• Title/Summary/Keyword: Ocean fog

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Fundamental Research on Spring Season Daytime Sea Fog Detection Using MODIS in the Yellow Sea

  • Jeon, Joo-Young;Kim, Sun-Hwa;Yang, Chan-Su
    • Korean Journal of Remote Sensing
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    • v.32 no.4
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    • pp.339-351
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    • 2016
  • For the safety of sea, it is important to monitor sea fog, one of the dangerous meteorological phenomena which cause marine accidents. To detect and monitor sea fog, Moderate Resolution Imaging Spectroradiometer (MODIS) data which is capable to provide spatial distribution of sea fog has been used. The previous automatic sea fog detection algorithms were focused on detecting sea fog using Terra/MODIS only. The improved algorithm is based on the sea fog detection algorithm by Wu and Li (2014) and it is applicable to both Terra and Aqua MODIS data. We have focused on detecting spring season sea fog events in the Yellow Sea. The algorithm includes application of cloud mask product, the Normalized Difference Snow Index (NDSI), the STandard Deviation test using infrared channel ($STD_{IR}$) with various window size, Temperature Difference Index(TDI) in the algorithm (BTCT - SST) and Normalized Water Vapor Index (NWVI). Through the calculation of the Hanssen-Kuiper Skill Score (KSS) using sea fog manual detection result, we derived more suitable threshold for each index. The adjusted threshold is expected to bring higher accuracy of sea fog detection for spring season daytime sea fog detection using MODIS in the Yellow Sea.

Ocean Fog Detection Alarm System for Safe Ship Navigation (선박 안전항해를 위한 해무감지 경보 시스템)

  • Lee, Chang-young
    • Journal of Advanced Navigation Technology
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    • v.24 no.6
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    • pp.485-490
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    • 2020
  • Recently, amid active research on domestic shipbuilding industry and IT convergence technology, with the development of satellite detection technology for ship safety operation, ships monitored the movement of ships with the mandatory long-range identification & tracking of vessels and automatic identification system. It is possible to help safe navigation, but it is necessary to develop safety device that alert the marine officer who rely on radar to correct conditions in case of weightlessness. Therefore, an ocean fog alarm system was developed to detect and inform using photo sensors. The fabricated ocean fog detect and alarm system consists of a small, low-power optical sensor transceiver and data sensing processing module. Through experiment, it is confirmed that the fabricated ocean fog detect and alarm system measure the corresponding concentration of ocean fog for fogless circumstance and fogbound circumstance, respectively. Furthermore, the fabricated system can control RPM of ship engine according to the concentration of ocean fog, and consequently, the fabricated system can be applied to assistant device for ship safety operation.

The Weatherproof Detection System of Sea Fog by Remote Sensing and its Applications

  • Bao, Xianwen;Wang, Xin;Sun, Litan;Zhou, Faxiu
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.1380-1382
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    • 2003
  • Detection of sea fog by remote sensing with spectroscopic analysis method and structural analysis method is introduced in this paper. On this base, designing principles and frame of weatherproof detection system of sea fog by remote sensing are systemically explained. Using GMS5 and NOAA visible and infrared channel data, progresses of sea fog on yellow sea on April 17,18, 2001 is monitored which accord with the observing.

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The GOCI-II Early Mission Marine Fog Detection Products: Optical Characteristics and Verification (천리안 해양위성 2호(GOCI-II) 임무 초기 해무 탐지 산출: 해무의 광학적 특성 및 초기 검증)

