This page has only limited features, please log in for full access.
Maritime traffic can reflect the diverse and complex relations between countries and regions, such as economic trade and geopolitics. Based on the AIS (Automatic Identification System) trajectory data of ships, this study constructs the Maritime Silk Road traffic network. In this study, we used a complex network theory along with social network analysis and network flow analysis to analyze the spatial distribution characteristics of maritime traffic flow of the Maritime Silk Road; further, we empirically demonstrate the traffic inequality in the route. On this basis, we explore the role of the country in the maritime traffic system and the resulting traffic relations. There are three main results of this study. (1) The inequality in the maritime traffic of the Maritime Silk Road has led to obvious regional differences. Europe, west Asia, northeast Asia, and southeast Asia are the dominant regions of the Maritime Silk Road. (2) Different countries play different maritime traffic roles. Italy, Singapore, and China are the core countries in the maritime traffic network of the Maritime Silk Road; Greece, Turkey, Cyprus, Lebanon, and Israel have built a structure of maritime traffic flow in the eastern Mediterranean Sea, and Saudi Arabia serves as a bridge for maritime trade between Asia and Europe. (3) The maritime traffic relations show the characteristics of regionalization; countries in west Asia and the European Mediterranean region are clearly polarized, and competition–synergy relations have become the main form of maritime traffic relations among the countries in the dominant regions. Our results can provide a scientific reference for the coordinated development of regional shipping, improvement of maritime competition, cooperation strategies for countries, and adjustments in the organizational structure of ports along the Maritime Silk Road.
Naixia Mou; Haonan Ren; Yunhao Zheng; Jinhai Chen; Jiqiang Niu; Tengfei Yang; Lingxian Zhang; Feng Liu. Traffic Inequality and Relations in Maritime Silk Road: A Network Flow Analysis. ISPRS International Journal of Geo-Information 2021, 10, 40 .
AMA StyleNaixia Mou, Haonan Ren, Yunhao Zheng, Jinhai Chen, Jiqiang Niu, Tengfei Yang, Lingxian Zhang, Feng Liu. Traffic Inequality and Relations in Maritime Silk Road: A Network Flow Analysis. ISPRS International Journal of Geo-Information. 2021; 10 (1):40.
Chicago/Turabian StyleNaixia Mou; Haonan Ren; Yunhao Zheng; Jinhai Chen; Jiqiang Niu; Tengfei Yang; Lingxian Zhang; Feng Liu. 2021. "Traffic Inequality and Relations in Maritime Silk Road: A Network Flow Analysis." ISPRS International Journal of Geo-Information 10, no. 1: 40.
Holiday tourism flow is a significant indicator to evaluate the development of tourism. The exploration of the rule of tourism flow between cities can not only provide reasonable suggestions for stimulating demand, promoting consumption and economic development, but also make crucial significance for the management of tourism destinations and the optimization of spatial structure of tourism flow. Based on Weibo check-in data, this paper, by using social network analysis, studies the spatial distribution and network structure characteristics of tourism flow in 50 major cities in China during the National Day holiday in 2018. The results show that: 1) the tourism flow connection of the main cities in China represents a diamond shaped spatial structure with “Beijing-Shanghai-Guangzhou-Chengdu” as the core. There exists spatial heterogeneity in different levels of tourism flow intensity and proximity and selectivity in tourism links between cities; 2) the intensity of tourism connection between cities in China is clearly divided into different levels. On the basis of index of degree of centrality, Beijing and Shanghai are far higher than other cities;3) there are obvious differences between core nodes and edge nodes, with the core nodes often composed of cities with high economic development or rich tourism resources. Although the number is small, it plays a significant role in driving the edge cities; 4) the urban tourism flow network is relatively stable, but most cities have relatively weak tourism links and more small-scale tourism flows. In the division of cohesive subgroups, the fifth and sixth subgroups are not only the main tourist sources but also the main destinations. Whether it is the internal connection of subgroups or the connection with other subgroups, tourism flow has a very high density of connection.
Anjun Li; Naixia Mou; Lingxian Zhang; Tengfei Yang; Wenbao Liu; Feng Liu. Tourism Flow Between Major Cities During China’s National Day Holiday: A Social Network Analysis Using Weibo Check-in Data. IEEE Access 2020, 8, 225675 -225691.
AMA StyleAnjun Li, Naixia Mou, Lingxian Zhang, Tengfei Yang, Wenbao Liu, Feng Liu. Tourism Flow Between Major Cities During China’s National Day Holiday: A Social Network Analysis Using Weibo Check-in Data. IEEE Access. 2020; 8 (99):225675-225691.
