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Urban spatial form influences the social, economic, and ecological development modes of the city. The spatial form during the urbanization of Hanjiang River Basin in Southern Shaanxi needs to be studied. In this study, research methodologies on urban spatial form in China and abroad were summarized. The concept of ecology background was applied, and the research framework for urban spatial form, which integrated the background, framework, core, axis, cluster, and skin, was established. Valley cities in the Hanjiang River Basin in Southern Shaanxi were classified into wide valley, narrow valley, and canyon cities. The spatial form characteristics of these three types of valley cities were discussed. A case study based on a typical city-Yang County-was conducted to discuss the characteristics of the aforementioned six elements of urban spatial form. Finally, spatial form characteristics were summarized. These characteristics provide a basis for the study of the small valley urban spatial form in the Hanjiang River Basin in Southern Shaanxi.

This paper explores whether the Euro-area sovereign credit default swap market is prone to contagion effects. It investigates whether the sharp increase in sovereign CDS spread of a given country is due to a deterioration of the macroeconomic variables or some form of contagion.

For this purpose, the authors use an innovative approach, i.e. spatial econometrics. Although modeling spatial dependence is an attractive challenge, its application in the field of finance remains limited.

The empirical findings show strong evidence of spatial dependence highlighting the presence of pure contagion. Furthermore, evidence of wake-up call contagion-increased sensitivity of investors to fundamentals of neighboring countries and shift contagion-increased sensitivity to common factors are well recorded.

This study aims to study a crucial financial issue that gained increased research interest, i.e. financial contagion. A methodological contribution is made by extending the standard spatial Durbin model (SDM) to analyze and differentiate between several forms of contagion. The results can be used to understand how shocks are spreading through countries.

Stock markets are highly sensitive to foreign and domestic events. Stock exchange markets react promptly to news and are known as an indicator of good and bad trading conditions. Terrorist attacks leave adverse effects on the economy and cause stock price volatility and, consequently, stock return volatility. Therefore, this paper aims to analyze the spatial effects of terrorism on stock market returns in the Middle East from 2008 to 2019.

This paper uses analytical research design and estimates spatial model. Before estimating the spatial model, the spillover effects were confirmed for the spatial autoregressive model using Moran’s diagnostic test for spatial dependence, Geary’s C test and Akaike statistic.

The results of this study on spatial panel data and based on spatial autoregressive estimator indicated that terrorism and associated neighborhood effects had a negative impact on stock returns in Middle East countries. Also, the corruption index and oil price negatively affected stock market return in these countries, while the democracy index had a positive effect on stock market returns. According to the results, to achieve a high and stable stock market return, it is recommended that high-level consultation is pursued with leaders of involved countries to reduce the devastating effects of terrorist activities, increase political and economic stability, attract stockholders to stock markets and spend corresponding incomes developing the infrastructures in this sector in countries of this region.

Most of the studies have investigated the impact of terrorism on the stock market returns at the national or provincial level. However, the effect of terrorism on the stock market index in the tense region of the Middle East, which is the center of terrorist attacks in the world, has not been dealt with by considering the spatial econometric effects. Thus, to the best of the authors’ knowledge, this research is a first attempt to study the impact of terrorism on the stock market returns in Middle East countries using the spatial econometric approach.

This study aims to construct a two-step model to examine how passive (mental imagery and immersion) and active (engagement) responses build a spatial presence in 360° virtual tours by constructing the spatial situation. This study further tests the difference between first-time and repeat users in building a spatial presence.

Systematic sampling was applied to collect data. Valid data from 355 participants were analysed using partial least squares structural equation modelling.

The results show that other than the direct effect of engagement on spatial presence, the spatial situation partially mediates the effects on the spatial presence of two passive responses. Through comparative analysis of the three models, this study confirms that the two-step model provides a better fit for the data. For repeat users, the spatial situation is the major source of spatial presence.

The results offer suggestions for destination marketers to develop effective virtual tours to induce the spatial presence of repeat users and first users.

This study contributes a two-step model for researchers to consider the mediating role of the spatial situation in further studies in the context of virtual reality (VR) tourism. This study also helps researchers design their future VR research in tourism by elucidating the roles of passive and active psychological responses in determining spatial presence.

该研究构建了一个两步模型, 以检查被动（心理意象和沉浸）和主动（参与）反应如何通过构建空间情境在 360° 虚拟旅游中构建空间存在。 这项研究进一步测试了初次使用者和重复使用者在建立空间呈现感方面的差异。

本研究应用系统抽样来收集数据。 使用 PLS-SEM 分析了来自 355 名参与者的有效数据。

结果表明, 除了参与对空间存在的直接影响外, 空间情况部分地调节了两种被动反应对空间存在的影响。 通过对三种模型的比较分析, 本研究证实了两步模型可以提供更好的数据拟合。 对于重复用户来说, 空间情境是空间呈现感的主要来源。

研究发现为目的地营销人员提供了建议, 以开发有效的虚拟旅游从而诱导重复用户和首次用户的空间呈现。

本研究为研究人员提供了一个两步模型, 以考虑空间状况在 VR 旅游背景下的进一步研究中的中介作用。 这项研究还通过阐明被动和主动心理反应在确定空间呈现中的作用, 帮助研究人员设计他们未来的旅游 VR 研究。

Traffic flow prediction has always been a top priority of intelligent transportation systems. There are many mature methods for short-term traffic flow prediction. However, the existing methods are often insufficient in capturing long-term spatial-temporal dependencies. To predict long-term dependencies more accurately, in this paper, a new and more effective traffic flow prediction model is proposed.

