Patterns Of Regional Development Research Articles

Research on Vocational Regional to Development by Vocational Education

Zhejiang province of China has a large economic aggregate, optimized industrial structure, balanced regional development pattern, transformation and upgrading of industrial layout, along with excellent business environment and urban-rural integrated development. For decades, through the training of technical talents which directly meets the needs of regional economic development; deepens the cooperation between schools and enterprises, provides skilled personnel support for economic and social development, and promotes regional cooperation and foreign cooperation. Taking Zhejiang Province as an example, this paper discusses how vocational education promotes the regional economy, and analyzes the existing problems and future prospects.

Spatial inequality in sub-national human development index: A case study of West Bengal districts

Human Development and its regional disparity is an area of topical interest. In this paper, we consider space as an instrumental variable in understanding this disparity and explore spatial interdependence in human development across districts of West Bengal using alternate indicators of human development. This study uses both the standard United Nations Development Programme (UNDP) technique and an alternative methodology to construct a sub-national human development index. Spatial interdependence is measured using Moran's I coefficient and Local Indicators of Spatial Autocorrelation (LISA) cluster maps. Spatial regression is used to evaluate the spatial association between the Human Development Index as the dependent variable and a few independent variables. A high degree of clustering in all three dimensions of human development is observed among the southern districts of West Bengal. The pattern of cluster maps indicates the presence of both the growth pole process and the metropole-periphery process in the state. Spatial regression results indicate that the share of socially backward class population and urbanization rate are important variables affecting regional human development patterns. The findings of this study suggest policies targeted to promote social inclusion and urbanization linked with better access to economic opportunities in the lagging areas can help reduce regional imbalances.

Whyalla and the transition to a decarbonised future

ABSTRACT Whyalla, an old steel town in the Upper Spencer Gulf in South Australia, has had a chequered history. Steel production has been precarious for a decade and more. Now, the promise of ‘Green Steel’ and a local major Hydrogen Hub holds out the hope of regional security. In this article, I trace the history of Whyalla, the region, and its steel works and outline the promise of a new future based on renewable industries. I start by outlining the importance of stressing both time and place in analysing the process and pattern of regional development. Insodoing, I question the validity of much ‘place-based’ analysis and point to Deep Place analysis as a possible alternative. I examine the limits and possibilities of the current transition and suggest that the future may not yet be entirely secure.

Evaluation method for ecology-agriculture-urban spaces based on deep learning

With the increasing global population and escalating ecological and farmland degradation, challenges to the environment and livelihoods have become prominent. Coordinating urban development, food security, and ecological conservation is crucial for fostering sustainable development. This study focuses on assessing the "Ecology-Agriculture-Urban" (E-A-U) space in Yulin City, China, as a representative case. Following the framework proposed by Chinese named "environmental capacity and national space development suitability evaluation" (hereinafter referred to as "Double Evaluation"), we developed a Self-Attention Residual Neural Network (SARes-NET) model to assess the E-U-A space. Spatially, the northwest region is dominated by agriculture, while the southeast is characterized by urban and ecological areas, aligning with regional development patterns. Comparative validations with five other models, including Logistic Regression (LR), Naive Bayes (NB), Gradient Boosting Decision Trees (GBDT), Random Forest (RF) and Artificial Neural Network (ANN), reveal that the SARes-NET model exhibits superior simulation performance, highlighting it’s ability to capture intricate non-linear relationships and reduce human errors in data processing. This study establishes deep learning-guided E-A-U spatial evaluation as an innovative approach for national spatial planning, holding broader implications for national-level territorial assessments.