Chicago/Turabian StyleAnjun Li; Naixia Mou; Lingxian Zhang; Tengfei Yang; Wenbao Liu; Feng Liu. 2020. "Tourism Flow Between Major Cities During China’s National Day Holiday: A Social Network Analysis Using Weibo Check-in Data." IEEE Access 8, no. 99: 225675-225691.
Geo-located travel blogs, a new data source, enable to achieve more detailed analysis of tourists' spatio-temporal behavior. Taking Chinese tourists in Nordic countries as the research object, this paper focuses on their behavior, seasonal patterns and complex network effects by using geo-located travel blog data collected from Qunar.com. The results show that: (1) Chinese tourists visiting Nordic countries are often experienced in traveling. The local climate during the cold season does not prevent them from pursuing the aurora scenery. (2) The travel behavior of Chinese tourists is spatially heterogeneous. The network analysis reveals that Iceland showcases stronger, compared to the other Nordic countries, community independence and small world effect. (3) During the warm season, Chinese tourists choose a variety of destinations, while in cold season, they tend to choose destinations with higher chances for spotting the northern lights. These results provide helpful information for the tourism management departments of Nordic countries to improve their marketing and development efforts directed for Chinese tourists.
Yunhao Zheng; Naixia Mou; Lingxian Zhang; Teemu Makkonen; Tengfei Yang. Chinese tourists in Nordic countries: An analysis of spatio-temporal behavior using geo-located travel blog data. Computers, Environment and Urban Systems 2020, 85, 101561 -101561.
AMA StyleYunhao Zheng, Naixia Mou, Lingxian Zhang, Teemu Makkonen, Tengfei Yang. Chinese tourists in Nordic countries: An analysis of spatio-temporal behavior using geo-located travel blog data. Computers, Environment and Urban Systems. 2020; 85 ():101561-101561.
Chicago/Turabian StyleYunhao Zheng; Naixia Mou; Lingxian Zhang; Teemu Makkonen; Tengfei Yang. 2020. "Chinese tourists in Nordic countries: An analysis of spatio-temporal behavior using geo-located travel blog data." Computers, Environment and Urban Systems 85, no. : 101561-101561.
As one of the most strategically important natural resources, crude oil can be dangerous to transport by sea. The resilience of a maritime transport network denotes the ability of the system to withstand damage and remain operational after disturbances, representing the invulnerability of the network and its ability to recover from harm. In this study, we built a crude oil transportation network titled the Maritime Silk Road using Automatic Identification System (AIS) sensor data, designed a resilience assessment framework based on complex network theory, and assessed the resilience of the maritime crude oil transportation network from both qualitative and quantitative perspectives with the help of complex network metrics and a resilience model. The results show that the topology of the crude oil transportation network has a significant impact on its resilience, in that network density and centrality are negatively related to network resilience, whereas network connectivity and size are positively related to resilience. Subsequently, the resilience of crude oil transportation networks declines at a steady rate under random attacks but declines sharply under intentional attacks. Finally, a comprehensive analysis of invulnerability and recovery in the context of resilience concludes that strengthening small and medium-sized ports in the network is important to enhance network resilience. These results can provide reference and decision support for port planning, route design, optimization, and form a foundation for a more secure and reliable maritime transportation network system.
Naixia Mou; Shuyue Sun; Tengfei Yang; Zhipeng Wang; Yunhao Zheng; Jinhai Chen; Lingxian Zhang. Assessment of the Resilience of a Complex Network for Crude Oil Transportation on the Maritime Silk Road. IEEE Access 2020, 8, 181311 -181325.
AMA StyleNaixia Mou, Shuyue Sun, Tengfei Yang, Zhipeng Wang, Yunhao Zheng, Jinhai Chen, Lingxian Zhang. Assessment of the Resilience of a Complex Network for Crude Oil Transportation on the Maritime Silk Road. IEEE Access. 2020; 8 (99):181311-181325.
Chicago/Turabian StyleNaixia Mou; Shuyue Sun; Tengfei Yang; Zhipeng Wang; Yunhao Zheng; Jinhai Chen; Lingxian Zhang. 2020. "Assessment of the Resilience of a Complex Network for Crude Oil Transportation on the Maritime Silk Road." IEEE Access 8, no. 99: 181311-181325.