This paper proposes a new and more effective traffic flow prediction model, named channel attention-based spatial-temporal graph neural networks. A graph convolutional network is used to extract local spatial-temporal correlations, a channel attention mechanism is used to enhance the influence of nearby spatial-temporal dependencies on decision-making and a transformer mechanism is used to capture long-term dependencies.

The proposed model is applied to two common highway datasets: METR-LA collected in Los Angeles and PEMS-BAY collected in the California Bay Area. This model outperforms the other five in terms of performance on three performance metrics a popular model.

(1) Based on the spatial-temporal synchronization graph convolution module, a spatial-temporal channel attention module is designed to increase the influence of proximity dependence on decision-making by enhancing or suppressing different channels. (2) To better capture long-term dependencies, the transformer module is introduced.

By discussing the spatial spillover effect and regional heterogeneity of digital economy and green agricultural development level, this paper aims to provide countermeasures and suggestions for the better development of green agriculture in the contemporary era when digital economy is universally developed and at the same time provide development suggestions suitable for green agriculture's development characteristics and initial conditions for different regions.

This paper discusses the theoretical foundation of the digital economy and green agriculture development and utilizes panel data from 30 provinces in China from 2011 to 2018. By employing the Super-Efficiency Slack-based Measure and Malmquist-Luenberger (SBM-ML) model based on unexpected output to measure the total factor productivity of green agriculture and employing the spatial panel Durbin model to empirically test the spatiotemporal effects of the digital economy on green agriculture development from both temporal and spatial dimensions. Finally, the model is tested for robustness as well as heterogeneity.

The research findings are as follows: First, from the perspective of time effect, digital economy has a continuous driving effect on the development of green agriculture and with the passage of time, this effect becomes more and more prominent; second, from the perspective of spatial effect, digital economy has a significant positive impact on the development of local green agriculture, while digital economy has a significant negative impact on the development of surrounding green agriculture. Finally, the impact of digital economy on the development of green agriculture shows significant differences in different dimensions and regions.

As an important driver of economic growth, the digital economy has injected new impetus into agricultural and rural development. Along with the intensifying environmental pollution problems, how to influence the green development of agriculture through the digital economy is a proposition worthy of attention nowadays. This paper analyzes the relationship between the digital economy and agricultural green development in multiple dimensions by exploring the temporal and spatial spillover effects of the digital economy on agricultural green development, as well as the heterogeneity in different dimensions and in different regions and derives policy insights accordingly in order to improve relevant policies.

Spatial planning is globally identified as an effective strategy for providing climate change adaptation needs. However, there is a dearth of literature on how spatial planning relates to climate change control in Ghana, particularly at the local level. Hence, this paper aims to investigate whether spatial planning plays a significant role in the control of climate change and the adaptive capacities at the local level.

The authors adopt a mixed-method approach, where both qualitative and quantitative data were obtained using an interview guide and survey, respectively. The authors analyze the data using a qualitative content analysis method and descriptive statistics.

The results show that spatial planning plays an important role in climate change adaptation, though in a limited way. The physical planning department at the municipal level has varying amounts of capacities across various determinants, but there are opportunities for improving the capacity of the department.

The authors provide empirical evidence to support the need to prioritize spatial planning as a strategy for dealing with the impacts of climate change and the building of capacities at the national and community levels for improved adaptive capacity.

This study discusses that the necessary criteria and the solution approach taken to resolve the main spatial infection problems with a burn center design should be evaluated holistically to achieve spatial infection control in a burn center. The burn center design plays an important role in protecting severely burned patients from infection because the microbial flora of the hospital can affect the infection risk. In hospitals, sterilization and disinfection are the basic components of infection prevention; however, the prevention and control of infection for burn patients also requires the design of burn centers that adhere to a specific set of criteria that considers spatial infection control in addition to appropriate burn treatment methods and treatments. In this study, a burn facility converted from a burn unit into a burn center is introduced and the necessary design inputs for the transformation are discussed because there is no holistic study in the literature that delas with all the spaces that should be in a burn center and relations between spaces. This study aims to define the functional relations between each of the units and the spaces that change according to different sterilization demands in the burn center for ensuring spatial infection control. Furthermore, it aims to propose a method for ensuring continuity in the control of spatial infections.