SPATIAL ANALYSIS OF LAND USE CHANGE IN SLAWI SUBDISTRICT, TEGAL REGENCY, 2014 - 2024 USING HIGH RESOLUTION SATELLITE IMAGERY DATA

This research aims to analyze land use change in Slawi Sub-district, Tegal Regency, from 2014 to 2024 using high-resolution satellite image data. This study used Worldview-2 high resolution satellite image data in 2014 and Geoeye-1 in 2024. This study was classified into 14 land use classes consisting of rivers, roads, railways, agriculture, green open space, other vegetation, industry, housing, government, public service facilities, trade services, transportation, defense and security and open land. The spatial analysis method was used to map changes in land area based on the main use classes such as agriculture, housing, and infrastructure. The results showed a significant decrease in agricultural land area as well as an increase in residential land area and infrastructure, reflecting the changing pattern of regional growth and development. In conclusion, an in-depth understanding of land use dynamics in Slawi Sub-district is important to support environmental management policies, natural resource conservation, and sustainable regional development in the future.

Exploring Regional Development Patterns using Machine Learning: A Python-based Clustering Analysis of Human Development Index in West Java

Many local governments now prioritize human development when trying to raise the standard of living and welfare of their citizens. Developing effective development policies in West Java, one of Indonesia's most populous provinces, requires a thorough understanding of human development patterns in various districts and cities. Using the Human Development Index (HDI) as the primary indicator, we examine regional development patterns in this study using machine learning techniques, specifically clustering analysis. This study's scope includes an HDI analysis for each of West Java's 27 districts and cities from 2017 to 2022. Finding clusters of districts or cities with comparable human development traits and comparing and contrasting them are our primary goals. We provide a solution that allows for improved mapping and comprehension of human development patterns in West Java by utilizing the Python programming language as the primary tool and the K-Means clustering algorithm. The study's findings indicate that there are three major categories of districts and cities, each with a distinct human development pattern. By using clustering analysis, we can determine which districts or cities within each group have the highest and lowest levels of human development. This information helps policymakers plan more inclusive and sustainable development. In conclusion, a clustering analysis approach based on machine learning can be a helpful tool for understanding and creating more focused and efficient regional development policies in West Java and other areas.

Construction and evolutionary pattern of the coupling relationship network of regional sustainable development in China

Climate change poses a serious threat to the survival and development of humankind. Accordingly, sustainable socioeconomic transformation has become a major global concern. This study quantitatively assesses the process and speed of regional-level sustainable development in China, as well as the degree of coupling and the degree of coupling coordination among Sustainable Development Goals (SDGs). To this end, based on regional development and data monitoring in China, we construct a regional sustainable development assessment system containing 111 indicators, which combines existing sustainable development assessment indicators with the indicators of the 2030 Agenda for Sustainable Development. On that basis, using network topology construction and modal transformation, we propose a framework for analyzing the coupling relationships and evolutionary patterns of regional sustainable development. The study found that the score for SDGs at the national level increased from 50.80 in 2010 to 60.86 in 2020, showing a good development trend and the differences between provinces and regions was gradually reduced. The development speed of regional sustainable transformation shows a change from decreasing to increasing. In recent years, there is a significant change in the acceleration of regional sustainable development in China, with the vast majority of provinces having positive acceleration and only three provinces having negative acceleration. China's regional sustainable development shows that mutual coordination and promotion among provinces was higher in the eastern area than in the central region, which was higher than in the western area. The sustainable processes of each region and the coordination of sustainable development steadily increased toward a high level of coupling, all achieving coordinated development. The degree of coupling coordination and the SDG scores in each region were positively correlated with economic development, reflecting the role of economic development in the promotion of sustainability. However, this positive correlation showed a tendency of strengthening and then weakening. The correlation of the evolution patterns in the eastern–central, eastern–western, and central–western regions over time presented a trend of first weakening, then strengthening, and then weakening. Although the process of promoting sustainable development in western and central regions over time is weak synergistic consistency with that in eastern regions, overall, China's regional sustainable development presents a development model of multi-province linkage and multi-goal coordination.

