Spatial Differentiation Characteristics Research Articles

Identification and Spatial Characterization of suburban areas in Chengdu

As transitional territories where urban and rural functions interpenetrate, suburban areas have multiple values such as recreation, ecology, agriculture and landscape. Promoting their benign development is the key to realizing global sustainable development of urban and rural areas. Planning control is based on precisely defining the spatial extent of suburban areas, and understanding suburban area differentiation and its driving forces scientifically is a key component in raising the bar for focused planning. However, there are currently few research on fine-scale quantitative identification of suburban regions because of their spatial complexity, ambiguous boundaries, and structural dynamic features. Based on this, this paper develops a multi-dimensional identification index system for suburban areas by using multi-source big data and remote sensing information technology, employs the random forest model and the K-Medoids clustering algorithm, identifies the distribution of suburban areas and their subdivided types, analyzes spatial differentiation characteristics, and conducts empirical research using Chengdu City as an example. The findings demonstrate that: (1) The majority of suburban areas in Chengdu City are concentrated in groups or belts surrounding the urban centers of various districts and counties, and the higher the functional class of a district or county, the denser the distribution of suburban areas. (2)The distribution pattern of suburban areas in Chengdu basically conforms to its planned urban hierarchy system.(3)Urban-oriented, suburban-interacted and rural-oriented suburban areas have their own characteristics in land use level, economic development and regional population characteristics.(4)Regional openness, government behavior, social development and geographical location are the core driving factors of spatial differentiation of suburban areas in Chengdu, and the interaction between urban and rural systems, the flow of social resources and the transformation of development models are the spatial mapping dimensions that affect its differentiation.(5)Chengdu can draw up detailed regulatory planning of suburban units to standardize and guide the overall development of suburban areas. In support of the global sustainable development goals, this study offers a methodology for precisely and impartially defining suburban areas, assisting in the implementation of integrated urban-rural development globally.

Simulation of Spatial and Temporal Variations in the Water Yield Function in the Source Area of the Yellow River and an Analysis of Influencing Factors

The Yellow River source area is an important eco-fragile and sensitive zone in the northeast of the Tibetan Plateau, where anthropogenic disturbances, climate change, and environmental problems have negatively affected the amount of water in the basin, which directly impacts the ecological security and high-quality sustainable development of the Yellow River Basin. Therefore, this study takes the Yellow River source area as its research area. Based on eight periods of land use from 1985 to 2020, topographic, soil, and meteorological data are combined, and a locally modified InVEST model and geological detector method are used to simulate watershed water production, evaluate the spatial differentiation characteristics of watershed water production, and analyze its spatial heterogeneity attribution. The results revealed that water production from 1985 to 2020 varied within the interval of 152.08–302.44 billion m3, with alternating decreases and increases and an overall upward trend. In the spatial distribution, the depth of water production is high in the east and low in the west, and the high-water-production area is concentrated in the counties of Maqin and Gande. In the vertical gradient, the water production capacity is strengthened with increasing altitudes. The spatial differentiation of the water production service and degree of influence is jointly determined by multiple factors. In this work, the parameter Z of the InVEST model was locally corrected to increase the applicability of the Z value to the Yellow River Basin to improve the accuracy of the simulation results, and the spatiotemporal differences in water yield from multiple perspectives were analyzed to provide a scientific basis for the ecological protection and high-quality sustainable development of the Yellow River Basin.

Exploring the temporal-spatial characteristics and determinants of high-quality development of city clusters in China

