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With the further advent of the era of big data, the scale of social media data containing geolocation information is exploding, providing a new source of big data information and perspective for an in-depth study of the changing spatio-temporal and geographical characteristics of the current tourist population. This paper extracts data on popular attractions in the Tibet Autonomous Region using the HDBSCAN algorithm combined with the TF-IDF algorithm based on information on images with geotags shared by users in the Flickr image sharing site from 2005-2018. Social network analysis was used to explore the changes in the spatial and temporal characteristics of inbound tourism flows in Tibet. The results show that: (1) in terms of temporal characteristics, the number of inbound tourists shows obvious off-peak seasons, with relatively high sensitivity to the influence of economic, policy and infrastructure construction factors; (2) in terms of spatial distribution characteristics, the inbound tourism flow in Tibet shows an “axis-scattered” distribution. The core area is centred on Lhasa and extends in three directions: west, north and east along important roads.
Huajian Gao; Naixia Mou. Changes in the spatial and temporal characteristics of inbound tourism flows in Tibet based on geotagged photographs. E3S Web of Conferences 2021, 251, 03009 .
AMA StyleHuajian Gao, Naixia Mou. Changes in the spatial and temporal characteristics of inbound tourism flows in Tibet based on geotagged photographs. E3S Web of Conferences. 2021; 251 ():03009.
Chicago/Turabian StyleHuajian Gao; Naixia Mou. 2021. "Changes in the spatial and temporal characteristics of inbound tourism flows in Tibet based on geotagged photographs." E3S Web of Conferences 251, no. : 03009.
Changes in snow cover over the Tibetan Plateau (TP) have a significant impact on agriculture, hydrology, and ecological environment of surrounding areas. This study investigates the spatio-temporal pattern of snow depth (SD) and snow cover days (SCD), as well as the impact of temperature and precipitation on snow cover over TP from 1979 to 2018 by using the ERA5 reanalysis dataset, and uses the Mann–Kendall test for significance. The results indicate that (1) the average annual SD and SCD in the southern and western edge areas of TP are relatively high, reaching 10 cm and 120 d or more, respectively. (2) In the past 40 years, SD (s = 0.04 cm decade–1, p = 0.81) and SCD (s = −2.3 d decade–1, p = 0.10) over TP did not change significantly. (3) The positive feedback effect of precipitation is the main factor affecting SD, while the negative feedback effect of temperature is the main factor affecting SCD. This study improves the understanding of snow cover change and is conducive to the further study of climate change on TP.
Chi Zhang; Naixia Mou; Jiqiang Niu; Lingxian Zhang; Feng Liu. Spatio-Temporal Variation Characteristics of Snow Depth and Snow Cover Days over the Tibetan Plateau. Water 2021, 13, 307 .
AMA StyleChi Zhang, Naixia Mou, Jiqiang Niu, Lingxian Zhang, Feng Liu. Spatio-Temporal Variation Characteristics of Snow Depth and Snow Cover Days over the Tibetan Plateau. Water. 2021; 13 (3):307.
Chicago/Turabian StyleChi Zhang; Naixia Mou; Jiqiang Niu; Lingxian Zhang; Feng Liu. 2021. "Spatio-Temporal Variation Characteristics of Snow Depth and Snow Cover Days over the Tibetan Plateau." Water 13, no. 3: 307.
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.
Location advantages of ports refer to the current developments of ports based on their conditions, such as geographic location, traffic accessibility and hinterland economy, etc., and the spatial pattern of ports’ location advantages reflects the spatial distributions, the regularities and the correlations among their conditions for development. A good understanding of the spatial patterns of ports’ location advantages can help to better identify the relative advantages of ports, position ports’ functions and make strategic plans for development. This paper selected 1259 ports from 63 countries along the Maritime Silk Road as research objects and builds an accessing model to analyze their location advantages on the bases of six factors: the influence of strategic shipping pivot, the competitiveness of port location potential, port network status, the influence of city, the influence of traffic trunk, and road network density in hinterland. The study has the following three findings. Firstly, the location advantages of ports show a “high-low-high” distribution pattern from the west to the east, displaying an obvious “core-periphery” regionalized distribution. Secondly, most ports have high location advantages, mainly located in Strait of Malacca, the United Arab Emirates, northern Mediterranean coastal region and China-Japan region, the top 10 ports are mainly located in Singapore, China, Malaysia and Japan, indicating that the shipping industry in Asia-Pacific region has stepped to the far front of the global competition; slow economic growths, wars, far away from the Belt and Road countries or bad climate have low location advantages, mainly located in African coastal areas, Oceania, Northeast Europe and Russia. Thirdly, compared with the landward location advantages, the seaward location advantages have a higher influence, and different indicators of location advantages have different influences on the evaluation results, the competitiveness of port location potential being the core indicator.