  • Kim, Minsang;Park, Myung-Sook
    • Korean Journal of Remote Sensing
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    • v.37 no.5_2
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    • pp.1317-1328
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    • 2021
  • This study analyzes the early satellite mission marine fog detection results from Geostationary Ocean Color Imager-II (GOCI-II). We investigate optical characteristics of the GOCI-II spectral bands for marine fog between October 2020 and March 2021 during the overlapping mission period of Geostationary Ocean Color Imager (GOCI) and GOCI-II. For Rayleigh-corrected reflection (Rrc) at 412 nm band available for the input of the GOCI-II marine fog algorithm, the inter-comparison between GOCI and GOCI-II data showed a small Root Mean Square Error (RMSE) value (0.01) with a high correlation coefficient (0.988). Another input variable, Normalized Localization Standard (NLSD), also shows a reasonable correlation (0.798) between the GOCI and GOCI-II data with a small RMSE value (0.007). We also found distinctive optical characteristics between marine fog and clouds by the GOCI-II observations, showing the narrower distribution of all bands' Rrc values centered at high values for cloud compared to marine fog. The GOCI-II marine fog detection distribution for actual cases is similar to the GOCI but more detailed due to the improved spatial resolution from 500 m to 250 m. The validation with the automated synoptic observing system (ASOS) visibility data confirms the initial reliability of the GOCI-II marine fog detection. Also, it is expected to improve the performance of the GOCI-II marine fog detection algorithm by adding sufficient samples to verify stable performance, improving the post-processing process by replacing real-time available cloud input data and reducing false alarm by adding aerosol information.

Sea Fog Detection Algorithm Using Visible and Near Infrared Bands (가시 밴드와 근적외 밴드를 이용한 해무 탐지 알고리즘)

  • Lee, Kyung-Hun;Kwon, Byung-Hyuk;Yoon, Hong-Joo
    • The Journal of the Korea institute of electronic communication sciences
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    • v.13 no.3
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    • pp.669-676
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    • 2018
  • The Geostationary Ocean Color Imager(: GOCI) detects the sea fog at a high horizontal resolution of $500m{\times}500m$ using the Rayleigh corrected reflectance of 8 bands. The visible and the near infrared waves strongly reflect the characteristics of the earth surface, causing errors in cloud and fog detection. A threshold of the Band7 reflectance was set to detect the sea fog entering the land. When the region on which Band4 reflectance is larger than Band8 is determinated as cloud, the error over-estimated as sea fog is corrected by comparing the average reflectance with the surrounding region. The improved algorithm has been verified by comparing the fog images of the Cheollian satellite (COMS: Communication, Ocean, and Meteorological Satellite) as well as the visibility data from the Korea Meteorological Administration.

A Study on the Fog Occurrence in Suyoung Bay (수영만의 안개 발생에 관한 연구)

  • Jo, Gyu-Dae;Kim, Sun-Yeong
    • Journal of the Korean Society of Fisheries and Ocean Technology
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    • v.26 no.3
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    • pp.254-264
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    • 1990
  • Using the meteorological data, surface weather map, and oceanographic data for 5 years(1984-1988). I investigated the characteristics of the fog occurrence and the role of the inshore in Pusan about the fog occurrence. And the meteorological data and sea surface temperature(SST), which were observed in July, 1989 in Suyoung Bay, were compared with those in Pusan. The fogs in Pusan concentrate in May, June and July. And at fog occurrence time the principal wind directions are Southwest(SW) winds, which easily supply with water vapor, and a series of Northeast(NE) wind. At the fog days pressure patterns are pattern 7 in spring time (March, April, and May) and pattern 10 and pattern 13 in summer time (June, July, and August). Also the advection fog(sea fog) is closely related with the relationship between warm and cold advection in 850~700mb and cold and warm SST rather than the increase of the instability of atmosphere in 850~500mb. The fogs in Taegu, which is the inland region, mainly occur at dawn in fall time due to the strong night radiation fog. On the other hand in Pusan the coastal region, the fogs occur from late spring time to summer time (May, June, and July). Because there is the abundant supply of the water vapor from the ocean owing to a series of South(S) wind at this time. Then the atmosphere, which has high relative humidity, reaches easily the supersaturation by the radiation cooling. In Suyoung Bay and Pusan the meteorological observation data, SST and fog days are almost similar. And I think that the mechanism of the fog occurrence nearly accords with both regions.