The complexity, severity, and uncertainty of the international situation have prompted the development of city clusters to focus more on resilience and the building of infrastructures and safeguards. Chinese-style modernization proposes a new realization path for the high-quality development (HQD) of city clusters, based on which an evaluation system for HQD indicators of city clusters is constructed. We also measured the HQD levels of 19 city clusters from 2011 to 2021 and analyzed their spatial differentiation characteristics, agglomeration evolution characteristics, and influencing factors by using kernel density, standard deviation ellipse, Moran's index, geographic detector, and geographically weighted regression. The study revealed that (1) the overall level of HQD of China's city clusters shows a trend of continuous growth, and there is obvious polarization in the high quality of city clusters in different regions. (2) The spatial distribution of HQD in city clusters decreased in the "East, Center and West" direction, but the spatial patterns of "Southeast highlighting" and "Northwest rising" became more obvious. (3) The HQD of city clusters shows obvious spatial agglomeration characteristics and overall presents a spatial pattern of "hot in the east and cold in the west", with the scope of the cold spot area gradually shrinking, and the hot spot area tends to spread outward, with mature city clusters at the core. (4) The influencing factors of HQD in Chinese city clusters are diverse, with financial levels, digital economics, human capital and green innovations having decreasing influence on HQD in city clusters but showing an obvious two-factor enhancement trend, with financial levels being able to effectively stimulate the driving potential of other factors. Financial levels can effectively stimulate the driving potential of other factors. (5) The coefficients of the driving factors affecting the HQD of city clusters vary significantly spatially, with human capital, financial levels and green innovations showing a north‒south hierarchical banded distribution of "high in the south and low in the north", and digital economy shows an east-west hierarchical belt distribution of "high west and low east". Based on the above conclusions, the realization path of accelerating the HQD of China's city clusters is proposed by optimizing the functional division of labor of the city clusters, giving full play to the comparative advantages of the hinterland city clusters, and relying on the high level of the city clusters for opening up.

The Spatial Differentiation Characteristics and Influencing Mechanisms of Intangible Cultural Heritage in China

Intangible cultural heritage represents a cultural evolution shaped by human responses to adapting and transforming environments. Unveiling the characteristics and patterns of its spatial distribution can offer a more scientific foundation for the protection of intangible cultural heritage and the development of heritage tourism. By using ArcGIS software and Geo-detector, the regional differentiation characteristics and influencing mechanisms of Intangible Cultural Heritage, specifically the Hometown of Chinese Folk Culture and Art (HCFCA), have been investigated. Results show that the distribution and structure of HCFCA in China vary significantly across regions and categories. Eastern China holds the highest number, while Southern China has fewer. Traditional fine arts and dance dominate, with folk literature being less represented. HCFCA exhibits a clear clustering trend, reflecting a "Polycentric Agglomeration" pattern, particularly in traditional drama, calligraphy, craftsmanship, sports, performing arts, and acrobatics. The study presents an influential mechanism model, with the natural environment as foundational, economic development as the primary driver, social development as supplementary support, and historical background as a catalyzing factor. This understanding not only enriches theoretical insights but also provides a scientific basis for the protection of intangible cultural heritage and the development of heritage tourism.

Measuring ecological well-being based on the degree of ecosystem service supply and demand matching in Shenzhen, China

Measuring urban ecological well-being and achieving a comprehensive understanding of its spatial differentiation characteristics are important foundations for meeting the growing health needs of residents and improving the insufficient and unbalanced development of the urban ecological environment. However, the current framework for defining urban ecological well-being that considers the supply and demand of ecosystem services (ESs) is unclear. The key to enhancing urban ecological well-being lies in measuring the level and patterns of ecological well-being in urban spaces through the degree of ES supply–demand matching; therefore, the present study aims to construct a measurement framework for urban ecological well-being based on this matching. The developed framework was applied to assess ecological well-being in Shenzhen in 2015 and 2020. This study summarizes the spatial patterns and analyzes their temporal and spatial distributions and influencing factors, showing that: (1) the spatial distribution of the comprehensive supply and demand of ESs in Shenzhen both have strong spatial heterogeneity; (2) the area of four types of relatively low ecological well-being patterns in Shenzhen was greater than that of five types of relatively low ecological well-being patterns in 2020, and the proportions of the areas of low, relatively low, and relatively sufficient well-being were the largest; (3) the overall trend of ecological well-being change is one of decline. The area in which Shenzhen’s ecological well-being has declined is far greater than the area in which it has improved. The main reasons for this are the increase in the urban vitality index, an increase in the demand for ESs, and an increase in impermeable surfaces, which have led to a decrease in the supply capacity of the ecosystem in some areas.