Differentiated Paths of Regional Green Development Driven by Industrial Enterprise Innovation

A fundamental shift in the regional development pattern is crucial to achieving a comprehensive green transformation in China. Currently, innovation-driven green development is a significant strategic option for regional development. As the main body of innovation and the basic unit of regional composition, enterprises have a profound impact on the development of regional economy, society, ecology, and other aspects. However, considering China’s vast territory and significant regional differences in natural environment and industrial structure, it’s necessary to further explore the specific impact paths of regional green development driven by enterprise innovation. Therefore, taking industrial enterprises as an example, based on the panel data of 30 provinces in China from 2016 to 2020, this study verifies the impact of industrial enterprise innovation on the regional green development level by constructing a parallel multiple mediating effect model and dividing the economy into eastern, central, and western regions to discuss the specific impact paths. The results show that industrial enterprise innovation has a significant positive effect on regional green development level, via different influencing paths in each region: (1) The eastern region improves the regional green development level by narrowing the urban-rural income gap; (2) The central region improves the regional green development level by reducing resource dependence; and (3) The western region raises the regional green development level by improving the rationalization of industrial structure.

The Spatio-Temporal Patterns of Regional Development in Shandong Province of China from 2012 to 2021 Based on Nighttime Light Remote Sensing.

As a major coastal economic province in the east of China, it is of great significance to clarify the temporal and spatial patterns of regional development in Shandong Province in recent years to support regional high-quality development. Nightlight remote sensing data can reveal the spatio-temporal patterns of social and economic activities on a fine pixel scale. We based the nighttime light patterns at three spatial scales in three geographical regions on monthly nighttime light remote sensing data and social statistics. Different cities and different counties in Shandong Province in the last 10 years were studied by using the methods of trend analysis, stability analysis and correlation analysis. The results show that: (1) The nighttime light pattern was generally consistent with the spatial pattern of construction land. The nighttime light intensity of most urban, built-up areas showed an increasing trend, while the old urban areas of Qingdao and Yantai showed a weakening trend. (2) At the geographical unit scale, the total nighttime light in south-central Shandong was significantly higher than that in eastern and northwest Shandong, while the nighttime light growth rate in northwest Shandong was significantly highest. At the urban scale, Liaocheng had the highest nighttime light growth rate. At the county scale, the nighttime light growth rate of counties with a better economy was lower, while that of counties with a backward economy was higher. (3) The nighttime light growth was significantly correlated with Gross Domestic Product (GDP) and population growth, indicating that regional economic development and population growth were the main causes of nighttime light change.

Cross-border e-commerce integrated with regional economic development on mixed depression among financial professionals

BackgroundIn recent years, mixed-type depression has become a widely recognized mental health issue. The rise of cross-border e-commerce and the new pattern of regional economic development may make financial professionals face more complex work environments, which may affect their mental health status. Considering that the combination of cross-border e-commerce and regional economic development may have a certain degree of impact on the mental health of financial practitioners, the study aims to explore the nature and extent of this impact, in order to take effective measures to improve the work environment and quality of life of financial practitioners.Subjects and MethodsThe study followed 80 financial professionals with mixed depression for 1 year. It investigated the extent of mixed-type depression in patients before and after the intersection of cross-border e-commerce and regional economic development. The study used the Hamilton Depression Scale (HAMD) to assess the severity of mixed depressive symptoms.ResultsAfter the mutual integration of cross-border e-commerce and regional economic development, the average HAMA score of mixed depression among financial employees decreased to approximately 10.45, with a significant pre-post difference (P<0.05), indicating that the patients’ mixed depression was significantly alleviated.ConclusionsThe combination of cross-border e-commerce and regional economic development has a significant positive impact on the mixed depression of financial professionals. Prove that while promoting economic restructuring and cross-border e-commerce development, it also indirectly promotes the psychological health of practitioners.AcknowledgementThe 2019 Research Project of Humanities and Social Sciences by Chongqing Municipal Commission of Education (No. 20skz092).

