Highway Density Research Articles

Spatial patterns and its influencing factors on villages around the Ji-shape bend of the Yellow River

Population migration brings about many problems in villages. The Ji (几)-shape bend of the Yellow River is an important ecological sensitivity study area, and some progress exists in the study of villages, still has many problems. This article addresses the inadequacy of the existing research and mainly solves the problems in three areas. It primarily used the research method of Arc GIS10.8, the big data research methods such as imbalance index, Gini coefficient, geographic concentration index, Geodetector, and other methods were used, laying the groundwork for additional analysis of various factors. Hence, the subsequent study findings were attained. 1) The distribution pattern in the village system around the Ji-shape bend of the Yellow River seems to be a positive spatial correlation, with the characteristics of random distribution, uneven spatial distribution, and low concentration, with Hohhot-Baotou serving as a center. 2) Natural factors are the most important factors in the distribution of villages. 3) Among the natural factors, elevation (0.244619), the value of slope (0.319805), and the aspect of slope (0.074089) appear to be the strongest explanatory power. Among the social factors, the rate of urbanization (0.019082), highway density (0.019082), and percentage of tertiary industry (0.018422) show the strongest explanatory power on socioeconomic factors. The natural and social characteristics of villages are important for the siting of villages. This paper put forward some suggestions for the protection and development of villages in ecologically sensitive areas.

Актуализация подходов к исследованию неоднородности экономического пространства

The article distinguishes the categories of “heterogeneity of economic space” and “interregional social differentiation”, as well as the ways of their assessment. On the basis of the theories of new economic geography and center-periphery theory, the nature of spatial heterogeneity is revealed. The heterogeneity of Russia’s economic space is analyzed through the prism of two key properties of space, i.e., density and connectivity. It is shown that the spatial heterogeneity in terms of population density is growing against the background of decreasing differentiation of space in terms of economic density, measured as GRP per 1 km 2 and volume of investment in fixed capital per 1 km 2 , which can be explained by the fact that the economy is in a phase of recession. A positive correlation between population density and highway density is revealed, which can be explained by the discreteness of space. Based on empirical data, the authors conclude that communicative compression of economic space is characteristic of regions with high population density and economic density and regions with extremely low population density and transport connectivity. In the first case, it is evidence of high business activity in the territory, while in the second case it is a way to increase the availability of services. Based on the comparison of population density and economic density of space, four types of territories were identified: territories of spatial compression; territories with growing population density against the background of high economic density of space; and territories characterized by high population density with relatively low density of economic space; territories with relatively low population density and a trend for its further reduction against the background of high economic density of space. The priorities of spatial development are defined for each type of territory.

ASSOCIATING HIGHWAY DENSITY WITH ASTHMA: UNRAVELING THE LINK BETWEEN TRAFFIC-RELATED POLLUTION AND HEALTH IN U.S. NON-CALIFORNIA METROPOLITAN AREAS

This study delves into the influence of traffic-related pollution on respiratory diseases within the United States. While prior research has established a connection between air pollution and mortality or morbidity in sensitive age groups, this association has been predominantly observed in highly polluted areas, particularly in California. In this paper, we extend this line of investigation by examining adult patients with asthma symptoms across various metropolitan areas throughout the country. To address potential endogeneity concerns in our empirical framework, we adopt highway density as an instrumental variable (IV) for NO2 concentrations. This approach allows us to gain a more robust understanding of the relationship between traffic-related pollution and respiratory health outcomes. Our findings indicate that NO2 does not have a significant impact on patients with asthma symptoms in the overall sample. However, we observed that it can exacerbate asthma conditions in patients residing in warm areas. A back-of-the-envelope calculation estimates a $6.758 billion economic loss due to increasing asthma attack on adults in the selected study area. This regional disparity outside of California underscores the necessity for adjusting current regulations on vehicle emissions based on unique regional characteristics. Such adjustments could help mitigate adverse health effects associated with traffic-related pollution in different parts of the United States.

