Case Study In Shenyang Research Articles

A Conceptual Model for Revitalizing Shenyang’s Cultural Heritage: Enhancing Customer Engagement via Social Media Branding

This paper presents a conceptual framework focused on reviving cultural heritage using social media branding strategies. Based on the case study of Shenyang, China, it focuses on how traditional cultural practices can best handle the challenges facing dealing with the shifting world of the internet. As we operate in the fast-moving digital world, it is increasingly more challenging for traditional cultural practices to move in pace with digital evolution. According to social networks, a gap exists between preserving cultural values and adapting a customer's modern behavior. This paper presents a framework for cultural preservation, digital marketing, and consumer participation. This paper stresses that social media can be viewed as a cultural heritage promotion enabler while engaging consumers in this framework. Core features include the digitalization of critical cultural elements, the development of cultural heritage-related online communities through social media, the increase of interaction of people with culturally created content, and so on. This framework offers a path to renewing the cultural landscape by incorporating digital strategies. It also acknowledges challenges like potential commodification and loss of authenticity. The insights will benefit policymakers, cultural institutions, and businesses while guiding further empirical research on social media’s role in cultural preservation.

The impact of the urban landscape on PM2.5 from LCZ perspective: A case study of Shenyang

Based on the World City Database Access Portal tool (WUDAPT), the local Climate zoning (LCZ) classification of Shenyang(China) was carried out. With 8 environmental monitoring stations at the observation of the study area, LCZ landscape categories in the buffer zone of 500 m, 1000 m, and 3000 m were analyzed using ArcMap and Fragstats. The sensitivity analysis of the landscape category index correlated with PM2.5 was conducted to select the representativeness index. Matlab was used to construct the regression equation between the LCZ categories and PM2.5. The results show that AI_500, LSI_500, PD_500, LSI_1000, AI_1000, LSI_3000, and AI_3000 can be used as representative landscape indices to represent the aggregation and diversity of LCZ categories. The regression equations for PM2.5 in all four seasons include factors influencing the LCZ category landscape. This study analyzed the relationship between PM2.5 distribution and urban patterns from the perspective of the LCZ types. It provided the scientific reference for rational planning of urban layout and coordination of environment and urban development.

A Coupling Model for Measuring the Substitution of Subways for Buses during Snowstorms: A Case Study of Shenyang, China

The development of integrated public transportation networks has received widespread attention in recent years. Especially in global northern cities, improving the substitution of subways for buses could meet population travel demand during snowstorms, which minimizes the impact of snowstorms on the public transportation network. Furthermore, the development of rail transit is conducive to the intensive and efficient use of land resources. Therefore, in this study, we selected a northern Chinese city, Shenyang, as a case study. For obtaining the population travel demand, we collected the actual population flow data in the morning and evening peaks during snowstorms. The network analysis was used to identify the loopholes and key stations in the subway and bus networks, respectively. A coupling model was built to measure the coupling value of each station in the subway and bus networks, according to its population travel demand and supply capacity, which was further used to measure the substitution of subways for buses in the morning and evening peaks during snowstorms. The results indicate that some subway stations were in a coupling state, while their surrounding bus stations were in a decoupling state. These subway stations could replace the bus stations to reduce the impact and damage of snowstorms on public transportation network. However, some subway stations and the surrounding bus stations were all in a decoupling state, which were under great pressure to meet the population commuting demand during snowstorms. This study can provide insight into optimizing public transportation network planning and design in many northern regions and help to coordinate land and transportation utilization.

Research on the Improvement Path of Prefabricated Buildings’ Supply Chain Resilience Based on Structural Equation Modeling: A Case Study of Shenyang and Hangzhou, China

Due to increasing cost and decreasing labor, prefabricated buildings have developed rapidly. With the prolongation of prefabricated buildings’ supply chain (PBSC) and an increase in risk factors, project delays and even interruptions occur occasionally. The difficulty of supply chain management is increasing. Supply chain resilience (SCR) as a risk management tool has gradually attracted the attention of scholars. This paper uses the grounded theory to identify the influencing factors of prefabricated buildings’ supply chain resilience (PBSCR) based on the dynamic capacity theory. By collecting questionnaires from relevant stakeholders in Shenyang and Hangzhou, a structural equation model (SEM) was used to test the research hypothesis. The capacity effect relationship of the PBSC was constructed. The results show that resilient capability has the highest direct effect on the improvement in PBSCR, and collaborative capability has the highest total and indirect effect on the improvement in PBSCR. The critical paths to improving PBSCR were then identified. Suggestions were made based on the calculated effect relationships. This paper is expected to improve PBSCR, enrich the research on supply chains in the construction field, and help better realize the stable development of prefabricated buildings.