Assortativity, one of the mixing patterns of complex networks, is characterized by measuring whether the nodes are preferentially connected to the nodes with a similar scale. While numerous studies have examined the assortative characteristics of various real-world networks, few studies have attempted to analyze the assortativity of networks in which the subject of trade is bulk. The novelty of this research is that, for the first time, the assortative coefficient method in physics is introduced into the bulk trade network, and the Automatic Identification System (AIS) data is used to explore the assortative mixing characteristics of the network. From the perspective of multi-scale (port and country) and multi-dimensional (node, link, and network) structure, this paper reveals the tendency of trade connection and explores the trade rules of bulk in networks. The results show that: (1) The trade network of bulk on the Maritime Silk Road is assortative. With the increase of spatial scale, the extent of assortativity is also gradually increasing; (2) In the bulk network of ports, trade cooperation shows the rule of distance attenuation; In the national bulk network, it shows the rule of preferential connection; (3) Ports with high out-degree will export bulk to the ports with high out-degree with broad market, while countries with high out-degree export to high in-degree countries with strong demand. The present study is expected to provide valuable references for port planning, national formulation of scientific bulk trade strategy, and promotion of coordinated development of bulk trade network along the Maritime Silk Road.
Naixia Mou; Yujie Fang; Tengfei Yang; Lingxian Zhang. Assortative Analysis of Bulk Trade Complex Network on Maritime Silk Road. IEEE Access 2020, 8, 131928 -131938.
AMA StyleNaixia Mou, Yujie Fang, Tengfei Yang, Lingxian Zhang. Assortative Analysis of Bulk Trade Complex Network on Maritime Silk Road. IEEE Access. 2020; 8 ():131928-131938.
Chicago/Turabian StyleNaixia Mou; Yujie Fang; Tengfei Yang; Lingxian Zhang. 2020. "Assortative Analysis of Bulk Trade Complex Network on Maritime Silk Road." IEEE Access 8, no. : 131928-131938.
Jing Zhao; Jason Blake Cohen; Yating Chen; Weihong Cui; Qianqian Cao; Tengfei Yang; Guoqing Li. High-resolution spatiotemporal patterns of China’s FFCO2 emissions under the impact of LUCC from 2000 to 2015. Environmental Research Letters 2020, 15, 044007 .
AMA StyleJing Zhao, Jason Blake Cohen, Yating Chen, Weihong Cui, Qianqian Cao, Tengfei Yang, Guoqing Li. High-resolution spatiotemporal patterns of China’s FFCO2 emissions under the impact of LUCC from 2000 to 2015. Environmental Research Letters. 2020; 15 (4):044007.
Chicago/Turabian StyleJing Zhao; Jason Blake Cohen; Yating Chen; Weihong Cui; Qianqian Cao; Tengfei Yang; Guoqing Li. 2020. "High-resolution spatiotemporal patterns of China’s FFCO2 emissions under the impact of LUCC from 2000 to 2015." Environmental Research Letters 15, no. 4: 044007.
The human immunodeficiency virus (HIV) infection rate for men who have sex with men (MSM) has rapidly increased in recent years in China and the migrant population accounts for a large proportion of this increase. The migration of MSM not only poses difficulties for government departments charged with treating the disease, but also increases the spread of HIV in geographical space, so it is important to understand the geographical distribution and migrant patterns of MSM. We searched the largest dating website in China to obtain open information from all users in the Chinese mainland from January 2006 to August 2017. For the analysis, the datasets were merged according to units of time and administrative regions. In total, 1,356,609 records were obtained for this study. The main users of the website were single males aged 18–35 years old. Most of the users were located in the large and mid-sized cities of East China. The distribution of MSM was strongly associated with the distribution of the development of service industry in geographical space. The main flow of MSM are mainly located inside the province as internal flow. For those MSM who prefer to migrate to other provinces, the Beijing-Tianjin-Hebei area, the Yangtze River Delta, the Pearl River Delta, and Sichuan and Chongqing area were their primary destinations. The interprovincial migration behavior of MSM was closely related to an increased average income. MSM prefer to migrate to cities with developed economies and open cultures. It is important to strengthen the management of migrant MSM and increase their basic understanding of HIV.
Dacang Huang; Jinfeng Wang; Tengfei Yang. Mapping the Spatial–Temporal Distribution and Migration Patterns of Men Who Have Sex with Men in Mainland China: A Web-Based Study. International Journal of Environmental Research and Public Health 2020, 17, 1469 .