Low carbon development patterns of land use under complex terrain conditions: The case of Chongqing in China

Land exhibits distinct carbon source/sink states under varying utilization conditions. Under the climate change environment, developing low-carbon land use optimization strategies has become an urgent problem. Thus, this study examines the characteristics of land use carbon emissions (LUCE) resulting from land use and land cover change (LUCC) in Chongqing under five shared socioeconomic pathways (SSPs). The results show: (1) From 2000 to 2020, the LUCE in Chongqing increased significantly and then decreased slightly. The improvement of energy technology can limit carbon emissions from expanding construction. (2) In 2030, Chongqing will have the highest LUCE in SSP5 scenario, followed by SSP4 scenario, and the lowest in SSP2 scenario. However, some districts and counties in Chongqing City have the opposite situation to the whole research area. (3) In the study area, LUCE exhibits a significant positive spatial correlation with Moran's indices of 0.48, 0.27, and 0.39 in 2000, 2010, and 2020, respectively. Carbon emissions in Chongqing primarily concentrate in the main urban areas, with high-emission areas spreading outward from specific centers in the districts and counties. In 2030, spatial LUCE aggregation will decrease significantly, especially in the SSP3 scenario, with a Moran's index of 0.25. When adjusting the land use structure, policymakers need to implement differentiated land use management strategies, considering the characteristics of LUCE and their development directions. This study confirms that socioeconomic development has a direct impact on LUCE. The results of this study provide a reference for the government’s land-use assessment, achieving low-carbon development goals, and identifying regional development patterns.

Geospatial characteristics and the application of land use functions in the Yangtze River Economic Belt, China: Perspectives on provinces and urban agglomerations

As an essential tool to evaluate land use sustainability, land use functions (LUFs) have become a hot topic in the field of land use science for promoting sustainable regional development. Previous studies focused more on the interaction analysis among LUFs and the zoning management of LUFs, ignoring the importance of geospatial characteristics of LUFs for regional development patterns. In this study, a series of geospatial analysis methods were adopted to identify the abrupt changes in LUFs, and evaluate the geospatial characteristics of LUFs in the Yangtze River Economic Belt (YREB), including agglomeration, coordination, and inequality. Finally, we combined the evaluation results to distinguish the development patterns of provinces and urban agglomerations (UAs). The findings show that the abrupt changes in LUFs occurred in 2002 and 2013, and the changes of LUFs experienced three stages: sharp decline, rapid rise, and steady development from 1990 to 2018. There was a significant agglomeration of LUFs in low value areas, and gradually to high value areas over time. The coordination of LUFs exhibited moderately coordinated, which was higher in the east than in the west, though the gap has been narrowing. The major contributor to LUF inequality was from within the province rather than among them, and so did UAs. All provinces and UAs were classified into radiation-driven, multi-core driven, stable, and low-level ones. Our research provides a reference for large-scale regional development and land use management.

Assessment of regional development pattern towards sustainability urban areas: empirical evidence from Yogyakarta urban areas

Assessment of regional development pattern towards sustainability urban areas: empirical evidence from Yogyakarta urban areas

Spatio-temporal evolution of population mobility differentiation patterns in a pandemic context: based on a network perspective

The COVID-19 has caused adverse effects in various aspects, and its impact on population mobility cannot be ignored. In this study, we obtain mobility data for the Beijing–Tianjin–Hebei region during the Chunyun period of 2019–2021 and divide it into four stages. By developing directional weighted networks, the mobility patterns for pre- and post-epidemic are examined. Firstly, the migration scale declines significantly post-epidemic. The fourth stage migration scale exceeds 65% of 2019 in 2021 indicating the situation improves. Secondly, the structural characteristics are compared. The average degree values, clustering coefficients, and path lengths in the fourth stage of 2021 are higher than the values in 2020, showing the recovery of migration, but also efficiency degradation. Thirdly, community detection results show that three communities can be highlighted in the network, which followed Regional Development Pattern. Finally, the findings of Modified Alter-based Centrality and Alter-based Power models show that Beijing (27.78, 17.74) and Tianjin (14.92, 4.38) are typical cities, Tangshan (3.74, 0.03) and Langfang (3.40, 2.00) are gateway cities and others are general cities. A reasonable population distribution has not been formed. The study provides fresh perspectives for applying spatio-temporal data in health emergencies, and the results provide theoretical support for policy formulation of socio-economic recovery.

