• 제목/요약/키워드: Terrain information

Search Result 762, Processing Time 0.026 seconds

A Study on the Surface Wind Characteristics in Suwon City Using a GIS Data and a CFD Model (GIS 자료와 CFD 모델을 이용한 수원시 지표 바람 특성 연구)

  • Kang, Geon;Kim, Min-Ji;Kang, Jung-Eun;Yang, Minjune;Choi, Seok-Hwan;Kang, Eunha;Kim, Jae-Jin
    • Korean Journal of Remote Sensing
    • /
    • v.37 no.6_2
    • /
    • pp.1837-1847
    • /
    • 2021
  • This study investigated wind corridors for the entire Suwon-city area using a geographic information system and a computational fluid dynamics model. We conducted numerical simulations for 16 inflow wind directions using the average wind speeds measured at the Suwon automated synoptic observation system (ASOS) for recent ten years. We analyzed the westerly (dominant wind direction) and easterly cases (not dominant but strong wind speed) in detail and investigated the characteristics of a wind speed distribution averaged using the frequencies of 16 wind directions as weighting factors. The characteristics of the wind corridors in Suwon city can be summarized as; (1) In the northern part of Suwon, complicated flows were formed by the high mountainous terrain, and strong (weak) winds and updrafts (downdrafts) were simulated on the windward (leeward) mountain slope. (2) On the leeward mountain slope, a wind corridor was formed along a valley, and relatively strong airflow flowed into the residential area. (3) The strong winds were simulated in a wide and flat area in the west and south part of Suwon city. (4) Due to the friction and flow blocking by buildings, wind speeds decreased, and airflows became complicated in the downtown area. (5) Wind corridors in residential areas were formed along wide roads and areas with few obstacles, such as rivers, lakes, and reservoirs.

Performance Analysis of Adaptive SC/MRC Diversity Combining using in AWGN (AWGN환경에서 적응형 SC/MRC 다이버시티 컴바이너 성능분석)

  • Yun, Deok-Won;Huh, Sung-Uk;Kim, Chun-Won;Choi, Yong-Tae;Lee, Won-Cheol
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
    • /
    • v.11 no.6
    • /
    • pp.757-763
    • /
    • 2018
  • It is very difficult to achieve sufficient data rate and required quality of service due to the time-varying nature of the radio channel and various jammers such as path loss, delay, Doppler, shadowing and interference. Especially, the propagation path between the transmitting antenna and the tracking antenna mounted on the fuselage during the test and evaluation of the projectile system considered in this paper is based on the rapid movement of the projectile, the interference due to multipath fading due to the terrain, The propagation path may be blocked. In order to effectively improve the multipath fading occurring in the wireless communication system, a diversity combiner technique is required. In this paper, to derive the design and improvement schemes for the space diversity combiner technique among the diversity combiner schemes, the BER performance of maximum ratio combining (MRC) and selection combining (SC) In an adaptive SC / MRC diversity combiner that operates with MRC when it is lower than the specified threshold criterion when comparing the SNR between two signals received from the channel and operates with SC at high and combines the two received signals The BER performance of the system was compared and analyzed.

A Study on the Development Site of an Open-pit Mine Using Unmanned Aerial Vehicle (무인항공기를 이용한 노천광산 개발지 조사에 관한 연구)

  • Kim, Sung-Bo;Kim, Doo-Pyo;Back, Ki-Suk
    • Journal of Convergence for Information Technology
    • /
    • v.11 no.1
    • /
    • pp.136-142
    • /
    • 2021
  • Open-pit mine development requires continuous management because of topographical changes and there is a risk of accidents if the current status survey is performed directly in the process of calculating the earthwork. In this study, the application of UAV photogrammetry, which can acquire spatial information without direct human access, was applied to open-pit mines development area and analyzed the accuracy, earthwork, and mountain restoration plan to determine its applicability. As a result of accuracy analysis at checkpoint using ortho image and Digital Surface Model(DSM) by UAV photogrammetry, Root Mean Square Error(RMSE) is 0.120 m in horizontal and 0.150 m in vertical coordinates. This satisfied the tolerance range of 1:1,000 digital map. As a result of the comparison of the earthwork, UAV photogrammetry yielded 11.7% more earthwork than the conventional survey method. It is because UAV photogrammetry shows more detailed topography. And result of monitoring mountain restoration showed possible to determine existence of rockfall prevention nets and vegetation. If the terrain changes are monitored by acquiring images periodically, the utility of UAV photogrammetry will be further useful to open-pit mine development.