Investigating built environment and traffic flow impact on crash frequency in urban road networks

While numerous studies have examined the factors that influence crash occurrence, there remains a gap in understanding the intricate relationship between built environment, traffic flow, and crash occurrences across different spatial units. This study explores how built environment attributes, and dynamic traffic flow characteristics affect crash frequency by focusing on proposed traffic density-based zones (TDZs). Utilizing a comprehensive dataset from Greater Melbourne, Australia, this research emphasizes on the dynamic traffic flow variables and insights from the Macroscopic Fundamental Diagram model, considering parameters such as shockwave velocity and congestion index. The association between the potential influencing factors and crash frequency is examined using a random parameter negative binomial regression model. Results indicate that the data segmentation based on TDZs is instrumental in establishing a more refined crash model compared to traditional planning-based zones, as demonstrated by improved goodness-of-fit measures. Factors including density (e.g., employment density), network design (e.g., road density and highway density), land use diversity (e.g., job-housing balance and land use mixture), and public transit accessibility (e.g., bus route density) are significantly associated with crash occurrence. Furthermore, the unobserved heterogeneity effects of the shockwave velocity and congestion index on crashes are revealed. The study highlights the significance of incorporating dynamic traffic flow variables in understanding crash frequency variations across different spatial units. These findings can inform optimal real-time traffic monitoring, environmental design, and road safety management strategies to mitigate crash risks.

Spatial-temporal characteristics and influencing factors of carbon emission in Chengdu-Chongqing area: an urban transportation perspective.

The Chengdu-Chongqing twin-city economic circle is a vital growth pole and a new power source for Chinese high-quality development. Studying the spatial-temporal characteristics of carbon emissions and the role of factors affecting them under the transportation perspective is of great significance for this region to realize the carbon peak and carbon neutrality and to formulate carbon emission reduction policies. We use the exploring spatial data analysis (ESDA) and spatial regression model combined with the STIRPAT model, and research finding: (1) The total carbon emissions in the research area gradually increased from 2014 to 2020, but the growth rate showed a significant decline in 2019. (2) There is significant spatial heterogeneity of carbon emissions in the study area; the hotspot areas of total carbon emissions are in Chongqing and Chengdu, forming a high-low aggregation of carbon emissions. Per capita carbon emissions show a high trend in the southwest and a low in the northeast. (3) From the factors of transportation perspective, highway density and private vehicles have a positive impact on carbon emissions, and urban road areas and public transportation have a very significant inhibition of carbon emissions and a spatial spillover effect. (4) Other factors, such as population size, national economic development, urbanization level, and industrial structure, all have a positive effect on carbon emissions, and disposable income has a negative effect on carbon emissions.

Impact assessment of construction waste policy intensity on environmental efficiency based on system generalized method of moments

With the acceleration of urbanization in recent years, China has witnessed large-scale construction across its provinces, generating massive amounts of construction waste that pose challenges to environmental protection and sustainable development. This study evaluated the impact of construction waste policy intensity on its environmental efficiency. Firstly, the content analysis method was used to analyze the construction waste policy text quantitatively. Second, this study constructed a slack-based measure (SBM) model based on data envelopment analysis (DEA), considering resource input and construction waste output to measure environmental efficiency. Finally, we built and tested an econometric model of how policies affect environmental efficiency using the system generalized method of moments (SYS-GMM). The findings indicate a non-linear U-shaped link between policy intensity and environmental efficiency. Among all five control variables, population density, urbanization level, and technological innovation enhance environmental efficiency, while economic development and highway density will lower it. This study advances the research on construction waste policies and offers some insights for the construction industry to pursue sustainable development.

Оценка транспортной связности Европейского Севера России

Transport connectivity has been and remains one of the key endogenous factors in the socioeconomic development of the Russian Federation. At the same time, in relation to the northern regions of Russia, connectivity is a factor not so much in terms of development as retention and preservation of the development of their territories, which is strategically important for the country due to the existing natural resource potential. The article analyzes the trends in the development of the transport system of the European North of Russia based on official statistics. As a result, its strengths have been identified, including the presence of all types of transport and related infrastructure on the territory, international transport corridors, etc., as well as its weaknesses, including a low density of highways, a high degree of depreciation of fixed assets, etc. The assessment of the transport connectivity of the largest settlement nodes in the European North has been carried out. As a result, it was found that the existing configurations of road and rail networks between them are significantly inferior to “ideal” options. Thus, the routes within the automobile network are about 51% longer than the shortest possible ones, and the railway is 1.7 times longer. It is shown that weak transport connectivity is a consequence not only of natural limitations but also of the weak efficiency of mechanisms for the development of the transport system.