AMA StyleDacang Huang, Jinfeng Wang, Tengfei Yang. Mapping the Spatial–Temporal Distribution and Migration Patterns of Men Who Have Sex with Men in Mainland China: A Web-Based Study. International Journal of Environmental Research and Public Health. 2020; 17 (5):1469.
Chicago/Turabian StyleDacang Huang; Jinfeng Wang; Tengfei Yang. 2020. "Mapping the Spatial–Temporal Distribution and Migration Patterns of Men Who Have Sex with Men in Mainland China: A Web-Based Study." International Journal of Environmental Research and Public Health 17, no. 5: 1469.
The abnormal change in the global climate has increased the chance of urban rainstorm disasters, which greatly threatens people’s daily lives, especially public travel. Timely and effective disaster data sources and analysis methods are essential for disaster reduction. With the popularity of mobile devices and the development of network facilities, social media has attracted widespread attention as a new source of disaster data. The characteristics of rich disaster information, near real-time transmission channels, and low-cost data production have been favored by many researchers. These researchers have used different methods to study disaster reduction based on the different dimensions of information contained in social media, including time, location and content. However, current research is not sufficient and rarely combines specific road condition information with public emotional information to detect traffic impact areas and assess the spatiotemporal influence of these areas. Thus, in this paper, we used various methods, including natural language processing and deep learning, to extract the fine-grained road condition information and public emotional information contained in social media text to comprehensively detect and analyze traffic impact areas during a rainstorm disaster. Furthermore, we proposed a model to evaluate the spatiotemporal influence of these detected traffic impact areas. The heavy rainstorm event in Beijing, China, in 2018 was selected as a case study to verify the validity of the disaster reduction method proposed in this paper.
Tengfei Yang; Jibo Xie; Guoqing Li; Naixia Mou; Cuiju Chen; Jing Zhao; Zhan Liu; Zhenyu Lin. Traffic Impact Area Detection and Spatiotemporal Influence Assessment for Disaster Reduction Based on Social Media: A Case Study of the 2018 Beijing Rainstorm. ISPRS International Journal of Geo-Information 2020, 9, 136 .
AMA StyleTengfei Yang, Jibo Xie, Guoqing Li, Naixia Mou, Cuiju Chen, Jing Zhao, Zhan Liu, Zhenyu Lin. Traffic Impact Area Detection and Spatiotemporal Influence Assessment for Disaster Reduction Based on Social Media: A Case Study of the 2018 Beijing Rainstorm. ISPRS International Journal of Geo-Information. 2020; 9 (2):136.
Chicago/Turabian StyleTengfei Yang; Jibo Xie; Guoqing Li; Naixia Mou; Cuiju Chen; Jing Zhao; Zhan Liu; Zhenyu Lin. 2020. "Traffic Impact Area Detection and Spatiotemporal Influence Assessment for Disaster Reduction Based on Social Media: A Case Study of the 2018 Beijing Rainstorm." ISPRS International Journal of Geo-Information 9, no. 2: 136.
Port development potential refers to the potential but unrealized status and capacity of ports, which can become a reality when external conditions permit. A correct analysis of port development potential helps to better formulate investment response plans and national development strategies, and finally achieve the sustainable development of the ports. Based on the Automatic Identification System (AIS) data, basic port data, hinterland city data, traffic network data, and relevant economic and policy data, we constructed an evaluation index system of port development potential, and evaluated the development potential of eight representative ports in the Yangtze River Delta port group of China with the methods of FAHP-entropy (FAHP—Fuzzy Analytical Hierarchy Process). The results show that: (1) The development potential of the port group in the Yangtze River Delta is positioned in the upper middle level; its development prospects are considerable, and other countries or ports could give priority of cooperation with it to maximize its benefits. (2) Port economy and policy are the primary core indicators affecting the development potential of ports, while per capita GDP (gross domestic product), number of berths, and port network status are the secondary core indicators affecting the development potential of ports. (3) Ports with larger development potential usually have one or more outstanding indicators, while the potential of ports with balanced development among all indicators is relatively weak.
Naixia Mou; Chunying Wang; Tengfei Yang; Lingxian Zhang. Evaluation of Development Potential of Ports in the Yangtze River Delta Using FAHP-Entropy Model. Sustainability 2020, 12, 493 .
AMA StyleNaixia Mou, Chunying Wang, Tengfei Yang, Lingxian Zhang. Evaluation of Development Potential of Ports in the Yangtze River Delta Using FAHP-Entropy Model. Sustainability. 2020; 12 (2):493.
