• The Journal of Fisheries Business Administration
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• v.51 no.2
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• pp.25-50
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• 2020

The aim of this study is to overview what changes happened on the maritime field during the early Meiji period, how the compilation of 'Japan Fisheries' linked to the changes, and when the 'Japan Fisheries' was launched, completed and published. The trilogy of Japan Fishing Method, Japan Fishery Products, and Japan's Useful Marine Products are called "Japan's Fishery." These were completed in 1895 for almost ten years since the compilation project was launched in 1886 at the Agricultural and Commercial Ministry. Japan Fishing Method selected, improved and recorded excellent fishing and fishing methods in various Japanese regions at that time whereas Japan Fisheries Products chose excellent fish products from various methods of manufacturing and recorded the enactment and sale of fishery products. Japan's Useful Marine Products is not currently passed on, so it is not known what kind of useful marine products are recorded. However, it can be assumed that the classification method of the "Japanese Fishing Classification Table" published in 1889 was based on the Japan Fishing Index. The cited texts in Japan Fisheries Products are up to 55 documents, including Engisiki and Wakansanzaizukai's "Report of the Great Japan Fishery Association," "Ariticle of the Fisheries Fair," "The Western Fishery Manufacturing Technique" and "Trade Situation with China." Completed with extensive research from old books to the latest fishery information, "Japan's Fishery" is Japan's best "Marine Products Encyclopedia" at the time. It is also a valuable literature that can trace fishing and fishing techniques and methods of manufacturing marine products in each Japanese fishing village before the end of the nineteenth century.

• Korean Journal of Remote Sensing
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• v.38 no.3
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• pp.265-282
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• 2022

Sea surface temperature (SST) is a factor that greatly influences ocean circulation and ecosystems in the Earth system. As global warming causes changes in the SST near the Korean Peninsula, abnormal water temperature phenomena (high water temperature, low water temperature) occurs, causing continuous damage to the marine ecosystem and the fishery industry. Therefore, this study proposes a methodology to predict the SST near the Korean Peninsula and prevent damage by predicting abnormal water temperature phenomena. The study area was set near the Korean Peninsula, and ERA5 data from the European Center for Medium-Range Weather Forecasts (ECMWF) was used to utilize SST data at the same time period. As a research method, Long Short-Term Memory (LSTM) algorithm specialized for time series data prediction among deep learning models was used in consideration of the time series characteristics of SST data. The prediction model predicts the SST near the Korean Peninsula after 1- to 7-days and predicts the high water temperature or low water temperature phenomenon. To evaluate the accuracy of SST prediction, Coefficient of determination (R²), Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE) indicators were used. The summer (JAS) 1-day prediction result of the prediction model, R²=0.996, RMSE=0.119℃, MAPE=0.352% and the winter (JFM) 1-day prediction result is R²=0.999, RMSE=0.063℃, MAPE=0.646%. Using the predicted SST, the accuracy of abnormal sea surface temperature prediction was evaluated with an F1 Score (F1 Score=0.98 for high water temperature prediction in summer (2021/08/05), F1 Score=1.0 for low water temperature prediction in winter (2021/02/19)). As the prediction period increased, the prediction model showed a tendency to underestimate the SST, which also reduced the accuracy of the abnormal water temperature prediction. Therefore, it is judged that it is necessary to analyze the cause of underestimation of the predictive model in the future and study to improve the prediction accuracy.