The Administrative Center or Economic Center: Which Dominates the Regional Green Development Pattern? A Case Study of Shandong Peninsula Urban Agglomeration, China

Central cities play a critical role as beneficial areas for regional development and lead the high-quality development of an entire region and surrounding cities. As social and economic activities expand, the regional development pattern becomes more complex. This is typically manifested in the separation of administrative and economic centers. In this context, there is high research value in identifying the roles of different types of central cities in the regional green development pattern. This paper analyzes the urban linkage pattern and evolving characteristics of green development in the Shandong Peninsula, China, from 2016 to 2020. The study adopts the methods of Bootstrap Data Development Analysis, Modified Gravity Model, and Social Network Analysis. The results show the following. (1) Both the administrative center and economic center have positive driving effects on the spatial connection of surrounding cities in the urban agglomeration. There is a multi-point, multi-core, and multi-path spatial correlation in the Shandong Peninsula urban agglomeration. (2) The joint strength of the administrative center is higher compared to the economic center, and most of the green development partnerships are centered on the provincial capital. (3) The gravitational force of cities close to the administrative center is generally higher than seen with the economic center cities, but there is a gradual emergence of a substantial gravitational effect of the economic center.

Unleashing the potential: Exploring the nexus between low-carbon digital economy and regional economic-social development in China

In 2020, China formally proposed the goal of achieving carbon peaking in 2030 and achieving carbon neutrality in 2060. Since then, widespread attention has been devoted to determining when and how this goal will be achieved. This paper creatively puts forward the view of low-carbon digital economy from the perspective of resource flow, digital flow and energy flow, and studies the synergy effect of low-carbon digital development by constructing the synergy model of low-carbon digital development economic and social development. Based on theoretical research, this paper constructs a synergy model and evaluation index system between low-carbon digital development and economic and social development, and an empirical analysis was conducted based on data related to regional low-carbon digital development and economic and social development in China from 2014 to 2019. The empirical results show that the development of China's low-carbon digital economy is the main driving force for future economic and social development. The effects of low-carbon digital economy on economic and social development varied across regions due to their different regional development patterns. The spatial pattern shows a trend of “high in the east and low in the west”. Further, if the low carbon economy and the digital economy included in the stimulus policies can play a synergistic role, it will be able to play the greatest role in promoting economic and social development. And such a scenario is used as a practice in different regions of China in future. The research conclusion of this paper enriches the discussion on the construction of ecological civilization and the construction of a community with a common future for mankind.

Analysis of spatiotemporal changes and driving factors of blue-green space in six metropolitan areas of the Yangtze River Delta based on the PLUS model

This study aims to examine the evolution of blue-green space and urban development in the Yangtze River Delta region using Arcgis spatial analysis, landscape pattern index, and PLUS model to inform urban planning and environmental protection efforts. The results indicate that:1) Blue space in the region's six metropolitan areas initially increased, then decreased significantly from 2000-2020, while green space continued to decline. However, recent environmental policies have mitigated this trend. 2) Improved living standards have led to increased green space within cities, but construction land occupation has reduced green space outside of cities. 3) Blue-green space is becoming more fragmented, scattered, and homogenized in shape, and that economic development influences green space, while different regional development patterns impact blue space. 4) Socioeconomic and natural factors both drive blue-green space to change. There is a "dual desirability" between blue-green space protection and urban development. In conclusion, the scale and landscape pattern of blue-green space have changed significantly in the last 20 years, which are greatly influenced by urban development, and the blue-green space differences among metropolitan areas are obvious. Therefore, it is necessary to protect and optimize the blue-green space pattern of the metropolitan areas.