Analysis on the Energy Demand, CO2 and Pollutant Emissions, and Health Benefits from Urban Road Transport Sector: A Case Study of Shenyang

As society develops and urbanization accelerates, energy requirement and environmental emissions in the road transport field have expanded in Shenyang, China. It is necessary to look at its future energy needs and environmental emission trends. In this work, we have used the LEAP model to account for the energy requirement and environmental emissions from 2017 to 2030 under five scenarios for the road transport sector in Shenyang. Additionally, the intake fraction approach was applied to estimate the health effects and financial damages of NOX, SO2, PM10, and PM2.5 emissions. The results indicate that the energy required in 2030 will reach 8.18~10.65 Mtce in various scenarios. By 2030, under the business as usual (BAU) scenario, the emissions of CO2, CO, SO2, NOX, PM10, and PM2.5 will be 31089.51, 1794.4, 20.59, 205.88, 6.6 and 6.5 kt, respectively. Regarding health benefits, financial damage caused by NOX, SO2, PM10, PM2.5 emissions will reach RMB 8.594, 0.117, 1.013, and 1.566 billion in 2030 under the BAU scenario. Moreover, the development of energy-efficient and new energy automobiles is the best means of reducing energy demand and environmental emissions; thus, this approach should be paid special attention when developing future energy efficiency and emission abatement policies for road transport.

Effect of Interior Space and Window Geometry on Daylighting Performance for Terrace Classrooms of Universities in Severe Cold Regions: A Case Study of Shenyang, China

Good daylighting performance positively affects students’ physical and mental health, learning efficiency, and the building’s energy-saving capability. Due to the terrace classroom having ample space, large capacity, the ability to avoid obstructing sight, and the ability to meet various use needs, it is the most important place in university buildings. However, research on the daylighting performance of university terrace classrooms is limited, leading to a lack of quantitative guidance in early design stages. This study aims to explore the effects of interior space and window geometry of terrace classrooms in universities in severe cold regions on daylighting performance. This research took Shenyang as an example; spatial daylight autonomy (sDA300,50%) and useful daylight illuminance (UDI100–2000) were selected as daylighting performance evaluation indices. Based on the Grasshopper parametric platform, the simulation was carried out using Ladybug and Honeybee plugins. Correlation and regression analyses revealed the relationship between interior space and window geometry parameters and the evaluation indices. The results showed the following: window-to-floor ratio (WFR), classroom height (Htc), window height (Hw), window-to-wall ratio (WWR), classroom width (Wtc), and window width (Ww) have positive effects on improving the daylight sufficiency of the terrace classrooms facing each orientation, and the degree of the effect decreases in order. To ensure the overall daylighting performance, the Wtc can be maximized. The width of walls between windows for south-facing and west-facing classrooms should be 0.9 m. The WWR and WFR for south-facing classrooms should be 0.3–0.5 and 0.11–0.14, respectively. The WWR and WFR for north-facing classrooms should be 0.6–0.7 and 0.14–0.20, respectively. Prediction models are established for the sDA300,50% and UDI100–2000 of the terrace classrooms facing each orientation.

Synergy Degree Evaluation in the Development of Intelligent Construction and Construction Industrialization—A Case Study of Shenyang, China

Abstract In recent years, China’s construction industry has faced looming problems such as sloppy production methods and environmental pollution. Then the initiative of ‘synergistic development of intelligent construction and construction industrialization (ICCI)’ was proposed, which brings new opportunities for the transformation and upgrading and high-quality development of the construction industry. However, the synergy degree in the development of ICCI cannot be measured by the senses. Therefore, this study is devoted to quantitative analysis of the synergy degree in the development of ICCI by establishing a mathematical model. The concept of the synergy degree in the development of ICCI is defined based on synergetics. CiteSpace software is used to determine the five basic elements of talent, technology, information, environment and policy for the synergistic development of ICCI. Based on this, building a mechanism for synergistic development of ICCI with the Driving Force-State-Response (DFSR) model. Establishing an evaluation index system for the synergy degree in the development of ICCI through expert interviews. Then, combining entropy power method and coupling coordination model to empirically analyse the synergy degree in the development of ICCI in Shenyang. The results show that Shenyang is currently at the stage of high-level coupling and high-quality synergy, which is consistent with the actual development. It is also confirmed that the evaluation system of the synergy degree in the development of ICCI is scientific and reasonable. Finally, this study summarizes the suggestions for different levels of the synergy degree in the development of ICCI, which provides a reference for each region to better promote the synergistic development of ICCI.