The role of vaccination and environmental factors on outbreaks of high pathogenicity avian influenza H5N1 in Bangladesh

High Pathogenicity Avian Influenza (HPAI) H5N1 outbreaks continue to wreak havoc on the global poultry industry and threaten the health of wild bird populations, with sporadic spillover in humans and other mammals, resulting in widespread calls to vaccinate poultry. Bangladesh has been vaccinating poultry since 2012, presenting a prime opportunity to study the effects of vaccination on HPAI H5N1circulation in both poultry and wild birds. We investigated the efficacy of vaccinating commercial poultry against HPAI H5N1 along with climatic and socio-economic factors considered potential drivers of HPAI H5N1 outbreak risk in Bangladesh. Using a multivariate modeling approach, we estimated that the rate of outbreaks was 18 times higher before compared to after vaccination, with winter months having a three times higher chance of outbreaks than summer months. Variables resulting in small but significant increases in outbreak rate were relatively low ambient temperatures for the time of year, literacy rate, chicken and duck density, crop density, and presence of highways; this may be attributable to low temperatures supporting viral survival outside the host, higher literacy driving reporting rate, density of the host reservoir, and spread of the virus through increased connectivity. Despite the substantial impact of vaccination on outbreaks, we note that HPAI H5N1 is still enzootic in Bangladesh; vaccinated poultry flocks have high rates of H5N1 prevalence, and spillover to wild birds has increased. Vaccination in Bangladesh thus bears the risk of supporting “silent spread,” where the vaccine only provides protection against disease and not also infection. Our findings underscore that poultry vaccination can be part of holistic HPAI mitigation strategies when accompanied by monitoring to avoid silent spread.

Spatial Distribution and Influencing Factors of Traditional Villages in Inner Mongolia Autonomous Region

This paper takes 207 traditional villages in Inner Mongolia as the research object and uses the ArcGIS10.7 software platform, using the nearest neighbor index, coefficient of variation analysis, spatial autocorrelation analysis, imbalance index, kernel density estimation method, geographical detector, and other methods to explore the spatial distribution characteristics and influencing factors of traditional villages in Inner Mongolia. The research shows that: (1) the spatial distribution of traditional villages in Inner Mongolia is condensed; the distribution of cities is uneven; and the overall distribution pattern of ‘two main and two vice’ is presented. (2) The traditional villages are mainly distributed in the altitude area of 500–1500 m, and their spatial distribution characteristics are positively correlated with the annual average temperature, annual precipitation, total population, the proportion of the primary industry, and the number of intangible cultural heritage, and negatively correlated with the slope, river distance, highway density, per capita GDP, urbanization, and the proportion of the secondary industry. (3) The results of GeoDetector2018 software show that socio-economic factors are the primary factors affecting the spatial distribution of traditional villages in Inner Mongolia, followed by natural geographical factors. The interaction and synergy between the influencing factors have increased significantly, which jointly affects the spatial pattern of the distribution of traditional villages in Inner Mongolia. The purpose of the study is to provide reference for the protection and development of traditional villages in Inner Mongolia and the implementation of the national rural revitalization strategy.

The Spatial Distribution and Impacts of Organic Certificates in Southwest China

Organic farming is a good choice for agricultural development in southwest China under the trade-off between environmental protection and agricultural development. However, no researcher has investigated the current state and development of organic agriculture in southwest China. As a result, this paper explored the spatial structure of organic agriculture in southwest China by examining the distribution of organic certificates, as well as the environmental and socioeconomic impacts. The results show a dramatically uneven distribution of certified organics among different provinces, cities, and organic certificate types. On the province scale, Guizhou has the highest number (1174) and density (73.40 per 1010 m2) of organic certificates. On the city scale, Zunyi and Chengdu have the highest densities (218.77 and 342.52 per 1010 m2, respectively). Most of the certified organics are plants, accounting for 76.95%. The spatial distribution of organic farming is influenced by the interaction of several factors, including precipitation, temperature, GDP, highway density, gross agriculture output, agriculture machinery, and rural employed persons. However, the related and determinant factors of organic certificate distribution vary greatly across different regions, spatial scales, economic development levels, and agricultural development statuses. For the entirety of southwestern China, the factors significantly related to the distribution of organic certificates are GDP, highway density, gross agriculture output, agriculture machinery, and rural employed persons. However, these factors are GDP, gross agriculture output, agriculture machinery, and rural employed persons for Sichuan, and gross agriculture output and rural employed persons for Guizhou. Factors constraining the development of organic agriculture in regions with better economic and agricultural conditions are much fewer than in poorer regions. All of the nine selected variables, except global radiation, are significantly related to organic certificate distribution in regions with better economic conditions, while none of them had a significant correlation with organic certificate distribution in poorer regions. Furthermore, climate is no longer a constraint in regions with better agricultural conditions. These findings are of great significance for the development and research of organic agriculture in southwest China. The development of organic agriculture in southwest China requires consideration of both the combination of multiple factors and the stage of regional economic and agricultural development.