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Automatic Ship Control System to According for Fog Conditions (안개 상태에 따른 선박 자동제어 장치)

  • Lee, Kyeong-Min;Kim, Shin-Hoo;Kim, Kab-Ki;Park, Sung-Hyeon
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.23 no.6
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    • pp.754-758
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    • 2017
  • In this paper, we designed and manufactured an automatic control system to minimize or avoid damage by automatically controlling ship engines in case of fog to allow for safer operation. This automatic power control system uses ATmega128 and an RPM detection circuit to measure RPM changes by artificially generating fog in the fog generator. For this purpose, we have created a complete schematic and applied our source code to an ATmega128 for PWM control using a Hall sensor motor. In future, an experiment and safety evaluation using this automatic power control system with an actual ship will be prepared.

Fog Type Classification and Occurrence Characteristics Based on Fog Generation Mechanism in the Korean Peninsula (안개 생성 메커니즘 기반 안개 유형 분류 및 한반도 지역내 발생 특성 분석)

  • Eun ji Kim;Soon-Young Park;Jung-Woo Yoo;Soon-Hwan Lee
    • Journal of Environmental Science International
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    • v.32 no.12
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    • pp.883-898
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    • 2023
  • To investigate the occurrence characteristics and types of fog on the Korean Peninsula over the past three years (2020 to 2022), data from 96 synoptic meteorological observatories and 21 ocean buoys were collected and analyzed. We included precipitation fog, which occurs after precipitation events, and cloud-base lowering fog, which is caused by the development of lower-level clouds, with a total six subtypes of fog. In the case of cloud-base lowering fog, the occurrence frequency at 2.6% was not high at 2.6%, but the duration of low visibility below 200 m was very long at 6.9 hours. The seasonal frequency of fog is low in spring and winter, high in summer over islands and coastal areas, and high in autumn over inland areas. The frequency of inland fog, which is characterized by high radiation fog and dense fog, requires attention in terms of transportation safety, with an occurrence time of 0500 LST to 1000 LST. Therefore, systematic analysis of precipitation fog and cloud-base lowering, as well as radiation and advection fog, is required in the analysis of recognizing fog as a disaster and causing transportation disorders.

Forecasting Advection Fog at Busan Area in the Month of July (7월의 부산지방의 이류무예보에 관하여)

  • 한영호
    • Journal of the Korean Society of Fisheries and Ocean Technology
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    • v.9 no.1
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    • pp.19-23
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    • 1973
  • The method of forecasting advection fog at Busan area in July is developed using the Spreen's scatter-diagraam technique. The used Parameters are (1) air temperature (2) dew-point temperature, (3) sea surface temperature (4) resultantt wind direction (5) resultant wind speed in Busan. The skill score and the pcr cent correct based on 4 yeare of dependent data are 0.79 and 90.3% respectively.

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EVALUATION OF SEA FOG DETECTION USING A REMOTE SENSED DATA COMBINED METHOD

  • Heo, Ki-Young;Ha, Kyung-Ja;Kim, Jae-Hwan;Shim, Jae-Seol;Suh, Ae-Sook
    • Proceedings of the KSRS Conference
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    • 2007.10a
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    • pp.294-297
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    • 2007
  • Steam and advection fogs are frequently observed in the Yellow Sea located between Korea and China during the periods of March-April and June-July respectively. This study uses the remote sensing (RS) data for monitoring sea fog. Meteorological data obtained from the Ieodo Ocean Research Station provided an informative synopsis for the occurrence of steam and advection fogs through a ground truth. The RS data used in this study was GOES-9, MTSAT-1R images and QuikSCAT wind data. A dual channel difference (DCD) approach using IR and near-IR channel of GOES-9 and MTSAT-1R satellites was applied to estimate the extension of the sea fog. For the days examined, it was found that not only the DCD but also the texture-related measurement and the weak wind condition are required to separate the sea fog from the low cloud. The QuikSCAT wind is used to provide a weak wind area less than threshold under stable condition of the surface wind around a fog event. The Laplacian computation for a measurement of the homogeneity was designed. A new combined method of DCD, QuikSCAT wind speed and Laplacian was applied in the twelve cases with GOES-9 and MTSAT-1R. The threshold values for DCD, QuikSCAT wind speed and Laplacian are -2.0 K, 8 m $s^{-1}$ and 0.1, respectively. The validation methods such as Heidke skill score, probability of detection, probability of false detection, true skill score and odds ratio show that the new combined method improves the detection of sea fog rather than DCD method.

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