Analysis of the Characteristics of Usage and Carbon Reduction Effect of Shared Bikes in Low Temperature and Snowy Area –A Case Study of Shenyang

Analysis of the Characteristics of Usage and Carbon Reduction Effect of Shared Bikes in Low Temperature and Snowy Area –A Case Study of Shenyang

Urban-Rural Fringe Long-Term Sequence Monitoring Based on a Comparative Study on DMSP-OLS and NPP-VIIRS Nighttime Light Data: A Case Study of Shenyang, China.

Urban–rural fringes, as special zones where urban and rural areas meet, are the most sensitive areas in the urbanization process. The quantitative identification of urban–rural fringes is the basis for studying the social structure, landscape pattern, and development gradient of fringes, and is also a prerequisite for quantitative analyses of the ecological effects of urbanization. However, few studies have been conducted to compare the identification accuracy of The US Air Force Defence Meteorological Satellite Program’s (DMSP) and the Visible Infrared Imaging Radiometer Suite (VIIRS) nighttime light data from the same year, subsequently enabling long time series monitoring of the urban–rural fringe. Therefore, in this study, taking Shenyang as an example, a K-means algorithm was used to delineate and compare the urban–rural fringe identification results of DMSP and VIIRS nighttime light data for 2013 and analyzed the changes between 2013 and 2020. The results of the study showed a high degree of overlap between the two types of data in 2013, with the overlap accounting for 75% of the VIIRS data identification results. Furthermore, the VIIRS identified more urban and rural details than the DMSP data. The area of the urban–rural fringe in Shenyang increased from 1872 km2 to 2537 km2, with the growth direction mainly concentrated in the southwest. This study helps to promote the study of urban–rural fringe identification from static identification to dynamic tracking, and from spatial identification to temporal identification. The research results can be applied to the comparative analysis of urban–rural differences and the study of the ecological and environmental effects of urbanization.

Classification of Housing Submarkets considering Human Preference: A Case Study in Shenyang, China

Housing submarket is affected by the quality of public facilities in neighborhood. In this article, a three-step framework is proposed to classify the housing market in Shenyang city, China. The saliences of point of interest, POI, are used to quantify the degree of activities using social media data and merged into the model of density-field hotspot detector to extract high-quality of urban facilities, aiming at exploring the influences on the housing price. The multiscale geographically weighted regression model, MGWR, is applied to investigate relations between the housing price and attribute variables geographically and to identify multiscale impacts on the housing price with flexible bandwidths. The spatial “k”luster analysis by the tree edge removal method, SKATER, is applied to delimit urban housing submarkets based on the MGWR betas, where ten groups of the housing submarkets are recognized. The proposed classification method captures multiscale spatial heterogeneity of the housing price and predominant influencing factors for each housing submarket in Shenyang, China. It also offers suggestions for urban planners to restrain the unbalanced development of the housing market.

Spatial Structure of Urban Residents’ Leisure Activities: A Case Study of Shenyang, China

Spatial Structure of Urban Residents’ Leisure Activities: A Case Study of Shenyang, China

A Case Study of Shenyang’s New Town Development Policy

중국의 도시화 과정의 추진에 따라 도시 경제가 빠르게 성장하고, 도시 면적이 끊임없이 증가하며, 도시 인구가 점차 유입되고, 도시는 더욱 높은 밀도 방향을 향해 발전한다. 그러나 현재의 도시계획과 도시건설 과정에는 체계적이고 과학적이며 지속가능한 지도가 결여되어 도시의 주택 부족, 도시 주거 공간의 밀집과 그로 인한 생태 환경 문제에 직면하게 될 것이며, 지속적인 신도시와 신시가지를 개발하여 도시 인구가 날로 증가하는 현상을 초래할 것이다. 신도시 개발은 구시가지의 인구와 취업 압력을 완화하고 도시경제 성장을 실현하는 중요한 방법 중의 하나이다. 신도시 개발은 신도시주의, 도시발전단계이론, 현대주거지역계획이론의 지도 아래 세계 각국의 도시지역 발전에 중요한 연구 내용이 되고 있다. 본 연구는 심양시(沈 陽市)의 신도시 개발정책을 연구 대상으로 사례분석 및 문헌연구 방법을 적용해 심양의 도시 발전 동인 및 신도시 계획과 개발의 특성을 연구하여, 현대주거지역 계획이론, 신도시주의 이론, 도시발전단계 이론을 종합해 심양신도시의 살기 좋은 도시의 정체성을 모색하고, 도시 기능의 제고와 도시공간의 발전을 위한 도시화단계에서 새로이 건설되는 신도시 개발정책에 시사점을 도출한다.