Spatial Differentiation and Influencing Factors of Available Potassium in Cultivated Soil in Mountainous Areas of Northwestern Hubei Province, China

This research was conducted based on 701 soil sampling points in cultivated land (0–20 cm) in Shiyan, a mountainous area in northwest Hubei Province, China. The methods of classical statistics, geostatistics, and geodetector were used to explore the spatial differentiation characteristics and influencing factors of soil available potassium (AK) in cultivated land in Shiyan. The results showed that the soil AK content in the study area ranged from 17.00 to 350.00 mg/kg, with an average value of 118.95 mg/kg and a coefficient of variation of 54.06%, exhibiting moderate variability. The spatial structure was well fitted by a spherical model; the block gold effect was 0.027, indicating strong spatial autocorrelation; and spatial variation was mainly caused by structural factors. The spatial differentiation characteristics of the soil AK content are obvious; overall, there was a spatial distribution pattern of high in the northeast and low in the southwest. The factor detection results show that soil pH plays a dominant role in the spatial variation in soil AK in the study area, followed by parent material and annual average temperature. The interaction detection results show that each environmental factor exhibits non-linear or dual factor enhancement between factors, with soil pH slope ranking first in explanatory power. The explanatory power of the interaction between soil pH, parent materials, annual average temperature, and other factors dominates. In the process of the fine management of soil AK in cultivated land in the study area, when considering the influence of dominant factors, the impact of the interaction of various factors on the spatial variation in soil AK should also be taken into account. This study could provide a theoretical reference for improving the soil and farmland improvement, improving farmland quality in this area.

Retrieval performance of mangrove tree heights using multiple machine learning regression models and UAV-LiDAR point clouds

ABSTRACT Mangroves are vital coastal ecosystems that provide crucial links between land and sea. Tree height is a key indicator for assessing mangroves’ health status. Currently, there are still numerous challenges in estimating mangrove tree height. In this study, multiple deep learning and shallow machine learning regression models were developed to accurately estimate mangrove tree height using multi-dimensional Light Detection and Ranging (LiDAR) point clouds and their derivatives. We constructed a novel CNN_RepMLP model for mangrove tree height mapping. We also further verified the applicability of different types of regression models in estimating mangrove tree heights, and explored the influence of different LiDAR-derived features on the inversion accuracy for tree heights. The results indicated the following: (1) The CNN_RepMLP displayed satisfactory performance in the inversion of mangrove tree heights, and exhibited better robustness and generalization ability than the convolutional neural network (CNN) model. (2) Among the different LiDAR-derived feature combinations, combining height variables with intensity variables can not only mitigate the negative impact of height variables on inversion models, but also enhance the mangrove tree height inversion accuracy. (3) The ensemble learning framework with ExtraTrees as the meta-model can make better use of the differences and complementarities between different single base models, and exhibited better accuracy in estimating the height of mangrove trees compared with other ensemble learning models. (4) Multiple machine learning models based on multi-dimensional UAV-LiDAR point-cloud-derived features are suitable for the inversion of mangrove tree height. The CNN_RepMLP model outperformed the CNN and stacking ensemble learning models and had more detailed differentiation in terms of mangrove tree height. Its prediction results can more realistically reflect the spatial differentiation characteristics of mangrove tree height.

Exploring the pattern and influencing factors of ecosystem services under multiscale perspective: implications for ecosystem services management

It is necessary to explore the spatial pattern and influencing factors of ecosystem services (ESs) to ensure the sustainability of ecosystems. However, research on ESs and their influencing factors across various spatial scales is scarce and is often restricted to a single scale. Water yield, soil conservation, carbon storage, and habitat quality were simulated with the InVEST model at multiple scales. The complex relationship between ES pairs was analyzed. Based on this, the Geographical Detector Model was used to reveal the influencing factors of the ESs, and the Geographically Weighted Regression was used to study the characteristics of local spatial distributions of the main influencing factors. The results indicated that: First, ESs showed prominent spatial differentiation characteristics at different scales. With the increase in spatial scale, the distribution of multiple ESs tended to become uniform and clustered. Then, the relationships between ESs were sensitive to alterations in the spatial scale of the evaluation unit, and the relationships of ESs changed with increasing scale. Finally, individual ES and total ecosystem service were subject to the combined effects of natural and social factors, and the level of influence of each influencing factor on ESs varies considerably at different spatial scales. The study can give guidance for policy decision-makers to conduct differentiated regional management.

