Ryuichi Shibasaki 교수

This study focuses on the expected impact of Northern Sea Route (NSR) usage and the Panama Canal (PC) expansion on liquefied natural gas (LNG) imports of Asian countries, from not only the macroeconomic viewpoint but also diversification of the supplying countries. First, the amounts saved from shipping costs due to these events are estimated, based on scenarios on the navigable period of the NSR, transit fee of the NSR considering the exchange rate between the Russian ruble and US dollar, and b

Abstract Enriched navigational information provided by an automatic identification system (AIS) could improve the estimation accuracy of trade patterns analysis by using different data sources. This paper estimates the global trade flow pattern of dry bulk cargo by commodity, namely iron ore, coal, grains, fertilisers, and iron and steel. We use AIS data and the information on commodities handled in ports, estimated by using a two-tiered Geohash geocoding. Estimation results are accurate at coun

This study estimates the port-based global shipping pattern of liquefied natural gas (LNG) from a vessel movement database. In general, the only information related to global shipping available is the vessel movement database; however, this does not include specifics of the cargo, making detailed estimates of the global shipping of any cargo difficult. Therefore, a method based on information from export and import terminals globally is proposed that allows laden or in-ballast shipping to be est

Central Asia (CA), comprising six independent countries and the Xinjiang Uygur Autonomous Region of China (XUAR), is an archetypal landlocked region suffering from poor access to global markets. Possible gateway seaports for CA cargo are scattered across the Eurasian continent, and access requires long-haul transport. Thanks to their shorter hinterland transport distances, Pakistani ports, including Gwadar Port, which has drawn attention in the context of China’s Belt and Road Initiative, are in

This study applied graph theory to conduct an empirical analysis of the evolution of global maritime container shipping networks, mainly focusing on the 1970s. In addition to analyzing the change in overall structures of the networks over the long term (from the 1970s to the present) and midterm (in the 1970s), the authors examined the changes in the container shipping networks before and after the reopening of the Suez Canal in 1975. As a result, it was confirmed that the initial single polar n

This study focuses on container shipping in Myanmar, which is expected to grow manifold in the near future, given the country’s rapid economic growth rates. This study simulates the impact of Myanmar’s logistics policies on container shipping. These initiatives include the improvement of the East–West Corridor of the Greater Mekong Subregion and the development of the Southern Corridor and Dawei port. The global logistics intermodal network simulation model including both maritime shipping and l

When discussing a roadmap for realizing trade liberalization and transport efficiency, a comprehension of the quantitative effects of the related policies could be highly supportive and suggestive. The authors developed a successive prediction system on trade value and international cargo flow that provides an effective tool for quantifying the impacts of trade and transport policy on international cargo shipping. In this paper, a forecasting system called Trade and Logistics Forecasting System

Cambodia has maintained steady economic growth in the past few years; however, its logistics infrastructure is still underdeveloped. Therefore, many logistics projects are being planned and implemented in Cambodia to improve its infrastructure. Because of a growing need to evaluate the effects of these projects quantitatively, this study forecasts the container flows in Cambodia in 2025, by taking into account the economic growth and progress of these projects. This study uses a combination of t

This study proposes the use of satellite images and a vessel’s automatic identification system (AIS) data to evaluate the congestion level at container ports for operational efficiency analysis, which was never attempted in previous studies. The congestion level in container yards is classified by developing a convolutional neural network (CNN) model and an annotation tool to reduce the workload of creating training data. The annotation tool calculates the number of vertically stacked containers

This study examines the development of a machine-learning model to forecast weekly throughputs of dry bulk cargo in the short term based on automatic identification system (AIS) data. Specifically, the weekly amounts of iron ore exported from several major ports in Australia and Brazil in the latter half of 2019 are forecasted three weeks in advance using a long short-term memory model. We examine many variables extracted from AIS data, including the vessel position, speed, draught, and destinat