To better guide the sustainable developing of freight transport aligning with environmental objectives it is of strategic importance to capture freight transportation characteristics more realistically. This paper characterizes freight transportation by using a complex network approach from multidimensional perspectives based on freight vehicle trips data. We first build two subnetworks from prefecture-level city-scale and county-level city-scale. Subsequently, network analysis indices based on complex network theory were applied to examine the topological structure and complexity of the freight transportation networks. Furthermore, the community detection method is introduced to reveal the networks’ clustering characteristics. The findings show that the prefecture-level city-scale network and the county-level city-scale network both have obvious small-world network characteristics, but the prefecture-level city-scale network has higher operating efficiency for goods movement. Additionally, the influence of the cross-border effect on the freight transportation network was verified. In terms of the community structure, the freight network shows distinct clustering features only at the county-level city-scale.

Understanding the factors that contribute to traffic crashes can help provide a fundamental basis to plan and develop appropriate countermeasures for road safety issues emerging in particular on two-lane rural roads. However, most of the studies have focused on urban roadways and freeway systems, and few studies have investigated the issue of heterogeneity on two-lane rural roads. The purpose of this study is to uncover the risk factors influencing crash severity on two-lane rural roads in China. A sample of 1490 traffic crashes occurring on two-lane rural roads between 2012 and 2017 was collected from the Mouding County Highway Bureau in Yunnan, China. A random-parameter ordered probit model was estimated using these data to capture underlying unobserved characteristics in personal traits, vehicle attributes, roadway conditions, environmental factors, and crash attribute. To better understand the effect of critical factors on crash severity outcome probability, an elasticity analysis was then introduced. The results show that six factors such as driver’s attribution, illegal driving behaviour, access segment, day of week, vehicle type, and crash form have a significant impact on the injury severity, and the impacts of driving behaviours, access segment, and vehicle-fixed object crashes had significant variation across observations. Besides, the correlations between critical factors and the probability of serious injury sustained in traffic crashes are identified and discussed. The local driver indicator has more positive impact on the crash severity than nonlocal driver, and nonaccess segment appears a higher probability of serious or vicious collisions. It is worth mentioning that motorcycle-involved crashes do show an obvious correlation with crash injury severity. As for crash forms, vehicle-vehicle crashes are more likely to lead to severe crash injury. Besides, high-risk driving behaviour (e.g., fatigue driving, speeding, and converse driving), weekends, and holidays are found to have significant contribution to increasing the probability of traffic crash injuries and fatalities on two-lane rural roads.

Coordinated development between landside transport at civil airports and aviation networks is key for determining the attractiveness and competition of tourist cities. However, only a few studies have focused on the accessibility of tourist locations around civil airports in tourist cities in China. This paper calculates the service coverage of civil airports for tourist locations in Yunnan in selected years, consisting of 2000, 2005, 2010, and 2015, by using an accessibility calculation method with the shortest path and a spatial analysis method in ArcGIS software. The results are compared with the structural characteristics of the aviation network in corresponding years. Additionally, some suggestions are given regarding transportation development and sustainable environmental development in tourist cities. The findings show that the service coverage of civil airports in Yunnan has gradually improved over time. Specifically, 83.41% of tourist locations can be reached within 1.5 h of driving from an airport, and all tourist destinations could be reached within 3 h in 2015. Among all civil airports, the airports in the hub city of Kunming and at world-renowned tourist destinations such as Dali and Lijiang displayed the highest airport service capabilities for tourist locations. Meanwhile, the aviation network of Yunnan Province is constantly improving with an increased number of airports and airlines, and it shows the centralization trend toward KMG. However, the mismatch is observed not only in tourist cities with hub airports, such as Kunming, but also in some cities located in remote areas (i.e., far from the central city). This finding reveals that in these tourist cities in Yunnan, the development of airport transport has not considered coordination between the airline network and the service coverage of civil airports for tourist locations. For the sustainable development of tourist cities, the equal importance of airport landside transport and the airline network in the planning and management of air transport should be emphasized.