Spatiotemporal Evolution of Urban Land Green Utilization Efficiency and Driving Factors: An Empirical Study Based on Spatial Econometrics

Green development is an inevitable choice for sustainable development under the constraints of environmental resources. This paper attempts to explore the connotation of urban land green utilization efficiency (LGUE) and reveal its spatial differentiation characteristics. This study adopts the super-SBM model to measure LGUE from 2009 to 2022 and analyzes the spatiotemporal variation rules. Then, the study reveals the spatial influencing factors of LGUE, drawing the following conclusions: (1) the average efficiency value of LGUE at the national level is still at a low level, but it is on an upward trend. There are significant differences in LGUE among the eastern, central, and western regions, with the highest LGUE in the eastern region and the lowest in the western region. (2) The spatial distribution of LGUE in various cities across the country is not entirely random but shows significant spatial autocorrelation characteristics. The improvement in LGUE in a region can improve the surrounding region's LGUE. (3) Economic development level promotes the improvement of local city LGUE, but its impact on LGUE of surrounding neighboring cities is not significant; local city industrial structure upgrading can improve LGUE in both local and neighboring cities; foreign investment in local cities can promote LGUE in both local and neighboring cities; the increase in population density will hinder LGUE in local cities but improve surrounding cities LGUE. The intervention degree of local city government will suppress the improvement of LGUE in both local and neighboring cities.

Evolvement of Spatio-Temporal Pattern and Driving Forces Analysis of Ancient Trees Based on the Geographically Weighted Regression Model in Guangzhou and Foshan, China

Ancient trees play an important ecosystem service role in high-density cities, revealing the zonal distribution characteristics of vegetation under climate influence. The ancient trees in Guangzhou and Foshan in 2018 and 2023 were taken as study objects to explore the evolution of their spatio-temporal patterns and to analyze the spatial differentiation characteristics of their driving factors using the geographical weighted regression (GWR) model. The results showed the following: (1) The ancient trees in Guangzhou and Foshan were composed of typical subtropical evergreen broad-leaved forest communities, mainly represented by broad-leaved species of evergreen dicotyledonous plants. The dominant species mainly included Litchi chinensis, Ficus microcarpa, Canarium pimela, Ficus virens, and Dimocarpus longan. However, there was a significant difference between Guangzhou and Foshan. (2) The number of ancient trees in Guangzhou showed negative growth, while Foshan saw a significant increase. However, species diversity in both areas increased, with the highest diversity in the northeast, higher diversity in the south-central part, and lower diversity in the western and northwestern parts. (3) The maximum kernel density of ancient trees in Guangzhou and Foshan differed 22-fold, indicating a spatial distribution pattern of multiple clusters. (4) The GWR model effectively explained the driving factors of the heterogeneity of the spatial distribution of ancient trees. The results showed that artificial disturbance was the most important factor affecting the spatial distribution of ancient trees in high-density urban agglomerations in the same vegetation zone. The study clarified the characteristics of the spatial distribution and species diversity of ancient trees in the region, revealed the driving factors for the evolution of the spatial pattern of ancient trees in highly urbanized areas, and provided guidelines for policies and measures for enhancing biodiversity and conserving germplasm resources in the region.

Spatial differentiation characteristics of the Hemiptera insects in China.

