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해상교통조사 관측일수에 관한 연구

A Study on the Observation Days of Maritime Traffic Investigation

  • 투고 : 2015.06.24
  • 심사 : 2015.08.27
  • 발행 : 2015.08.31

초록

본 연구는 관측일수에 따른 교통량의 신뢰성을 검증하고자 한다. 목포항의 1년간 선박자동식별장치(AIS) 자료를 사용하여 월별, 요일별, 시간별 변화지수를 비교한 후, 각 관측일수에 따른 최대표준오차를 산출하였다. 월별변화지수를 비교한 결과 9월달 1.11, 2월달 0.84로 나타나 9월달이 2월달 교통량 보다 약 32.1 % 많은 것으로 나타났다. 요일변화지수는 화요일 1.05, 일요일 0.92로 나타나 화요일이 일요일 교통량보다 약 14.1 % 많았다. 해상교통조사는 요일변화지수를 고려하여 최소 1주일 이상 실시하면 최대표준오차를 21 % 이내로 산출할 수 있다. 따라서 해상교통조사 관측시기에 따라 각 변화지수를 적용하여 교통량의 흐름을 반영한 연구가 뒷받침 되어야 하겠다.

This study is to compare variation indexes by monthly, weekly and hourly using AIS data, which was collected for 365 days from January 1st to December 31st, 2013 at Mokpo Port and then, computed the maximum standard error by observation days. The comparison of monthly variation indexes showed that the monthly variation indexes for September and February were 1.11 and 0.84, respectively, in turn revealing that the maritime traffic in September was about 32.1 % larger than February. Also, the daily variation indexes for Tuesday and Sunday were 1.05 and 0.92, respectively, in turn revealing that the maritime traffic in Tuesday was about 14.1 % larger than Sunday. When the maritime traffic investigation is executed for at least 1 week in consideration of the daily variation index, it is possible to reduce the maximum standard error rate to be within 21 %. Therefore, if the maritime traffic investigation is made in the month and week with low maritime traffic, each variation index should be applied to reflect the actual maritime traffic.

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참고문헌

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피인용 문헌

  1. A Study on Traffic Safety Assessments for Fishing Vessels Near the Southwest Sea Offshore Wind Farm vol.23, pp.3, 2015, https://doi.org/10.7837/kosomes.2017.23.3.231
  2. 부산 북항 통항 선박간의 시간간격 최적 확률분포에 관한 연구 vol.43, pp.6, 2015, https://doi.org/10.5394/kinpr.2019.43.6.413