Conversion of a military vessel into a civilian refrigerated vessel

River transport is one of the oldest in the Russian Federation. It is of particular importance for the northern and eastern regions, where the density of railways and highways is not high enough, or they do not exist at all. In these regions, the share of river transport in the total cargo turnover is about four percent. The use of river water transport for military purposes will never be stopped. Since requirements that are more stringent are imposed on military transport, the decommissioning of these vessels is faster than in commercial use. In most cases, the technical condition of the vessel is not critical, and it can be further operated. In view of the fact that recycling is a rather expensive process, ships are idle and are not used for their intended purpose. The way out of this situation can be the use of decommissioned military vessels for commercial purposes by converting them into a refrigerator in order to extend the operational life of the vessel, improve the technical and economic indicators of the vessel and make a profit. From the point of view of the methodological approach, the analysis of existing refrigerated containers was carried out, additional devices for converting electricity were given, the technological process of manufacturing the frame of the refrigerator installation was developed, and its strength calculation was carried out. The economic feasibility of converting the vessel into a refrigerator is shown.

Tourist Attractions and Economic Growth in China: A Difference-in-Differences Analysis

The construction of tourist attractions has become an important manifestation of local performance and the image of tourist destinations, as well as an important means for local governments to promote economic development. However, the causal relationship between tourist attractions and economic growth remains unclear. The article’s main purpose is to explore the causal effect of tourist attractions on economic growth. To do so, a difference-in-differences model is employed based on China’s city-level panel data from 2001 to 2019 involving 313 cities and 5947 observations. The results demonstrate that tourist attractions have a significant positive causal effect on China’s economic growth. Such causality is significant only in the east and central regions. Highway density, urban disposable income per capita, and the share of the tertiary industry have significant moderating effects. The validity of the causal relationship is confirmed using various rigorous robustness tests.

Spatial Pattern Evolution and Influencing Factors of Tourism Flow in the Chengdu–Chongqing Economic Circle in China

Based on Ctrip’s ‘tourism digital footprint’, the spatial pattern of tourism flows in the Chengdu–Chongqing Economic Circle from 2018 to 2021 is explored, social network analysis and spatial visualisation of tourism information data are conducted, and factors affecting the network structure of tourism flows are analysed using linear weighted regression methods. The results show that tourism flows in the Chengdu–Chongqing Economic Circle show a significant ‘dual core’ polarisation effect. At the end of 2019, as a turning point, the density value of the tourism flow network shows an irregular inverted ‘U’ distribution. Kuanzhai Alley, Hong Ya Dong and Chunxi Road have irreplaceable competitive advantages in the tourism flow network. The density of highways, the number of star-rated hotels and the regional GDP per capita are positively correlated with the effective size of the structural hole of the administrative unit. Finally, based on the research results, countermeasures are proposed to optimise the tourism development of the Chengdu–Chongqing Economic Circle.