The Hemiptera insects are the largest incomplete metamorphosis insect group in Insecta and play a vital role in ecosystems and biodiversity. Previous studies on the spatial distribution of Hemiptera insects mainly focused on a specific region and insect, this study explored the spatial distribution characteristics of Hemiptera insects in China (national scale), and further clarified the dominant factors affecting their spatial distribution. We used spatial autocorrelation analysis, hot spot analysis, and standard ellipse to investigate the spatial distribution characteristics of Hemiptera insects in China. Furthermore, we used geographic detectors to identify the main factors affecting their spatial distribution under China's six agricultural natural divisions and explore the influencing mechanism of dominant factors. The results show that: (i) The spatial differentiation characteristics of Hemiptera insects in China are significant, and their distribution has obvious spatial agglomeration. The Hu Huanyong Line is an important dividing line for the spatial distribution of Hemiptera insects in China. From the city scale, the HH type (high-high cluster) is mainly distributed on both sides of the Hu Huanyong Line. (ii) The hot spots of Hemiptera insects are mainly distributed in southwest China, along the Qinling Mountains, the western side of the Wuyi Mountains, the Yinshan Mountains, the Liupanshan Mountains, the Xuefeng Mountains, the Nanling Mountains, and other mountainous areas. (iii) Under agricultural natural divisions, the influence of natural environmental factors on the spatial distribution of Hemiptera insects is obviously different. Temperature and precipitation are the dominant factors. Natural factors and socio-economic factors have formed a positive reinforcement interaction mode on the spatial distribution of Hemiptera insects. These can provide the decision-making basis for biodiversity conservation and efficient pest control.

Spatio-temporal Differentiation of County Carbon Budget and Territorial Space Optimization Zoning Strategy in Gansu Province from the Perspective of Carbon Neutrality

Under the background of comprehensively practicing the overall system concept of the "living community" in the new era, incorporating the carbon neutral development goal into the territorial spatial planning and construction and establishing the territorial spatial pattern and optimization strategy in line with the actual development of Gansu Province are of great significance for promoting the comprehensive green low-carbon transformation and high-quality development of regional economy and society. Taking counties in Gansu Province as an example, based on the perspective of carbon neutrality research, the land use carbon budget of 87 counties in Gansu Province in 2010, 2015, and 2021 was calculated and analyzed. GIS spatial analysis and social network analysis were used to further explore their spatial differentiation characteristics and the overall characteristics of the carbon emission spatial correlation network. At last, combined with the main function zoning, the low-carbon oriented land space optimization zoning was carried out, and differentiated low-carbon development strategies were proposed. The results were as follows： ① Carbon emissions in Gansu Province showed an upward trend, but the increase rate decreased, showing a spatial distribution of "high in the central and eastern part of the country, low in the southwest." Construction land was the main carbon source. The carbon uptake showed a spatial distribution of "high in the south and low in the north, high in the west and low in the east." Woodlands were the main carbon sinks. The net carbon emissions showed an increasing trend, and approximately 58.62% of the counties in the province were in a carbon imbalance situation. ② In 2021, the spatial network of county carbon emissions was closely related, showing a "core-edge" pattern. The Chenguan District and Qilihe District were in the core position of the network and received more correlation relationships in the network. The network contacts in Longzhong area were frequent, followed by the contacts in Longdongnan area. ③ Based on carbon emissions, carbon sequestration, and ecological carrying capacity coefficients and using the results of spatial correlation of social networks as role positions, the province was divided into four carbon-neutral sub-districts. At the same time, superimposed analysis of the main function zoning, the county area of the province was reconstructed into seven territorial space zones, and the differentiated regional low-carbon optimization development strategy was proposed for each zone.

Spatial Differentiation Characteristics and Influencing Factors of Surface Soil Cd in Karst Plateau Area of Guiyang City