Impact of high-speed railway construction on spatial patterns of regional economic development along the route: A case study of the Shanghai–Kunming high-speed railway

The Shanghai–Kunming high-speed railway spans the eastern, central, and western regions of China and is an important "horizontal" in the "eight vertical and eight horizontal" railway network of China. This paper estimates the direct impact of opening a high-speed railway on the spatial patterns of regional economic development along the route by integrating GIS technology, spatial panel data models, and the entropy method. The results show that the high-speed railway can significantly increase the economic aggregate and urbanization rates along the route and promote the upgrading of industrial structures, but it has a limited effect on the economic growth rate, showing a weak trend. In terms of spatial patterns, the high-speed railway significantly improves regional accessibility, the strength of economic ties, and economic potential along the route. The regional economy is characterized by weak spatial agglomeration and presents a trend of balanced development. In general, although the economic effect of HSR for the economically lagged regions is smaller in the short term than that in the economically and less economically developed regions, the high-speed railway has the greatest impact on regional economic development and spatial patterns in economically backward areas, thus the economically backward regions have a greater posterior advantage, which is conducive to balancing regional economies and narrowing regional differences.

Regional Drinking Water Supply in Pakistan: Regional Disparity, Inequality, and Development Pattern

This article explores the regional disparities in water supply coverage in Pakistan in the context of intraregional development patterns. We applied the Gini index, Esteban and Ray index, and Moran’s I to measure regional development patterns in terms of inequality, polarization, and spatial concentration and build an integrated framework combining them with other widely accepted factors to understand regional differences in water coverage quantitatively. Our results show that improved water (tap and pump water) is more widely supplied in Pakistan with lower inequality but higher spatial concentration than tap water supply coverage, although the patterns differ by urban–rural divisions and provinces. Western regions with smaller populations tend to have higher tap water coverage, and eastern regions with large populations are more covered by improved water. The regression models show various mechanisms of improved water and tap water coverage. Both are related to local economic conditions but tap water coverage is more related to local environmental conditions, and improved water is more related to local demographic conditions. Strong and dense population centers decrease improved water coverage but promote tap water coverage. Urban planners and policymakers should address polycentric regional development to fulfill various development targets and improve regional equity of drinking water coverage in terms of accessibility, availability, and quality.

Nighttime light data‐based analysis of spatiotemporal patterns evolution and driving forces of economic development in China at prefecture level (1992–2020)

AbstractIntercity lighting data are an important resource for studying spatial and temporal patterns in regional urban development as an indicator of the intensity of urban social and economic activity. Understanding the evolutionary characteristics of the spatial pattern of regional economic development can support decision‐making in regional economic coordination and sustainable development strategies. Based on a long time series of nighttime lighting data from 1992 to 2020, this study used the Theil index, Markoff transfer matrix, spatial autocorrelation, and spatial regression to analyze spatiotemporal evolutionary characteristics and drivers of urban economic development in China. The study found that from 1992 to 2020, China's economic development hot spots have been concentrated in highly developed urban agglomerations namely the Beijing–Tianjin–Hebei region, Shandong Peninsula, Yangtze River Delta, and Pearl River Delta. Cold spots were mainly concentrated in the central‐west and southwest of the country. The economic growth rate shows an opposite spatial pattern, which demonstrates the effectiveness of the national coordinated development strategy for regions. The Theil index for urban economic development in China shows an overall downward trend, and the overall economic disparity is mainly due to the relatively low economic development of Tibet, Xinjiang, Gansu, and other western provinces. Therefore, regional economic development remains significantly uneven. In China, the economic type of cities is relatively stable, and the probability of leapfrogging types is low; however, the level of cities with high resource dependence or a single economic structure easily downgrades. The level of economic development and the related socioeconomic factors of neighboring cities influence an obvious spatial spillover effect in the development of urban economies in China. The pattern of China's urban economic development is mainly affected by innovation capacity, financial support, capital investment, transportation infrastructure, and industrial structure.