• Title/Summary/Keyword: Pohang Korea

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Throughput Prediction of Pohang Port using Time Series Data: Application of SARIMA, Prophet and Neural Prophet (시계열 데이터를 활용한 포항항 물동량 예측: SARIMA, Prophet, Neural Prophet의 적용)

  • Jin-Ho Oh;Jeong-Won Choi;Tae-Hyun Kang;Young-Joon Seo;Dong-Wook Kwak
    • Korea Trade Review
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    • v.47 no.6
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    • pp.291-305
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    • 2022

  • In this study, the volume of Pohang Port was predicted. All cargo of Pohang port, iron ore, steel, and bituminous coals were selected as prediction targets. SARIMA, Prophet, and Neural Prophet were used as analysis methods. The predictive power of each model was verified, and a predictive model with high performance was used to predict the volume of goods in Pohang port. As a result of the analysis, it was found that Neural Prophet showed the highest performance in all predictive power. As a result of predicting the future volume of goods until August 2027 using Neural Prophet, it was found that the volume of all items in Pohang port was decreasing. In particular, it was analyzed that the decline in steel cargo was steep. In order to increase the volume of cargo at Pohang port, it is necessary to diversify the cargo handled at Pohang port and check the policy of increasing the volume of cargo.

  • https://doi.org/10.22659/KTRA.2022.47.6.291 인용 PDF

Damage Proxy Map (DPM) of the 2016 Gyeongju and 2017 Pohang Earthquakes Using Sentinel-1 Imagery

  • Nur, Arip Syaripudin;Lee, Chang-Wook
    • Korean Journal of Remote Sensing
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    • v.37 no.1
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    • pp.13-22
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    • 2021

  • The ML 5.8 earthquake shocked Gyeongju, Korea, at 11:32:55 UTC on September 12, 2016. One year later, on the afternoon of November 15, 2017, the ML 5.4 earthquake occurred in Pohang, South Korea. The earthquakes injured many residents, damaged buildings, and affected the economy of Gyeongju and Pohang. The damage proxy maps (DPMs) were generated from Sentinel-1 synthetic aperture radar (SAR) imagery by comparing pre- and co-events interferometric coherences to identify anomalous changes that indicate damaged by the earthquakes. DPMs manage to detect coherence loss in residential and commercial areas in both Gyeongju and Pohang earthquakes. We found that our results show a good correlation with the Korea Meteorological Administration (KMA) report with Modified Mercalli Intensity (MMI) scale values of more than VII (seven). The color scale of Sentinel-1 DPMs indicates an increasingly significant change in the area covered by the pixel, delineating collapsed walls and roofs from the official report. The resulting maps can be used to assess the distribution of seismic damage after the Gyeongju and Pohang earthquakes and can also be used as inventory data of damaged buildings to map seismic vulnerability using machine learning in Gyeongju or Pohang.

  • https://doi.org/10.7780/kjrs.2021.37.1.2 인용 PDF KSCI HTML