In order to explore the spatial differentiation characteristics and variation law of soil Cd content in a high geological background area, 14 421 topsoil samples were collected from topsoil in the karst area of Guiyang City. Global Moran's I index, cold hot spot analysis, semi-variance function, and Kriging interpolation were used to reveal the spatial structure and distribution law of soil Cd content. The influence of environmental factors on soil Cd content and its main controlling factors were analyzed through analysis of variance and geographic detector. The results showed that： ① The Cd content of karst surface soil in Guiyang varied from 0.03 to 1.36 mg·kg-1, with an average of 0.440 mg·kg-1, which was 1.77 times and 5.95 times the Guizhou soil Cd background value and Chinese soil Cd background value, respectively. The over-standard rate of soil Cd was 30%, which was 4.29 times that of 7% of soil Cd in China. ② There was a significant spatial positive correlation of soil Cd content, showing an aggregation trend in the global space, whereas in the local region, the northeast and southwest were hot spots, and the north was a cold spot. The nugget coefficient of soil Cd content was 10.37%, indicating that soil Cd was mainly affected by structural factors. ③ In terms of spatial distribution, soil Cd showed different accumulation trends. In some massive soils, such as Xifeng County, Xiuwen County, Qingzhen City, Huaxi District, and Nanming District, the soil ω（Cd）was less than 0.3 mg·kg-1. The soil ω（Cd）was between 0.3 and 0.6 mg·kg-1,and soil Cd in Baiyun District, Wudang District, Guanshan Lake area, and Yunyan area as a whole lied within this range. The soil ω（Cd）between 0.6 and 0.9 mg·kg-1 was concentrated in the southwest of Qingzhen City, the south of Huaxi District, and the north of Kaiyang County, whereas soil ω（Cd） between 0.9 and 1.2 mg·kg-1 was mainly concentrated in the southwest of Qingzhen City. The extreme value of soil Cd content （ > 1.2 mg·kg-1） was mostly distributed in Kaiyang County, Xiuwen County, Qingzhen City, and Huaxi District. ④ The results of analysis of variance and geo-detector showed that different environmental factors had significant effects on the spatial differentiation of soil Cd, but their explanatory power on soil Cd content varied： stratum （0.176 5） > soil type （0.026 0） > organic matter （0.025 1） > altitude （0.010 5） > parent rock （0.007 3） > land use （0.006 4） > pH （0.001 3）, and the interaction between stratum and arbitrary environmental factors was the greatest. Therefore, stratum was the main factor affecting the spatial differentiation of soil Cd content.

Spatial Differentiation Characteristics, Driving Mechanisms, and Governance Strategies of Rural Poverty in Eastern Tibet

Rural areas in Tibet, with its complex terrain, fragile ecology, and poor facilities, are subject to a combination of social–ecological system elements, facing the typical risks of recurrent, marginal, and potential poverty. At present, the spatial differentiation and driving mechanism of rural spatial poverty risk in Tibet are not clear, which adversely affects the formulation of differentiated and precise governance strategies. Thus, based on the social–ecological system perspective, 967 poor rural villages in eastern Tibet were taken as an example, using intelligent techniques such as random forest, geographic detector, and multi-scale geographically weighted regression to identify the spatial differentiation characteristics and the driving mechanism of poverty. The results indicated that (1) the high poverty incidence of rural areas in eastern Tibet showed a scattered block distribution, of which approximately 37% of the villages presented a spatial distribution characterised by a high degree of clustering of the high poverty incidence. (2) Topography and the level of public facilities were key factors influencing the poverty levels of rural areas in eastern Tibet, in which the coupling explanatory power between the construction land slope index (CLSI) and several poverty-causing factors was high. (3) Geological disaster, land surface temperature, CLSI, traffic accessibility, livestock resources, cropland per capita, and tourism resources differentially drove the poverty incidence of rural areas in eastern Tibet, forming spatial partitions dominated by the risks of potential, marginal, and recurrent poverty. For different partitions, differentiated governance strategies of upgrading ecological environments, optimising geographical locations, and revitalising social resources were proposed to provide references for solving the problem of relative poverty in the new period.

