Accurately understanding the connotation and meaning of ecological interests in national territory space, explore the mechanism of the allocation of ecological benefits in national space, is the foundation for resolving spatial conflicts and optimizing the pattern of national territory space development and protection. Research has shown that: 1) The naturally formed spatial environment and the profit-seeking human mechanism, the market mechanism that plays a decisive role in resource allocation, and the policy mechanism for correcting market failure jointly affect the mechanism of ecological interest allocation in territory space. 2) The function of ecological benefit allocation in national territory space is to implement the structure of national land spatial planning, ensure the spatial redistribution of ecological benefits, and correct the profit seeking nature of market mechanisms. 3) The standardized spatial structure, rational allocation of public resources, and effective allocation of spatial rights are the predetermined benchmarks for ecological benefit allocation. At present, the spontaneous allocation of ecological interests in national territory space is characterized by prominent competition in spatial use, numerous misallocations of spatial resources, unequal spatial rights, and hidden concerns about the imbalance of secondary allocation boundaries. It is necessary to define the bottom line boundary of the ecological carrying capacity of the “three lines and one order” and the upper limit boundary of constraining government power for the allocation of ecological interests in national territory space, optimize the collaborative mechanism of ecological interests allocation in national territory space, reasonably allocate ecological interests at different spatial scales, and achieve the universal sharing of ecological interests.
Branched glycerol dialkyl glycerol tetraethers (brGDGTs) produced by microorganisms such as bacteria are important tools for reconstructing past climatic and environmental changes. However, previous works on brGDGTs mainly focus on various proxies based on their distributions, whereas environmental controls on their concentration remains unclear. This hampers our proper understanding on the climatic significance of brGDGT concentration in geological records as well as the seasonality of brGDGT proxies. This study investigated brGDGT concentration in surface soils in different regions of China and analyzed its correlations with environmental factors. The aims were to: 1) Explore environmental controls on soil brGDGT concentration, 2) Verify whether soil brGDGT concentration can be used as a paleoclimatic proxy, and 3) Clarify the seasonal bias of brGDGT-based paleotemperature proxies in soils. Totaling 273 natural soils were collected during 5 fieldtrips from 5 regions including: the Chinese Loess Plateau and its surroundings, North China to Northeast China, South China, the Shandong Peninsula, and the Northeast Tibetan Plateau. The correlations between brGDGT concentration and aridity index (AI), soil pH, and mean annual air temperature (MAAT) were analyzed. For the whole surface soil dataset, brGDGT concentration showed stronger correlations with AI and soil pH (r = 0.81 and −0.74, respectively) than that with MAAT (r=0.10). For the 5 different regions, brGDGT concentration all correlated positively with AI and the correlations were strong or moderate (0.94>r>0.42). On the other hand, the correlations with pH or MAAT were generally weaker and not stable. Specifically, brGDGT concentration correlated negatively with soil pH with r ranging from −0.17 to −0.75, except for a positive correlation (r=0.98) for soils collected from the Shandong Peninsula, while negatively with MAAT with r ranging from −0.12 to −0.94, except that no correlation (r=0.02) was observed for soils collected from the Chinese Loess Plateau and its surroundings. The strongest and most consistent correlations between brGDGT concentration and AI across regions and the whole dataset indicate that soil moisture is the controlling factor for brGDGT production in surface soils. Therefore, we propose that variations in brGDGT concentration in geological records, such as loess-paleosol sequences, can potentially be used to indicate past drying and wetting events. Moreover, our results imply that the seasonal bias in brGDGT-based paleo proxies, traditionally believed to reflect the seasonality of temperature, can also be influenced by seasonal changes in soil moisture (precipitation).
The spatiotemporal evolution characteristics and their coordination mechanisms between land use/cover change (LUCC) and socio-economic development along railway corridors, driven by railway construction and operation, constitute critical determinants of regional development quality. Taking Addis Ababa-Djibouti Railway as a case study, this investigation systematically examines the spatiotemporal patterns of LUCC and economic development dynamics along the railway corridor during the 2010—2018 period. Through the integrated application of the Tapio decoupling model and bivariate spatial autocorrelation analysis, this study elucidates the spatiotemporal coordination mechanisms between these 2 interconnected systems. The findings reveal that: 1) The magnitude of LUCC induced by Addis Ababa-Djibouti Railway’s construction and operation was relatively limited, predominantly manifesting as the transformation of agricultural land into construction land. The overall land use intensity along the railway remained relatively low, showing expansion based on the original pattern. 2) The effective nighttime light along Addis Ababa-Djibouti Railway is mainly concentrated in three major urban centers, displaying distinct transportation-oriented spatial expansion characteristics. The economic development of these central cities effectively drives the development of surrounding areas, with economic growth transitioning from rapid initial expansion to moderated development. 3) The construction and operation of Addis Ababa-Djibouti Railway have enhanced the spatiotemporal coordination between land use systems and economic development along the corridor. The relationship between these 2 aspects has transitioned from “weak decoupling” to “weak negative decoupling”. Spatial correlation analysis demonstrates strengthening interdependence between land use intensity and economic development levels, characterized by decreasing “HL” clusters and expanding “HH” and “LH” clusters. These spatial changes confirm the railway’s progressively intensifying radiating and driving effects on regional spatial restructuring.