Eco-Environmental Effects of Industrial Cities Based on Remote Sensing Images: A Case Study of Shenyang, China

With Landsat remote sensing image and GIS spatial analysis method, the ecological environment of the built-up urban area in the third ring of Shenyang was studied, which was an industrial city. The LST and NDVI were extracted to analyze the urban spatial patterns and the relationship with urban land use types. The results showed that LST and NDVI were negatively correlated in urban ecosystem. The urban surface temperature and vegetation index of different land use types were significantly different. On the scale of 1 km, LST was weakly positively correlated with SHDI, while NDVI was negatively correlated with SHDI; LST increased with the increase of land use type diversity, while NDVI decreased with the increase of land use type diversity.

Analysis of Spatial Scale Effect on Urban Resilience: A Case Study of Shenyang, China

Based on urban physical space and theory of landscape ecology, a triune assessment framework —‘size-density-morphology’—was constructed in order to analyze the spatial pattern and the scale effect of urban resilience in Shenyang of China in 2015, and to explore the main impact factors of landscape under different spatial scale backgrounds. The results show that: 1) Urban resilience is an optimal combination of the resilience of size, density, and morphology. The urban resilience of Shenyang displays scale effect; the overall resilience level increases with the increase in scale, while the spatial difference and spatial similarity tend to decrease resilience. 2) As 2 km, 1 km and 2 km are scale inflection points of average value curves for size resilience, density resilience and morphology resilience, respectively in an urban setting; the optimal scale unit of comprehensive resilience is 1 km. Choosing 1 km–2 km as the basic spatial scale better depicts overall pattern and detailed characteristics of resilience in Shenyang. The spatial amplitudes of 0.5 km and 1 km are sensitive points for spatial autocorrelation of morphology and density resilience, size, and comprehensive resilience to scale effect. 3) The major landscape factors of urban size and morphology resilience transform with scale expansion. Aggregation index (AI) has a significant impact on urban resilience at different scales; its influence increases significantly with the increase in scale. 4) The high-level area of comprehensive resilience in Shenyang is the eastern ecological corridor area, while the low value area is the peripheral extension area of the city. To promote the overall level of resilience in Shenyang, this paper argues that the construction of ecological infrastructure should be strengthened in the peripheral extension area in a balanced manner. In the city center, population and building density should be controlled; the intensity of human activities should be reduced; impetus should be placed on landscape heterogeneity; and the homogeneous expansion of the area of construction should be prevented. In the eastern ecological corridors, the exploitation of ecosystem lands should be strictly controlled, and the integrity of the green landscape patches should be maintained.

Modeling the Impact of Urban Three-Dimensional Expansion on Atmospheric Environmental Conditions in an Old Industrial District: A Case Study in Shenyang, China

Modeling the Impact of Urban Three-Dimensional Expansion on Atmospheric Environmental Conditions in an Old Industrial District: A Case Study in Shenyang, China

Optimization-based method to develop practical driving cycle for application in electric vehicle power management: A case study in Shenyang, China

In this study, a novel method for the construction of a driving cycle based on a two-layer optimization process is proposed with a case study in Shenyang, China. First, the statistical data is obtained and divided into many micro-trips, namely the speed profiles between two successive stops; then, three representative parameters are derived from the vehicular model. Second, the development of the driving cycle is transferred to an optimization problem, and a two-layer optimization method is proposed to construct the typical driving cycle. In the first layer, the optimal combination of micro-trips is determined using a genetic algorithm (GA) with varying quantity of micro-trips, whereas in the second layer, the best quantity of micro-trips is determined according to the speed–acceleration probability distribution (SAPD) and average energy consumption (AEC). The results indicate that the proposed method can produce a more representative driving cycle, 2.49% closer to the statistical data than the traditional Markov chain method. Finally, the established driving cycle is applied to power management design with three different vehicle types. The results indicate that the established driving cycle can help in reducing the energy cost by up to 19.8% under the real-world Shenyang driving condition.

Response of microbial community structure to the hydrochemical evolution during riverbank filtration: a case study in Shenyang, China

Microorganisms are widely involved in the transformation process of physical and chemical properties in the geological and hydrogeological environment. Active participation of microorganisms is important features of the biogeochemical reactions during groundwater exploiting along the riverbank filtration. Hydrodynamic condition has a direct or indirect difference control of the biological effectiveness, chemical activity and mobility of the pollution components, which can affect biogeochemical process. In different biogeochemistry, there will be some exclusive functional bacteria, which is of great significance to understand the biogeochemical mechanism of river water infiltration. This study confirms that there are two main different flow paths from river to the center of the depression cone due to different hydrodynamic conditions and spatial characteristics and scaling effects of redox zonation during riverbank filtration. In different flow paths, the microbial abundance shows obvious spatial heterogeneity. The microbial abundance and species similarity degree of the riverbed and deep flow path sediments has significant correlation. There is a significant correlation between the dominant bacteria and the environmental factors in different hydrodynamic conditions on a spatial scale. This study is the first to reveal the response of microbial community structure to water chemical evolution during riparian filtration. Due to significant positive correlation between the Fe/Mn and As, it brings the potential danger for drinking water.