Spatial differentiation characteristics of selenium in Se-rich yellow soils developed from black shale and coal bearing formations in Guizhou Province

Spatial differentiation characteristics of selenium in Se-rich yellow soils developed from black shale and coal bearing formations in Guizhou Province

Research on Traditional Village Spatial Differentiation from the Perspective of Cultural Routes: A Case Study of 338 Villages in the Miao Frontier Corridor

The traditional villages in the Miao Frontier Corridor are the products of migrations, social interactions, and transportation, as well as production interchanges between the central plains and the frontiers of China in ancient times. They have made significant contributions to local multicultural inheritance and regional social development. However, with the increasing pressure of heritage conservation and sustainable development, there is growing attention on how traditional villages can tap into their cultural continuity and distinctiveness. This study introduces the concept of cultural routes, with the aim of integrating traditional villages of different ethnicities, regions, and characteristics from the perspective of diversity. It analyzes their spatial differentiation characteristics and the factors influencing them, providing basic support for the overall protection of traditional villages with special characteristics. Following this idea, 338 remaining traditional villages in the Miao Frontier Corridor were selected as the research objects. With the help of 91-satellite maps and a geographic information system (GIS), a cultural and geographic database of the traditional villages in the Miao Frontier Corridor was constructed to objectively explore the roles of the traditional villages’ natural geography, historical, and humanistic elements in the spatial categorization on a large scale. This study shows that the spatial distribution of the traditional villages in the Miao Frontier Corridor is uneven, exhibiting a cluster structure with of a “single primary nucleus with multiple secondary nuclei”. The spatial differentiation of traditional villages exhibits a similar clustering pattern based on individual natural geographic factors, such as elevation, mountain undulation, slope, and water systems. Additionally, there is discernible regularity concerning historical and humanistic factors, such as ethnicity type, age of village establishment, and the presence of guard stations. Further exploring the micro-spatial level, the natural geographical environment serves as the structural foundation of traditional village space, while the historical and humanistic environment fosters multiple differentiations in traditional village space in terms of influencing factors. Together, these factors jointly influence the spatial differentiation of traditional villages. This study enriches the dynamic aspects of linear cultural heritage preservation and also provides new insights into the specialized development within the overall protection of traditional villages.

Spatio-Temporal Evolution and Driving Mechanism of Coupling Coordination of Pseudo Human Settlements in Central China’s Urban Agglomerations

The construction of pseudo human settlements in the context of “digital-real integration” in the information age is crucial for the high-quality development of human settlements in the new era. This study aimed to investigate the spatio-temporal evolution of the pseudo human settlements and its mechanism to provide new ideas for scientific breakthroughs in cross-disciplinary fields, such as human settlements, and to provide a strong basis for promoting the overall improvement of the quality of the human settlements in the central China’s urban agglomerations in the new era. Employing the theoretical framework of “three states” in human settlements, this study utilizes big data, including tourism, shopping, work, and socialization, to investigate the dynamic patterns and driving mechanisms of pseudo human settlements within Central China’s urban agglomerations from 2011 to 2021, employing methodologies such as the coupling coordination model, standard deviation ellipse, kernel density, and gray correlation degree. The results show the following: (1) the overall pseudo human settlements in central China’s urban agglomerations exhibit a pattern of “high coupling and low coordination”. (2) The overall coupling degree exhibits a fluctuating upward trend and has been at a high coupling-state level. (3) The degree of coupling coordination has obvious spatial differentiation characteristics, such as the core circle, “tower”, and “two main and one secondary” core structure. (4) The overall level of pseudo human settlements is influenced by the combination of time, space, and the multidimensionality of systems and indicators. This study conducted research on pseudo human settlements to enrich the theory of the human–land interaction relationship in geography and reflect the decision-making needs in the strategy of network power.

Spatial patterns and influencing factors of takeaway consumption in 56 cities in China