Predicting Road Surface Temperature using Solar Radiation Data from SOLWEIG(SOlar and LongWave Environmental Irradiance Geometry-model): Focused on Naebu Expressway in Seoul (태양복사모델(SOLWEIG)의 복사플럭스 자료를 활용한 노면온도 예측: 서울시 내부순환로 대상)

  • AHN, Suk-Hee;KWON, Hyuk-Gi;YANG, Ho-Jin;LEE, Geun-Hee;YI, Chae-Yeon
    • Journal of the Korean Association of Geographic Information Studies
    • /
    • v.23 no.4
    • /
    • pp.156-172
    • /
    • 2020
  • The purpose of this study was to predict road surface temperature using high-resolution solar radiation data. The road surface temperature prediction model (RSTPM) was applied to predict road surface temperature; this model was developed based on the heat-balance method. In addition, using SOLWEIG (SOlar and LongWave Environmental Irradiance Geometry-model), the shadow patterns caused by the terrain effects were analyzed, and high-resolution solar radiation data with 10 m spatial resolution were calculated. To increase the accuracy of the shadow patterns and solar radiation, the day that was modeled had minimal effects from fog, clouds, and precipitation. As a result, shadow areas lasted for a long time at the entrance and exit of a tunnel, and in a high-altitude area. Furthermore, solar radiation clearly decreased in areas affected by shadows, which was reflected in the predicted road surface temperatures. It was confirmed that the road surface temperature should be high at topographically open points and relatively low at higher altitude points. The results of this study could be used to forecast the freezing of sections of road surfaces in winter, and to inform decision making by road managers and drivers.

DB-Based Feature Matching and RANSAC-Based Multiplane Method for Obstacle Detection System in AR

  • Kim, Jong-Hyun
    • Journal of the Korea Society of Computer and Information
    • /
    • v.27 no.7
    • /
    • pp.49-55
    • /
    • 2022
  • In this paper, we propose an obstacle detection method that can operate robustly even in external environmental factors such as weather. In particular, we propose an obstacle detection system that can accurately inform dangerous situations in AR through DB-based feature matching and RANSAC-based multiplane method. Since the approach to detecting obstacles based on images obtained by RGB cameras relies on images, the feature detection according to lighting is inaccurate, and it becomes difficult to detect obstacles because they are affected by lighting, natural light, or weather. In addition, it causes a large error in detecting obstacles on a number of planes generated due to complex terrain. To alleviate this problem, this paper efficiently and accurately detects obstacles regardless of lighting through DB-based feature matching. In addition, a criterion for classifying feature points is newly calculated by normalizing multiple planes to a single plane through RANSAC. As a result, the proposed method can efficiently detect obstacles regardless of lighting, natural light, and weather, and it is expected that it can be used to secure user safety because it can reliably detect surfaces in high and low or other terrains. In the proposed method, most of the experimental results on mobile devices reliably recognized indoor/outdoor obstacles.

Improved Estimation of Hourly Surface Ozone Concentrations using Stacking Ensemble-based Spatial Interpolation (스태킹 앙상블 모델을 이용한 시간별 지상 오존 공간내삽 정확도 향상)

  • KIM, Ye-Jin;KANG, Eun-Jin;CHO, Dong-Jin;LEE, Si-Woo;IM, Jung-Ho
    • Journal of the Korean Association of Geographic Information Studies
    • /
    • v.25 no.3
    • /
    • pp.74-99
    • /
    • 2022
  • Surface ozone is produced by photochemical reactions of nitrogen oxides(NOx) and volatile organic compounds(VOCs) emitted from vehicles and industrial sites, adversely affecting vegetation and the human body. In South Korea, ozone is monitored in real-time at stations(i.e., point measurements), but it is difficult to monitor and analyze its continuous spatial distribution. In this study, surface ozone concentrations were interpolated to have a spatial resolution of 1.5km every hour using the stacking ensemble technique, followed by a 5-fold cross-validation. Base models for the stacking ensemble were cokriging, multi-linear regression(MLR), random forest(RF), and support vector regression(SVR), while MLR was used as the meta model, having all base model results as additional input variables. The results showed that the stacking ensemble model yielded the better performance than the individual base models, resulting in an averaged R of 0.76 and RMSE of 0.0065ppm during the study period of 2020. The surface ozone concentration distribution generated by the stacking ensemble model had a wider range with a spatial pattern similar with terrain and urbanization variables, compared to those by the base models. Not only should the proposed model be capable of producing the hourly spatial distribution of ozone, but it should also be highly applicable for calculating the daily maximum 8-hour ozone concentrations.

Short-Term Precipitation Forecasting based on Deep Neural Network with Synthetic Weather Radar Data (기상레이더 강수 합성데이터를 활용한 심층신경망 기반 초단기 강수예측 기술 연구)

  • An, Sojung;Choi, Youn;Son, MyoungJae;Kim, Kwang-Ho;Jung, Sung-Hwa;Park, Young-Youn
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
    • /
    • 2021.05a
    • /
    • pp.43-45
    • /
    • 2021
  • The short-term quantitative precipitation prediction (QPF) system is important socially and economically to prevent damage from severe weather. Recently, many studies for short-term QPF model applying the Deep Neural Network (DNN) has been conducted. These studies require the sophisticated pre-processing because the mistreatment of various and vast meteorological data sets leads to lower performance of QPF. Especially, for more accurate prediction of the non-linear trends in precipitation, the dataset needs to be carefully handled based on the physical and dynamical understands the data. Thereby, this paper proposes the following approaches: i) refining and combining major factors (weather radar, terrain, air temperature, and so on) related to precipitation development in order to construct training data for pattern analysis of precipitation; ii) producing predicted precipitation fields based on Convolutional with ConvLSTM. The proposed algorithm was evaluated by rainfall events in 2020. It is outperformed in the magnitude and strength of precipitation, and clearly predicted non-linear pattern of precipitation. The algorithm can be useful as a forecasting tool for preventing severe weather.