Naixia Mou; Chunying Wang; Jinhai Chen; Tengfei Yang; Lingxian Zhang; Mengdi Liao. Spatial pattern of location advantages of ports along the Maritime Silk Road. Journal of Geographical Sciences 2021, 31, 149 -176.
AMA StyleNaixia Mou, Chunying Wang, Jinhai Chen, Tengfei Yang, Lingxian Zhang, Mengdi Liao. Spatial pattern of location advantages of ports along the Maritime Silk Road. Journal of Geographical Sciences. 2021; 31 (1):149-176.
Chicago/Turabian StyleNaixia Mou; Chunying Wang; Jinhai Chen; Tengfei Yang; Lingxian Zhang; Mengdi Liao. 2021. "Spatial pattern of location advantages of ports along the Maritime Silk Road." Journal of Geographical Sciences 31, no. 1: 149-176.
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.
Previous studies have shown that the existing maritime network presents unbalanced characteristics as reported by Mou et al. (Sustainability, 10(4): 977–989, 2018). The research in this paper shows that the network movement caused by the opening of the Arctic Northeast Passage will share part of the pressure of the Belt and Road passage, which will play a positive role in the global maritime transportation network. Based on the 2014 global container Automatic Identification System (AIS) data, this research constructs a global maritime transportation network and conducts scenario simulations on the opening of the Arctic Northeast Passage. An evaluation system based on a complex network index is established to evaluate changes in the geometric characteristics of maritime network and community characteristics, and PageRank is used to evaluate the status changes of ports in communities before and after the opening of the network. Finally, the impact of the opening of the Arctic Northeast Passage on the global maritime network pattern is analyzed and discussed. Results show that after opening the Arctic Northeast Passage, (1) the small-world features of the global maritime network are more obvious and the scale-free features are weaker, which indicates that the transportation efficiency of the global network is promoted; (2) the center of global maritime network moves northward with a latitude of 1.3° and eastward with a longitude of 4°; and (3) the importance of some ports, such as the Middle East, Mediterranean, and Southeast Asia communities, has reduced by 0.0073, 0.0078, and 0.0092 respectively. Conversely, the importance of some ports has increased, such as the Northeast Asia community and West Europe community, with increase values of 0.0074 and 0.0097 respectively. These findings are expected to provide advice on national strategies and regional port investments.
Naixia Mou; Jie Li; Shuyue Sun; Tengfei Yang; Lingxian Zhang; Hengcai Zhang; Wenbao Liu. The impact of opening the Arctic Northeast Passage on the global maritime transportation network pattern using AIS data. Arabian Journal of Geosciences 2020, 13, 1 -16.
AMA StyleNaixia Mou, Jie Li, Shuyue Sun, Tengfei Yang, Lingxian Zhang, Hengcai Zhang, Wenbao Liu. The impact of opening the Arctic Northeast Passage on the global maritime transportation network pattern using AIS data. Arabian Journal of Geosciences. 2020; 13 (11):1-16.
Chicago/Turabian StyleNaixia Mou; Jie Li; Shuyue Sun; Tengfei Yang; Lingxian Zhang; Hengcai Zhang; Wenbao Liu. 2020. "The impact of opening the Arctic Northeast Passage on the global maritime transportation network pattern using AIS data." Arabian Journal of Geosciences 13, no. 11: 1-16.