With the development of the digital economy, the takeaway industry is expanding rapidly. To realize the high-quality development of the takeaway sector, it is necessary to understand the spatial differentiation characteristics of takeaway consumption in Chinese cities and its influencing factors. To this end, we quantitatively studied the spatial distribution of takeaway consumption in 56 cities. We used the number of takeaway orders (copies/person) and the per capita takeaway consumption amount (RMB/person) in major Chinese cities in 2019 to characterize takeaway consumption in China. We investigated the driving mechanisms and factors affecting takeaway consumption amounts per capita and order per capita in China. The results show that takeaway consumption amounts per capita and order per capita is higher in East China than in North and Central China. The tertiary industry population ratio is crucial to takeaway consumption amounts per capita and order per capita in major Chinese cities. Amounts and orders increase as the tertiary industry population ratio rises. Factors affecting takeaway consumption amounts per capita and order per capita in Chinese cities of different population sizes vary. The working-age population ratio heavily influences the takeaway consumption amounts per capita and orders per capita in megacities. Additionally, internet penetration and average annual temperature play a significant role in takeaway consumption amounts per capita and orders per capita in megalopolis. In big cities Ⅰ, the road capacity per capita and GDP per capita are the main factors affecting takeaway consumption amounts per capita and orders per capita. The tertiary industry population ratio is the core factor that determines takeaway consumption amounts per capita and orders per capita in big cities Ⅱ. The interaction between natural and socio-economic factors dramatically increases the impact of takeaway consumption amounts per capita and order per capita in Chinese cities. In conclusion, this study provides a macro-level insight into the spatial characteristics and development factors of takeaway consumption in major Chinese cities. This knowledge is crucial for promoting the takeaway economy's sustainable development and realizing the takeaway industry's green transformation.

Analysis of the spatial–temporal evolution and driving factors of carbon emission efficiency in the Yangtze River economic Belt

As an important economic growth pole and ecological area in China, the urban agglomeration of the Yangtze River Economic Belt (YREB) is the key to carbon emission reduction. Exploring the spatial–temporal evolution and driving variables of its carbon emission efficiency (CEE) is crucial for realizing the goals of carbon peaking and carbon neutrality. The super-efficiency SBM model, the nuclear density method, and the spatial autocorrelation method were used to discuss the spatial–temporal CEE characteristics of 105 cities in the YREB. On the driving factors of carbon emissions, the geographic detector and the Tobit model were combined to explore the spatial differentiation characteristics of the driving factors from the perspective of heterogeneity, and concurrently analyze the single-factor’s effecting intensity and impacting direction, as well as the dual-factors’ interaction effects. The findings indicated that the CEE of YREB generally showed a slow upward trend during 2006–2021. From the perspective of time dynamic evolution, the differentiation of efficiency intensified, and the overall development was toward the high efficiency level. Furthermore, the results of spatial pattern evolution showed that the CEE presents the pattern of “downstream areas > midstream areas > upstream areas”, “high in the east and low in the west”, “hot in the east and cold in the west”, while the spatial clustering effect was significant, showing the distributions of low-low clustering or high-high clustering. Moreover, the results of the geographic detector showed that government intervention, economic growth, and technological progress were the main driving factors. In addition, the interactions government intervention and the other factors were significantly detected. Tobit regression results showed that technological advancement and economic growth had a favorable impact on CEE, but foreign investment, urbanization, and government involvement had negative impacts. In the future, the correlations between provinces and cities should be strengthened and amplified to promote the integrated green development, as well as to improve the ecological environments.

Analysis of the Current Situation of Sustainable Development of the Yangtze River Economic Belt based on SDGs

This paper evaluates the level of sustainable development of 11 provinces and cities in the Yangtze River Economic Belt from 2011 to 2020, and analyzes its spatial and temporal differentiation and trend evolution characteristics. This paper adopts the coupling coordination model based on CRITIC-entropy weight combination weight, spatial autocorrelation model, spatial Markov chain and other methods, based on the measurement indicators of the United Nations Sustainable Development Goals, and conducts a comprehensive evaluation from four aspects: innovation-driven, welfare guarantee, resources and environment, and economic development. The research results show that the sustainable development level of the Yangtze River Economic Belt presents the characteristics of continuous improvement, regional difference, hierarchical leap, spatial dependence, spillover effect, etc. According to the research findings, this paper puts forward some suggestions, such as strengthening regional coordinated development, optimizing spatial planning and governance, coordinating policies and work, promoting rule of law and innovation, etc., aiming to promote the high-quality development of the Yangtze River Economic Belt, achieve the coordinated development of economy, society and ecology, and localize the SDGs. This paper’s research has important theoretical significance and practical value for deeply understanding the current situation and problems of sustainable development of the Yangtze River Economic Belt.