Analyzing Industrial Structure Evolution of Old Industrial Cities Using Evolutionary Resilience Theory: A Case Study in Shenyang of China

The recession and revitalization of old industrial cities concerns urban industrial evolution and its characteristics. Based on the theory of evolutionary resilience, we developed an analytical framework for the industrial structure evolution of old industrial cities, and applied the framework to a case study in Shenyang. The following conclusions are drawn. First, since 1978, Shenyang’s industrial growth capacity has shown fluctuation between ‘contraction-expansion’. As the secondary industry has a much stronger expansionary and contractionary capacity for growth, this results in lacking stability leading to industrial structure transformation. Second, since 1999, the orientation towards a high-end manufacturing industry in Shenyang has weakened, and the evolution of the new and old growth path is characterized by low-end orientation. Third, since 2007, Shenyang’s industrial innovation output capacity has dropped sharply which has been significantly affected by scientific and technological personnel and enterprise-owed science and technology institutions and to a less extent by R&D expenditure. We applied the resilience theory to study the industrial evolution of an old industrial city, explored new study perspectives on industrial evolution and verified the applicability of the resilience theory. This paper provides a scientific reference for understanding the recent deceleration in economic growth in the Northeast old industrial base, and for exploring new paths toward revitalization.

Profile and concentric zonal analysis of relationships between land use/land cover and land surface temperature: Case study of Shenyang, China

In this study, relationships between land use/land cover (LULC) types and land surface temperature (LST) patterns in Shenyang, China were investigated using Landsat 8 image. Typical characteristics of LST in summer time and temperature variations over all LULC types were firstly examined. Afterwards, spatial distribution of LST in radial and circumferential directions was characterized based on profile and concentric zonal analysis, in which contributions of LULC types to LST were studied. In addition, models that can effectively predict LST distribution were developed based on multiple linear regression method (MLRM) and the partial least squares regression method (PLSRM). Results indicate that (1) LST of the study area mainly ranges from 32°C to 41°C, where building and road are main drivers leading to hot temperatures. (2) Temperature profiles vary greatly with LULC types, while urban expansion along central axis causes to horizontal arrangement of building and road, resulting in hot but small-fluctuated LST temperature in 0° and 180°. (3) Mean and standard deviation of LST in concentric zones are 36.0±4.2°C, and LST over all LULC types follows the following pattern: building>road>bare land>agricultural land>green land>water bodies. Due to large proportions of building and road, Buffer 3, 4 and 5 undergo the highest temperature. Although green land and water bodies show significant capability to mitigate UHI effects, cooling effects are unapparent when their sizes are small. (4) Both models developed on MLRM and PLSRM have high degree of accuracy, while the latter is more reasonable for different coefficients can respectively indicate negative and positive roles of LULC types in affecting surface temperature. In general, this study can assist urban planners and policy makers to understand relationships between local LULC types versus LST patterns, and can help them predict UHI patterns along rapid urban expansion, and then make rational urban planning decisions for UHI mitigation.

Application of data mining to the analysis of meteorological data for air quality prediction: A case study in Shenyang

Air pollution is one of the important reasons for restricting the current economic development. PM2.5 which is a vital factor in the measurement of air pollution is defined as a kind of suspended particulate matter with its equivalent diameter less than 25μm, which may enter the alveoli and therefore make a great impact on the human body. Meteorological factors are also one of the main factors affecting the production of PM2.5, therefore, it is essential to establish the model between meteorological factors and PM2.5 for the prediction. Data mining is a promising approach to model PM2.5 change, Shenyang which is one of the most important industrial city in Northeast China with severe air pollutions is set as the case city. Meteorological data (wind direction, wind speed, temperature, humidity, rainfall, etc.) from 2013 to 2015 and PM2.5 concentration data are used for this prediction. As to the requirements of the World Health Organization (WHO), three data mining models, whereby the predictions of PM2.5 are directly generated by the meteorological data. After assessment, the random forest model is appeared to offer better prediction performance than the other two. At last, the accuracy of the generated models are analysed.