Spatial patterns of tourist flows represent the movement of tourists and show differences in tourism resources giving advice for promoting balanced and sustainable tourism development. This paper proposes a novel framework for analyzing these patterns based on tourists' digital footprint data collected from online travel diaries. Based on illustrative case study data from Qingdao (China), the framework, combining traditional quantitative and social network analysis, is able to pinpoint: (1) The influence of distance decay and attractions’ popularity on the spatial patterns of tourist flows; (2) The uneven distribution of the core tourist nodes and the existence of the structural hole phenomenon, which form a network pattern with unbalanced power and intense internal competition; (3) The formation of the core area for tourism along the coastline – as is typical for coastal tourism cities. This difference of tourism resources between coastal and inland areas, thus, remains a challenge for future tourism development in Qingdao.
Naixia Mou; Yunhao Zheng; Teemu Makkonen; Tengfei Yang; Jinwen(Jimmy) Tang; Yan Song. Tourists’ digital footprint: The spatial patterns of tourist flows in Qingdao, China. Tourism Management 2020, 81, 104151 .
AMA StyleNaixia Mou, Yunhao Zheng, Teemu Makkonen, Tengfei Yang, Jinwen(Jimmy) Tang, Yan Song. Tourists’ digital footprint: The spatial patterns of tourist flows in Qingdao, China. Tourism Management. 2020; 81 ():104151.
Chicago/Turabian StyleNaixia Mou; Yunhao Zheng; Teemu Makkonen; Tengfei Yang; Jinwen(Jimmy) Tang; Yan Song. 2020. "Tourists’ digital footprint: The spatial patterns of tourist flows in Qingdao, China." Tourism Management 81, no. : 104151.
Association rules can detect the association pattern between POIs (point of interest) and serve the application of indoor location. In this paper, a new index, tuple-relation, is defined, which reflects the association strength between POI sets in indoor environment. This index considers the potential association information such as spatial and semantic information between indoor POI sets. On this basis, a new R-FP-growth (tuple-relation frequent pattern growth) algorithm for mining association rules in indoor environment is proposed, which makes comprehensive use of the co-occurrence probability, conditional probability, and multiple potential association information among POI sets, to form a new support-confidence-relation constraint framework and to improve the quality and application value of mining results. Experiments are performed, using real Wi-Fi positioning trajectory data from a shopping mall. Experimental results show that the tuple-relation calculation method based on cosine similarity has the best effect, with an accuracy of 87%, and 19% higher than that of the traditional FP-growth algorithm.
Naixia Mou; Hongen Wang; Hengcai Zhang; Xin Fu. Association Rule Mining Method Based on the Similarity Metric of Tuple-Relation in Indoor Environment. IEEE Access 2020, 8, 52041 -52051.
AMA StyleNaixia Mou, Hongen Wang, Hengcai Zhang, Xin Fu. Association Rule Mining Method Based on the Similarity Metric of Tuple-Relation in Indoor Environment. IEEE Access. 2020; 8 (99):52041-52051.
Chicago/Turabian StyleNaixia Mou; Hongen Wang; Hengcai Zhang; Xin Fu. 2020. "Association Rule Mining Method Based on the Similarity Metric of Tuple-Relation in Indoor Environment." IEEE Access 8, no. 99: 52041-52051.
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.
We estimated the equivalent water height (EWH) over Qinghai-Tibet Plateau (QTP) from time-variable gravity field models derived from the Gravity Recovery and Climate Experiment (GRACE) data released by CSR, JPL, GFZ, and GRGS. EWHs calculated from CSR, GFZ, JPL, and GRGS models, respectively, were taken as the observed signals, and the corresponding 4 independent source signals of each observed signal were determined by independent component analysis to remove the north-south stripe errors and identify the fourth independent components as meaningful water storage change (WSC) signals. These interesting signals are highly correlated to those predicted by hydrological models such as CPC and GLDAS with the maximum and minimum correlation coefficients of 0.89 and − 0.5, respectively. The result shows that EWHs over QTP wholly have the rising trend with the mean rate of WSC of greater than 0.7 mm/year. The in situ precipitations on 140 meteorological stations are also analyzed to verify the water storage changes determined from GRACE data. The results indicate that precipitation is one important water source to replenish the groundwater in QTP.
