, similarity aggregation model (SAM), and grey theory model (GTM) to perform a comparative analysis. The same input data are used for all models to enable a fair comparison. The FMEA is applied to military supplies by considering methodological issues. In general, the fuzzy theory is based on a hypothesis regarding the likelihood of the conversion of the crisp value to the fuzzy input. Fuzzy FMEA is the basic method to obtain the fuzzy RPN. The three elements of the FMEA are used as five linguistic terms. The membership functions as triangular fuzzy sets are the simplest models defined by the three elements. In addition, a fuzzy set is described using a membership function mapping the elements to the intervals 0 and 1. The fuzzy rule base is designed to identify the failure modes according to the expert knowledge. The IF-THEN criterion of the fuzzy rule base is formulated to convert a fuzzy input into a fuzzy output. The total number of rules is 125 in the fuzzy rule base. The SAM expresses the judgment corresponding to the individual experiences of the experts performing FMEA as weights. Implementing the SAM is of significance when operating fuzzy sets regarding the expert opinion and can confirm the concurrence of expert opinion. The GTM can perform defuzzification to obtain a crisp value from a fuzzy membership function and determine the priorities by considering the degree of relation and the form of a matrix and weights for the severity, occurrence, and detectability. The proposed models prioritize the failure modes of the rotorcraft landing system. The conventional FMEA and fuzzy rule base can set the same priorities. SAM and GTM can set different priorities with objectivity through weight setting.

Seismic Vulnerability Assessment and Mapping for 9.12 Gyeongju Earthquake Based on Machine Learning (기계학습을 이용한 지진 취약성 평가 및 매핑: 9.12 경주지진을 대상으로)

  • Han, Jihye;Kim, Jinsoo
    • Korean Journal of Remote Sensing
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    • v.36 no.6_1
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    • pp.1367-1377
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    • 2020
  • The purpose of this study is to assess the seismic vulnerability of buildings in Gyeongju city starting with the earthquake that occurred in the city on September 12, 2016, and produce a seismic vulnerability map. 11 influence factors related to geotechnical, physical, and structural indicators were selected to assess the seismic vulnerability, and these were applied as independent variables. For a dependent variable, location data of the buildings that were actually damaged in the 9.12 Gyeongju Earthquake was used. The assessment model was constructed based on random forest (RF) as a mechanic study method and support vector machine (SVM), and the training and test dataset were randomly selected with a ratio of 70:30. For accuracy verification, the receiver operating characteristic (ROC) curve was used to select an optimum model, and the accuracy of each model appeared to be 1.000 for RF and 0.998 for SVM, respectively. In addition, the prediction accuracy was shown as 0.947 and 0.926 for RF and SVM, respectively. The prediction values of the entire buildings in Gyeongju were derived on the basis of the RF model, and these were graded and used to produce the seismic vulnerability map. As a result of reviewing the distribution of building classes as an administrative unit, Hwangnam, Wolseong, Seondo, and Naenam turned out to be highly vulnerable regions, and Yangbuk, Gangdong, Yangnam, and Gampo turned out to be relatively safer regions.

Image Data Loss Minimized Geometric Correction for Asymmetric Distortion Fish-eye Lens (비대칭 왜곡 어안렌즈를 위한 영상 손실 최소화 왜곡 보정 기법)

  • Cho, Young-Ju;Kim, Sung-Hee;Park, Ji-Young;Son, Jin-Woo;Lee, Joong-Ryoul;Kim, Myoung-Hee
    • Journal of the Korea Society for Simulation
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    • v.19 no.1
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    • pp.23-31
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    • 2010
  • Due to the fact that fisheye lens can provide super wide angles with the minimum number of cameras, field-of-view over 180 degrees, many vehicles are attempting to mount the camera system. Not only use the camera as a viewing system, but also as a camera sensor, camera calibration should be preceded, and geometrical correction on the radial distortion is needed to provide the images for the driver's assistance. In this thesis, we introduce a geometric correction technique to minimize the loss of the image data from a vehicle fish-eye lens having a field of view over $180^{\circ}$, and a asymmetric distortion. Geometric correction is a process in which a camera model with a distortion model is established, and then a corrected view is generated after camera parameters are calculated through a calibration process. First, the FOV model to imitate a asymmetric distortion configuration is used as the distortion model. Then, we need to unify the axis ratio because a horizontal view of the vehicle fish-eye lens is asymmetrically wide for the driver, and estimate the parameters by applying a non-linear optimization algorithm. Finally, we create a corrected view by a backward mapping, and provide a function to optimize the ratio for the horizontal and vertical axes. This minimizes image data loss and improves the visual perception when the input image is undistorted through a perspective projection.