Modeling rules of regional flash flood susceptibility prediction using different machine learning models

The prediction performance of several machine learning models for regional flash flood susceptibility is characterized by variability and regionality. Four typical machine learning models, including multilayer perceptron (MLP), logistic regression (LR), support vector machine (SVM), and random forest (RF), are proposed to carry out flash flood susceptibility modeling in order to investigate the modeling rules of different machine learning models in predicting flash flood susceptibility. The original data of 14 environmental factors, such as elevation, slope, aspect, gully density, and highway density, are chosen as input variables for the MLP, LR, SVM, and RF models in order to estimate and map the distribution of the flash flood susceptibility index in Longnan County, Jiangxi Province, China. Finally, the prediction performance of various models and modeling rules is evaluated using the ROC curve and the susceptibility index distribution features. The findings show that: 1) Machine learning models can accurately assess the region’s vulnerability to flash floods. The MLP, LR, SVM, and RF models all predict susceptibility very well. 2) The MLP (AUC=0.973, MV=0.1017, SD=0.2627) model has the best prediction performance for flash flood susceptibility, followed by the SVM (AUC=0.964, MV=0.1090, SD=0.2561) and RF (AUC=0.975, MV=0.2041, SD=0.1943) models, and the LR (AUC=0.882, MV=0.2613, SD=0.2913) model. 3) To a large extent, environmental factors such as elevation, gully density, and population density influence flash flood susceptibility.

Assessment of Urban Flood Vulnerability Using the Integrated Framework and Process Analysis: A Case from Nanjing, China

Flooding is a serious challenge that increasingly affects residents as well as policymakers. Many studies have noted that decreasing the urban flood vulnerability (UFV) is an indispensable strategy for reducing flood risks; however, some studies have several pertinent assessment limitations. The objective of this study is to assess the UFV of the Xuanwu-Qinhuai-Jianye-Gulou-Yuhua (XQJGY) region from 2012 to 2018 by integrating various indicators into a composite index. This study uses the environment for visualizing images (ENVI) and the geographic information system (GIS) to extract indicators that have geographic attributes for the assessment of UFV and the process analysis method is then used to explore the relationship between these indicators. The results indicated that: (1) The UFV of Xuanwu, Qinhuai, and Gulou decreased from 2012 to 2018 and the UFV of Jianye and Gulou increased from 2012 to 2015 and decreased from 2015 to 2018. (2) The vegetation coverage, precipitation during the flood season, population density, and highway density significantly contributed to the UFV. (3) There also exist transformation pathways between the indicators that led to vulnerability in five districts. This study provides a theoretical basis for the government to manage floods.

Climatic Variability Caused by Topographic Barrier Prevents the Northward Spread of Invasive Ageratina adenophora.

Ageratina adenophora (Spreng.) R.M.King & H.Rob. is one of the most threatening invasive alien plants in China. Since its initial invasion into Yunnan in the 1940s, it spread rapidly northward to southern Mount Nyba in Sichuan, which lies on the eastern edge of the Qinghai-Tibet Plateau. During fieldwork, we found an interesting phenomenon: A. adenophora failed to expand northward across Mount Nyba, even after the opening of the 10 km tunnel, which could have served as a potential corridor for its spread. In this work, to explore the key factors influencing its distribution and spread patterns, we used a combination of ensemble species distribution models with the MigClim model. We found that the temperature annual range (TAR), precipitation of driest month (PDM), highway density (HW), and wind speed (WS) were the most predominant factors affecting its distribution. The north of Mount Nyba is not suitable for A. adenophora survival due to higher TAR. The spatial-temporal dynamic invasion simulation using MigClim further illustrated that the northward invasion of A. adenophora was stopped by Mount Nyba. Overall, Mount Nyba may act as a topographic barrier that causes environmental differences between its south and north sides, preventing the northward invasion of A. adenophora. However, other suitable habitats on the northern side of the mountain still face challenges because A. adenophora is likely to invade via other routes. Therefore, long-term monitoring is needed to prevent human-induced long-distance spread events.

Quantifying the photovoltaic potential of highways in China

Installing photovoltaic (PV) modules on highways is considered a promising way to support carbon neutrality in China. However, collecting the area of the highway, and precisely assessing the shadow area of the highway under complex terrain remain challenges. That severely hinders the assessment of highway PV potential.To address these challenges, a spatiotemporal model is developed in this study to estimate the annual solar PV potential on highways over the whole Chinese territory.First, the areas of different highway segments are calculated based on highway network and highway toll stations. Second, hourly shadow area on highways created by nearby terrain is estimated based on a digital elevation model (DEM). When calculating the highway PV potential, the solar irradiation received in these shadow areas is regarded as zero. Finally, the PV potential of all lanes and emergency lanes was estimated at the prefecture-level city scale using surface radiation data and radiation assessment models. Based on the highway data with a total mileage of 143,684 km at the end of 2020, the results show that the annual PV potential is 3,932 TW and that the corresponding installed capacity is 700.85 GW, which can generate clean electricity at a rate of up to 629.06 TWh. The annual PV potential of highways in the southeast is greater than that in the northwest owing to the higher highway density in the southeast. This study provides a reference basis for highway PV construction planning and suitably assessment in each region of China for PV highway development.