Xin Liu; Ning Zhao; Jinyun Guo; Yu Sun; Bin Guo; Naixia Mou. Equivalent water height changes over Qinghai-Tibet Plateau determined from GRACE with an independent component analysis approach. Arabian Journal of Geosciences 2020, 13, 1 -13.
AMA StyleXin Liu, Ning Zhao, Jinyun Guo, Yu Sun, Bin Guo, Naixia Mou. Equivalent water height changes over Qinghai-Tibet Plateau determined from GRACE with an independent component analysis approach. Arabian Journal of Geosciences. 2020; 13 (4):1-13.
Chicago/Turabian StyleXin Liu; Ning Zhao; Jinyun Guo; Yu Sun; Bin Guo; Naixia Mou. 2020. "Equivalent water height changes over Qinghai-Tibet Plateau determined from GRACE with an independent component analysis approach." Arabian Journal of Geosciences 13, no. 4: 1-13.
POI configuration of a region indicates a combination of POI counts on various types inside the region. Exploring POI configurations of urban regions facilitates to understand their functionalities, vibrancy, and developments. However, current studies and applications mainly make statistics toward POI counts on various types separately, neglecting the implicit semantic relations between different types and failing to uncover POI-configuration patterns intuitively. This study proposes a novel framework for visualizing and exploring POIs on POI-type semantic space, with semantic relations of the types being considered. Firstly, using a word-embedding technique (i.e., Word2Vec), the embeddings of POI types are learned from their neighborships on geographic space. Secondly, using a dimension-reduction technique (i.e., t-SNE), all POI-type embeddings are mapped onto 2-dimensional semantic space, where related or similar types would be nearer to each other. Finally, taking the POI-type semantic space as a “base map”, POI configuration of each region is rendered as a “thematic map” by POI counts on various types, which can help intuitively understand and conveniently compare urban regions. The proposed framework can be applied to any urban region and any POI data source, which provides an effective information delivery method for urban planning and POI related urban studies and applications.
Kang Liu; Ling Yin; Feng Lu; Naixia Mou. Visualizing and exploring POI configurations of urban regions on POI-type semantic space. Cities 2020, 99, 102610 .
AMA StyleKang Liu, Ling Yin, Feng Lu, Naixia Mou. Visualizing and exploring POI configurations of urban regions on POI-type semantic space. Cities. 2020; 99 ():102610.
Chicago/Turabian StyleKang Liu; Ling Yin; Feng Lu; Naixia Mou. 2020. "Visualizing and exploring POI configurations of urban regions on POI-type semantic space." Cities 99, no. : 102610.
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.
Knowledge on spatio-temporal changes of inbound tourism flow is important for destination economy, cultural communication and city image. This paper proposes a novel research framework for the spatio-temporal distribution and changes of inbound tourism flow by, first, using R-HDBSCAN clustering algorithm to extract tourism area of interest (AOI), second, by utilizing several key indicators adopted from the complex network theory literature to study the structure of inbound tourism flow with a case study example from Shanghai, China. The results show, first, that tourism in Shanghai is highly concentrated on the most popular AOI clustered in the city center relatively close to each other and, second, that, the inbound tourism flow network of Shanghai has small-world characteristics, while the distribution of its AOI (nodes) and tourist routes (edges) has general power law features, which has been influenced by the World Expo.
Naixia Mou; Rongzheng Yuan; Tengfei Yang; Hengcai Zhang; Jinwen(Jimmy) Tang; Teemu Makkonen. Exploring spatio-temporal changes of city inbound tourism flow: The case of Shanghai, China. Tourism Management 2019, 76, 103955 .
AMA StyleNaixia Mou, Rongzheng Yuan, Tengfei Yang, Hengcai Zhang, Jinwen(Jimmy) Tang, Teemu Makkonen. Exploring spatio-temporal changes of city inbound tourism flow: The case of Shanghai, China. Tourism Management. 2019; 76 ():103955.
Chicago/Turabian StyleNaixia Mou; Rongzheng Yuan; Tengfei Yang; Hengcai Zhang; Jinwen(Jimmy) Tang; Teemu Makkonen. 2019. "Exploring spatio-temporal changes of city inbound tourism flow: The case of Shanghai, China." Tourism Management 76, no. : 103955.