The burn care and health facilities guidelines are examined within the framework of spatial standards, together with a comprehensive literature review. The design method was based on the spread of microorganisms and the effect of human movement on space and spatial transitions in the burn center, according to all relevant literature reviews. To determine the extent to which the differences in treatment protocols of burn care guidelines were reflected in the space, interviews were conducted with burn facility officials. The plan–do–check–act (PDCA) method is also modeled to ensure the continuity of infection control in the burn center.

The burn center design findings are classified under three main headings, namely, location of the burn center in the hospital, spatial organization and physical features of the burn center and the air flowing system. The importance of the interactions among the criteria for spatial infection control has been revealed. Due to the physical space characteristics and air flow characteristics that change according to human movement and the way microorganisms spread, it has been seen that designing the air flow and architectural aspects together has an effective role in providing spatial infection control. Accordingly, a functional relation scheme for the center has been suggested. It is also proposed as a model to ensure the continuity of infection control in the burn center.

This research presents spatial measures for infection control in burn centers for practitioners in health-care settings such as designers, engineers, doctors and nurses. The PDCA method also leads to continuity of infection control for hospital management.

This is the first study, to the best of the authors’ knowledge, to focus on developing the criteria for spatial infection control in burn center. Moreover, the aim is to create a function chart that encompasses the relationships between the units within the burn center design so that infection control can be coordinated spatially.

This paper aims to explore the relationship between market pricing and design quality within the development industry. Currently, there is a lack of research that examines real estate at the property level. Development quality is widely believed to have diminished over the past decades, while many investors seem uninterested in the design process. The study aims to address these issues through a pricing model that integrates design attributes. It is hoped that empirical findings will invite broader stakeholder interest in the design process.

The research establishes a framework for assessing spatial compliance across residential developments within London. Compliance is assessed across ten boroughs, with technical space guidelines used as a proxy for design quality. Transaction prices and spatial assessments are aligned within a hedonic pricing model. Empirical findings are used to establish whether undermining spatial standards presents a significant development risk.

Findings suggest a relationship between sale time and unit size, with “compliant” units typically transacting earlier than “non-compliant” units. Almost half of the 1,600 apartments surveyed appear to undermine technical guidelines.

It is suggested that an array of design attributes be explored that extend beyond unit size. Additionally, future studies may consider the long-term implications of design quality via secondary transaction prices.

Practical implications include the development of a more scientific approach to design valuation. This may enhance the position of product design management within the development industry and architectural services.

Social implications may include improvement in residential design.

An innovative approach combines a thorough understanding of both design and economic principles.

The purpose of this study is to identify the situation of spatial inequality in the residential system of Tehran city in terms of housing prices in the year 2021 and to examine its changes over time (1991–2021).

In terms of purpose, this study is applied research and has used a descriptive-analytical method. The statistical population of this research is the residential units in Tehran city 2021. The average per square meter of a residential unit in the level of city neighborhoods was entered in the geographical information system (GIS) in 2021. Moran’s spatial autocorrelation method, map cluster analysis (hot and cold spots) and Kriging interpolation have been used for spatial analysis of points. Then, the change in spatial inequality in the residential system of Tehran city has been studied and measured based on the price per square meter of a residential unit for 30 years in the 22 districts of Tehran by using statistical clustering based on distance with standard deviation.

The result of spatial autocorrelation analysis with a score of 0.873872 and a p-value equal to 0.000000 indicates a cluster distribution of housing prices throughout the city. The results of hot spots show that the highest concentration of hot spots (the highest price) is in the northern part of the city, and the highest concentration of cold spots (the lowest price) is in the southern part of Tehran city. Calculating the area and estimating the quantitative values of data-free points by the use of the Kriging interpolation method indicates that 9.95% of Tehran’s area has a price of less than US$800, 17.68% of it has a price of US$800 to US$1,200, 25.40% has the price of US$1,200 to US$1,600, 17.61% has the price of US$1,600 to US$2,000, 9.54% has the price of US$2,000 to US$2,200, 6.69% has the price of US$2,200 to US$2,600, 5.38% has the price of US$2,600 to US$2,800, 4.59% has the price of US$2,800 to US$3,200 and finally, the 3.16% has a price more than US$3,200. The highest price concentration (above US$3,200) is in five neighborhoods (Zafaranieh, Mahmoudieh, Tajrish, Bagh-Ferdows and Hesar Bou-Ali). The findings from the study of changes in housing prices in the period (1991–2021) indicate that the southern part of Tehran has grown slightly compared to the average range, and the western part of Tehran, which includes the 21st and 22nd regions with much more growth than the average price.

There is massive inequality in housing prices in different areas and neighborhoods of Tehran city in 2021. In the period under study, spatial inequality in the residential system of Tehran intensified. The considerable increase in housing prices in the housing market of Tehran has made this sector a commodity, intensifying the inequality between owners and non-owners. This increase in housing price inequality has caused an increase in the informal living for the population of the southern part. This population is experiencing a living situation that contrasts with the urban plans and policies.