The characteristics and influencing factors of the spatial distribution of intangible cultural heritage in the Yellow River Basin of China

This paper explores the characteristics and influencing factors of the spatial distribution of 889 national intangible cultural heritage sites in the Yellow River basin of China based on ArcGIS spatial analysis and Geodetector. The results show that the distribution of national intangible cultural heritage sites in the Yellow River basin is significantly different among provinces, and most of them are distributed in the central and western regions. From east to west, the density of intangible heritage in the Yellow River basin presents a triangular "one area and three points" pattern. All kinds of intangible cultural heritage in the Yellow River basin generally show the characteristic of aggregated distribution.Traditional skills, traditional medicine, traditional theatre, traditional music, and folklore have high levels of agglomeration, and traditional dance, Quyi, folk literature, and traditional fine arts have lower levels. The levels of traditional sports, entertainment and acrobatics have the lowest agglomeration. Among social and humanistic factors, highway density is the most influential indicator for the spatial distribution of national intangible cultural heritage in the Yellow River basin. GDP, population density and the urbanization level also have a great impact on the spatial distribution of national intangible cultural heritage in the Yellow River basin. Among geographical environmental factors, the river system and topography have a certain effect on the spatial distribution of national intangible cultural heritage in the Yellow River basin. Based on these facts, this paper finally discusses the specific path to protect and develop intangible cultural heritage in the Yellow River basin in the context of the newerato promote its creative protection and innovative development.

Evaluation of industrial development quality and analysis of influencing factors in Xi'an, China.

Industry is the lifeblood of the national economy, and it is the inevitable course of sustainability for China to promote the high-quality development of industry. A theoretical framework of industrial development quality (IDQ) was constructed, and 32 influencing factors were selected based on complex system theory. The IDQ in Xi'an from 2004 to 2019 was evaluated, and the influencing mechanisms of each IDQ factor were analyzed through an integrated maximum generalized information entropy (MGIE)-self-organizing feature mapping (SOFM) neural network-decision-making trial and evaluation laboratory (DEMATEL)-interpretive structural modeling (ISM) approach. The results show that the IDQ in Xi'an is on the rise, but the development of internal subsystems is uneven, with the technology subsystem contributing the most and the social subsystem contributing the least. There is a multi-layer hierarchical structure among the influencing factors of IDQ, and the multi-layer structure model can be divided into 10 layers. The first layer is the investment intensity of industrial pollution control, which is the most direct factor that affects IDQ. The tenth layer is the industrial wastewater discharge intensity, industrial waste gas emission intensity, water consumption per unit of industrial added value, highway density, and energy consumption per unit of industrial added value, which are the root factors affecting IDQ. This study can provide a theoretical basis and reference for the promotion of high-quality industrial development.

Integration Level and Influencing Factors’ Analysis of Forest Product Market Based on the Mathematical Model

This paper uses Python programming to improve the existing price index method and calculate the integration level of the forest products market in China. Based on the model, the influencing factors of domestic forest product market integration were examined empirically. The results show that the integration degree of the forest product market in recent years lags behind the average level in China. In this paper, the improvement of the existing price index method can calculate the level of market integration more quickly and accurately, and this improvement has obvious advantages in the case of a large amount of data. In terms of development, the overall pattern shows an increasing trend, and the eastern, central, and western provinces are gradually converging, although the differences between provinces continue to expand. In terms of influencing factors, the coefficient of the local government’s emphasis on forestry, the prosperity of international trade in forest products, and highway density were significantly positive factors, while the number of foreign investors and the railway density had no significant effects. In this paper, the optimization of the measurement method of market integration makes it easier for scholars to obtain the data on the level of market integration and promote in-depth research in the field of market integration.