Change detection is a key step in various geographic information applications such as land cover change monitoring, agricultural assessment, natural disaster evaluation, and illegal building investigation. In practice, discovering, or outlining these changes is labour intensive and time-consuming. To address this problem, a novel end-to-end Siamese correlation-and-attention-based change detection network (SCA-CDNet) is proposed for bitemporal very-high-resolution images in this paper. In this method, five strategies are adopted to improve the final change detection results. First, data augmentation is used to reduce the overfitting effectively and improve the generalization ability of the training model. Second, in encoding, classic networks (e.g. ResNet) are introduced to extract the multiscale features of the image and make full use of the existing pretraining weights of the network to reduce the difficulty of subsequent model training. Third, a new correlation module is designed to stack the above bitemporal features correspondingly and extract change features with smaller dimensions. Fourth, an attention model is introduced between the correlation module and the decoder module to make the network pay more attention to areas or channels with a greater effect on change analysis. Fifth, a new weighted cross-entropy loss function is designed, which enables training to focus on error detection and improve the final accuracy of the training model. Finally, extensive experimental results on three public data sets including the evaluation of data augmentation, ablation study, and comparison with the state of the art demonstrate the effectiveness and superiority of our proposed method, achieving an intersection of union (IoU) of 84.15%, 83.50%, and 77.29% on the three data sets, respectively.

In this paper, the bilevel programming model of the public transport network considering factors such as the per capita occupancy area and travel cost of different groups was established, to alleviate the urban transportation equity and optimize the urban public transport network under fairness constraints. The upper layer minimized the travel cost deprivation coefficient and the road area Gini coefficient as the objective function, to solve the optimization scheme of public transport network considering fairness constraints; the lower layer was a stochastic equilibrium traffic assignment model of multimode and multiuser, used to describe the complex selection behavior of different groups for different traffic modes in the bus optimization scheme given by the upper layer. The model in addition utilised the noninferior sorting genetic algorithm II to validate the model via a simple network. The results showed that (1) the travel cost deprivation coefficient of the three groups declined from 33.42 to 26.51, with a decrease of 20.68%; the Gini coefficient of the road area declined from 0.248 to 0.030, with a decrease of 87.76%; it could be seen that the transportation equity feeling of low-income groups and objective resource allocation improved significantly; (2) before the optimization of public transport network, the sharing rate of cars, buses, and bicycles was 42%, 47%, and 11%, respectively; after the optimization, the sharing rate of each mode was 7%, 82%, and 11%, respectively. Some of the high and middle income users who owned the car were transferred to the public transportation. It could be seen that the overall travel time of the optimized public transport network reduced, enhancing the attraction of the public transport network to various travel groups. The model improves the fairness of the urban public transport system effectively while ensuring the travel demand of the residents. It provides theoretical basis and model foundation for the optimization of public transit network, and it is a new attempt to improve the fairness of the traffic planning scheme.

Transportation infrastructure has a positive impact on freight transportation activities when it has excellent economic and social performances. At the current stage of economic development in China, sustainable development of the region is facing the imbalance of transport supply and transport demand. With the growing flow of freight transportation, it is essential to explore the relationship between freight transportation activity and transport infrastructure, which helps to guarantee that the development of transport infrastructure matches freight transportation demand growth. In contrast to the existing literature, this study describes freight transportation activities as a network. The degree, and freight degree of the freight transportation network (FTN) and development level of the transport infrastructure were first analyzed considering intercity freight flow. Then, the coupling relationship between them was tested using a coupling coordination degree model (CCDM) focusing on the hysteresis status, and the link strength model was established to further reveal the causal mechanisms behind the coupling relationship. The results revealed that the interaction between freight transportation activities and transport infrastructure development was significant, and there was a relatively coordinated relationship between freight transportation activities and transport infrastructure overall. The contribution of freight transportation activities to transport infrastructure development was less than the contribution of transport infrastructure development to freight transportation activities in most cities of Yunnan, which ultimately causes the advanced development in transport infrastructure and freight transportation activities to become the key factor to promote the coordinated development of Yunnan's transport. In addition, we found that a good coupling coordination degree existed in cities with increased freight transportation activities and high transport infrastructure development, as well as in cities with less active freight transportation activities and a low level of transport infrastructure development. From the perspective of coordinated development, the results indicated that without planning a large number of transport facilities devoted to an increase in transport infrastructure construction might not necessarily be good for its development