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.
China’s 21st Century Maritime Silk Road trade initiative includes investment in international port infrastructure. Comprehensive analysis of port competitiveness is of great significance for effectively guiding the flow of such resources. Conventional models mainly consider statistical indices for port operation, while neglecting the real operational status of these ports and their position in the changing global maritime transport network. To fill this gap in existing research, we designed a comprehensive evaluation CCPE model measuring port competitiveness by 18 factors related to conditions, capacity, potential, and efficiency using big data related to the geographical environment, cargo vessels trajectories, port infrastructure, and regional socioeconomics. This model was then used to evaluate the competitiveness of 99 ports in 51 countries along the Maritime Silk Road, with several important results. First, a port’s status in the global maritime transport network was the most influential of all competitiveness indices. Second, competitive ports were mainly concentrated in the Mediterranean, the Suez Canal, and the Hormuz Strait, with Singapore, Marsaxlokk, and Algeciras ranking as the top three. The least competitive ports were mainly concentrated in East Africa, with Rangoon, Berbera, Lamu, Songkhla, Mtwara, and Sittwe ranking lowest. Third, port competitiveness was clearly polarized in that the most competitive ports stood far above all others due to significant gaps in their network status index.
Peng Peng; Yu Yang; Feng Lu; Shifen Cheng; Naixia Mou; Ren Yang. Modelling the competitiveness of the ports along the Maritime Silk Road with big data. Transportation Research Part A: Policy and Practice 2018, 118, 852 -867.
AMA StylePeng Peng, Yu Yang, Feng Lu, Shifen Cheng, Naixia Mou, Ren Yang. Modelling the competitiveness of the ports along the Maritime Silk Road with big data. Transportation Research Part A: Policy and Practice. 2018; 118 ():852-867.
Chicago/Turabian StylePeng Peng; Yu Yang; Feng Lu; Shifen Cheng; Naixia Mou; Ren Yang. 2018. "Modelling the competitiveness of the ports along the Maritime Silk Road with big data." Transportation Research Part A: Policy and Practice 118, no. : 852-867.
Land use/cover change (LUCC) is one of the major factors influencing the storage of ecosystem carbon. The carbon storage in Qinghai-Tibet Plateau, the world’s highest plateau, is affected by a combination of many factors. Using MCD12Q1 land classification data, aboveground biomass, belowground biomass, soil carbon and humus carbon data, as well as field sampling data for parameters verification, we applied the InVEST model to simulate the ecosystem carbon storage and the impacts of driving factors. The field survey samples were used to test the regression accuracy, and the results confirmed that the model performance was reasonable and acceptable. The main conclusions of this study are as follows: From 2001 to 2010, carbon storage in the Qinghai-Tibet Plateau increased by 10.39 billion t when assuming that the carbon density in each land cover type was constant. Changes of the land cover types caused carbon storage to increase by 116 million t, which contributed 13.82% of the dynamic carbon storage. Consequently, changes in carbon density accounted for 86.18% of the carbon storage change. In addition, we investigated the soil organic matter and aboveground biomass characteristics between 2012 and 2014 and found that the influences of fencing and dung on carbon storage were positive.
Zhonghe Zhao; Gaohuan Liu; Naixia Mou; Yichun Xie; Zengrang Xu; Yong Li. Assessment of Carbon Storage and Its Influencing Factors in Qinghai-Tibet Plateau. Sustainability 2018, 10, 1864 .
AMA StyleZhonghe Zhao, Gaohuan Liu, Naixia Mou, Yichun Xie, Zengrang Xu, Yong Li. Assessment of Carbon Storage and Its Influencing Factors in Qinghai-Tibet Plateau. Sustainability. 2018; 10 (6):1864.
Chicago/Turabian StyleZhonghe Zhao; Gaohuan Liu; Naixia Mou; Yichun Xie; Zengrang Xu; Yong Li. 2018. "Assessment of Carbon Storage and Its Influencing Factors in Qinghai-Tibet Plateau." Sustainability 10, no. 6: 1864.