Chicago/Turabian StyleNaixia Mou; Chunying Wang; Tengfei Yang; Lingxian Zhang. 2020. "Evaluation of Development Potential of Ports in the Yangtze River Delta Using FAHP-Entropy Model." Sustainability 12, no. 2: 493.
Nearly 70% of the world’s maritime crude oil transportation relies on the Maritime Silk Road (MSR). In order to deeply explore the impact of slumping oil price on the shipping situation of tanker along the MSR, this paper establishes the relationship between monthly ship and oil price through Autoregressive Distributed Lag model. Distributions of cargo flow before and after the oil price slumped are compared to explore the changing law of tanker shipping situation. The study finds: (1) The correlation between the cargo flow situation of the tanker seaborne export and oil price, where the export cargo flow correlation is stronger than that of the import cargo flow. (2) The MSR tanker shipping situation is lagging (3 months) behind the impact of oil price. The lag effect in Europe, North Asia and East Asia is strong while that in Southeast Asia and South Asia is weak. (3) After the oil price slumped, the tanker shipping cargo flow increased less during the crude oil export stage, and the increase in the crude oil shipping trade after the transfer period was larger. The research results can provide a scientific basis for improving the decision-making ability of the crude oil shipping market and formulating maritime operations management measures.
Naixia Mou; Yanxin Xie; Tengfei Yang; Hengcai Zhang; Yoo Ri Kim. The Impact of Slumping Oil Price on the Situation of Tanker Shipping along the Maritime Silk Road. Sustainability 2019, 11, 4796 .
AMA StyleNaixia Mou, Yanxin Xie, Tengfei Yang, Hengcai Zhang, Yoo Ri Kim. The Impact of Slumping Oil Price on the Situation of Tanker Shipping along the Maritime Silk Road. Sustainability. 2019; 11 (17):4796.
Chicago/Turabian StyleNaixia Mou; Yanxin Xie; Tengfei Yang; Hengcai Zhang; Yoo Ri Kim. 2019. "The Impact of Slumping Oil Price on the Situation of Tanker Shipping along the Maritime Silk Road." Sustainability 11, no. 17: 4796.
Social media contains a lot of geographic information and has been one of the more important data sources for hazard mitigation. Compared with the traditional means of disaster-related geographic information collection methods, social media has the characteristics of real-time information provision and low cost. Due to the development of big data mining technologies, it is now easier to extract useful disaster-related geographic information from social media big data. Additionally, many researchers have used related technology to study social media for disaster mitigation. However, few researchers have considered the extraction of public emotions (especially fine-grained emotions) as an attribute of disaster-related geographic information to aid in disaster mitigation. Combined with the powerful spatio-temporal analysis capabilities of geographical information systems (GISs), the public emotional information contained in social media could help us to understand disasters in more detail than can be obtained from traditional methods. However, the social media data is quite complex and fragmented, both in terms of format and semantics, especially for Chinese social media. Therefore, a more efficient algorithm is needed. In this paper, we consider the earthquake that happened in Ya’an, China in 2013 as a case study and introduce the deep learning method to extract fine-grained public emotional information from Chinese social media big data to assist in disaster analysis. By combining this with other geographic information data (such population density distribution data, POI (point of interest) data, etc.), we can further assist in the assessment of affected populations, explore emotional movement law, and optimize disaster mitigation strategies.
Tengfei Yang; Jibo Xie; Guoqing Li; Naixia Mou; Zhenyu Li; Chuanzhao Tian; Jing Zhao. Social Media Big Data Mining and Spatio-Temporal Analysis on Public Emotions for Disaster Mitigation. ISPRS International Journal of Geo-Information 2019, 8, 29 .
AMA StyleTengfei Yang, Jibo Xie, Guoqing Li, Naixia Mou, Zhenyu Li, Chuanzhao Tian, Jing Zhao. Social Media Big Data Mining and Spatio-Temporal Analysis on Public Emotions for Disaster Mitigation. ISPRS International Journal of Geo-Information. 2019; 8 (1):29.
Chicago/Turabian StyleTengfei Yang; Jibo Xie; Guoqing Li; Naixia Mou; Zhenyu Li; Chuanzhao Tian; Jing Zhao. 2019. "Social Media Big Data Mining and Spatio-Temporal Analysis on Public Emotions for Disaster Mitigation." ISPRS International Journal of Geo-Information 8, no. 1: 29.