  • PDF

Utilization of Drone LiDAR for Field Investigation of Facility Collapse Accident (붕괴사고 현장조사를 위한 드론 LiDAR 활용)

  • Yonghan Jung ;Eontaek Lim ;Jaewook Suk;Seul Koo;Seongsam Kim
    • Korean Journal of Remote Sensing
    • /
    • v.39 no.5_2
    • /
    • pp.849-858
    • /
    • 2023
  • Investigating disaster sites such as earthquakes and landslides involves significant risks due to potential secondary disasters like facility collapse. In situations where direct access is challenging, there is a need to develop methods for safely acquiring high-precision 3D disaster information using light detection and ranging (LiDAR) equipped drone survey systems. In this study, the feasibility of using drone LiDAR in disaster scenarios was examined, focusing on the collapse accident at Jeongja Bridge in Bundang-gu, Seongnam City, in April 2023. High-density point clouds for the accident bridge were collected, and the bridge's 3D terrain information was reconstructed and compared to the measurement performance of 10 ground control points. The results showed horizontal and vertical root mean square error values of 0.032 m and 0.055 m, respectively. Additionally, when compared to a point cloud generated using ground LiDAR for the same target area, a vertical difference of approximately 0.08 m was observed, but overall shapes showed minimal discrepancies. Moreover, in terms of overall data acquisition and processing time, drone LiDAR was found to be more efficient than ground LiDAR. Therefore, the use of drone LiDAR in disaster sites with significant risks allows for safe and rapid onsite investigations.

A Study on Health Impact Assessment and Emissions Reduction System Using AERMOD (AERMOD를 활용한 건강위해성평가 및 배출저감제도에 관한 연구)

  • Seong-Su Park;Duk-Han Kim;Hong-Kwan Kim;Young-Woo Chon
    • Journal of the Society of Disaster Information
    • /
    • v.20 no.1
    • /
    • pp.93-105
    • /
    • 2024
  • Purpose: This study aims to quantitatively determine the impact on nearby risidents by selecting the amount of chemicals emitted from the workplace among the substances subject to the chemical emission plan and predicting the concentration with the atmospheric diffusion program. Method: The selection of research materials considered half-life, toxicity, and the presence or absence of available monitoring station data. The areas discharged from the materials to be studied were selected as the areas to be studied, and four areas with floating populations were selected to evaluate health risks. Result: AERMOD was executed after conducting terrain and meteorological processing to obtain predicted concentrations. The health hazard assessment results indicated that only dichloromethane exceeded the threshold for children, while tetrachloroethylene and chloroform appeared at levels that cannot be ignored for both children and adults. Conclusion: Currently, in the domestic context, health hazard assessments are conducted based on the regulations outlined in the "Environmental Health Act" where if the hazard index exceeds a certain threshold, it is considered to pose a health risk. The anticipated expansion of the list of substances subject to the chemical discharge plan to 415 types by 2030 suggests the need for efficient management within workplaces. In instances where the hazard index surpasses the threshold in health hazard assessments, it is judged that effective chemical management can be achieved by prioritizing based on considerations of background concentration and predicted concentration through atmospheric dispersion modeling.

Development and Application of a Scenario Analysis System for CBRN Hazard Prediction (화생방 오염확산 시나리오 분석 시스템 구축 및 활용)

  • Byungheon Lee;Jiyun Seo;Hyunwoo Nam
    • Journal of the Korea Society for Simulation
    • /
    • v.33 no.3
    • /
    • pp.13-26
    • /
    • 2024
  • The CBRN(Chemical, Biological, Radiological, and Nuclear) hazard prediction model is a system that supports commanders in making better decisions by creating contamination distribution and damage prediction areas based on the weapons used, terrain, and weather information in the events of biochemical and radiological accidents. NBC_RAMS(Nuclear, Biological and Chemical Reporting And Modeling S/W System) developed by ADD (Agency for Defense Development) is used not only supporting for decision making plan for various military operations and exercises but also for post analyzing CBRN related events. With the NBC_RAMS's core engine, we introduced a CBR hazard assessment scenario analysis system that can generate contaminant distribution prediction results reflecting various CBR scenarios, and described how to apply it in specific purposes in terms of input information, meteorological data, land data with land coverage and DEM, and building data with pologon form. As a practical use case, a technology development case is addressed that tracks the origin location of contaminant source with artificial intelligence and a technology that selects the optimal location of a CBR detection sensor with score data by analyzing large amounts of data generated using the CBRN scenario analysis system. Through this system, it is possible to generate AI-specialized CBRN related to training and analysis data and support planning of operation and exercise by predicting battle field.