Soil moisture is the link between soil and atmosphere material energy migration. Quantitative analysis of soil moisture migration law is of great significance for understanding regional hydrological processes and efficient utilization of regional water resources. This study based on the isotope data of different water bodies in typical cultivated land and non-cultivated land in the eastern Loess Plateau during the growing season (April-November) of 2023, the spatial-temporal heterogeneity of soil water’s δ2H and δ18O under different land use conditions were systematically analyzed; the soil water infiltration process and the temporal and spatial variation law of soil water storage were analyzed; the soil water evaporation loss at different soil depths was quantitatively evaluated, and the intrinsic relationship between soil water evaporation loss and the main environmental factors in the region was explored and revealed the laws of soil moisture migration. The results show that: 1) Under both land use types, the average soil water δ18O values are most enriched in the 0-20 cm soil layer and most depleted in the 80-100 cm soil layer, and also show dramatic fluctuations during the monsoon period. 2) The maximum infiltration duration of rainfall under non-cultivated land (6 days) was shorter than that under typical cultivated land (8 days), and the infiltration depth was slightly greater than that under typical cultivated land, but neither exceeded 80 cm. 3) The average value of soil moisture evaporation loss in the two land is the largest before the monsoon period (7.35%) and the smallest after the monsoon period (2.25%), which showed a fluctuating decreasing trend with increasing soil depth. 4) The soil water storage of both land showed a decreasing trend during the study period, and gradually increased from the surface to the deep layer. The soil water storage of typical cultivated land (average value 63 mm) was higher than that of non-cultivated land (average value 57 mm). 5) Temperature and vapor pressure deficit have extremely significant effects on soil water content and soil moisture evaporation loss. Compared with typical cultivated land, the soil moisture migration process under non-cultivated land is more significant affected by changes in environmental factors.
This study investigates the spatiotemporal evolution of vegetation coverage in the Liupan Mountain area from 1990 to 2024, based on the Google Earth Engine (GEE) global geospatial cloud platform. Utilizing GEE’s efficient data acquisition and processing capabilities, the research employs methods such as the Pixel Binary Model, trend analysis, and the Hurst index to explore the spatiotemporal changes in vegetation coverage and predict future trends. Furthermore, the study conducts an in-depth analysis of the primary geographic factors influencing vegetation coverage, using the Geographic Detector. The results show that: 1) The spatial distribution of vegetation coverage follows a high-medium-low-high pattern from southeast to northwest, with significant differences in vegetation coverage across different land use types; 2) Over the 35-year period, vegetation coverage generally showed a fluctuating upward trend, with an average value of
This study performs multi-scenario wetland simulations for the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) in 2030, including four land use change scenarios: baseline, economic development, ecological protection, and balanced development. The simulations include 16 driving factors, with the Wetland Damage Index (WDI) as a key component. We propose the Future Wetland Damage Index (FWDI) and identify zones for wetland management and conservation. The results indicate that: 1) Incorporating WDI as a driving factor significantly enhances the accuracy of wetland simulations in the PLUS model, achieving a Figure of Merit (FoM) value of 0.28 and an overall accuracy of 0.89. 2) Between 2020 and 2030, the areas of rivers, reservoirs, and lakes undergo minimal changes, reflecting the protective impact of land conversion restriction policies on wetlands. In contrast, pond wetlands display the most significant area changes, featuring a more compact distribution under the balanced development scenario, which highlights the balance between economic and ecological benefits. 3) FWDI results from 2020 to 2030 reveal that wetland expansion and loss primarily occur at the peripheries of contiguous wetlands. The FWDI in wetland expansion areas is lower than in regions where wetlands are lost, underscoring the need for further investigation into areas predicted to maintain stable wetlands in the future. 4) The FWDI functions as a targeted indicator for assessing the risk of future wetland loss. Using FWDI, three zones for wetland management and conservation are delineated. The wetland reconstruction zone, representing future wetland expansion areas, is concentrated in the western GBA regions rich in ponds and coastal areas. The wetland conservation zone, characterized by stable distribution and low FWDI, is widespread. The wetland control zone encompasses areas predicted to undergo wetland loss or remain unchanged but with high FWDI values, predominantly located in the pond-dense regions of central GBA. These conclusions offer scientific insights for the targeted protection of wetlands, aligning with the objectives of ecological conservation and socio-economic development.
The article defines synergistic development as a vector with the dual characteristics of synergistic degree and value-added capacity, which has the characteristics of “direction” and “size”, and adopts the vector modeling method and GeoDetector to analyze the synergistic evolution trend and driving factors of ecological protection and high-quality economic development in the Yellow River Basin. The results show that the degree of co-evolutionary and value-added capacity in the Yellow River Basin will show a fluctuating upward trend from 2011 to 2022, but most of the cities are still at the level of “low synergy and low value-added”, the overall level of synergy in the Yellow River Basin is low. The difference in synergy level between the upper and middle reaches of the Yellow River Basin is large, with the lower reaches significantly higher than the upper and middle reaches, and the lower reaches of the Yellow River Basin have more cities at the level of “high synergy and high value-addedness” and the upward trend is more obvious. The indicators related to high-quality economic development have a greater driving effect on the level of synergy in the Yellow River Basin than those related to ecological protection, in which the total sales of social retail goods and the urbanization rate play an important role, and the driving effects of pressure, state and response are in increasing order. The article concludes with 3 targeted policy recommendations in terms of supplementation, adherence to internal cooperation and external exchanges in different river basins in order to expand the spillover effect of advanced experience and policy implementation, empowering the transformation of ways and means of ecological protection, and improving the level of infrastructure and public services in order to better carry and guarantee the synergistic advancement of ecological protection and high-quality development of the Yellow River Basin.
Severe air pollution disrupts traffic, poses significant health risks, and adversely affects economic development. Therefore, systematically analyzing the causes of severe pollution in typical urban areas and accurately predicting the occurrence of severe pollution events is of considerable scientific and practical importance. The northeastern region of China, a major hub for heavy industry and agriculture, is characterized by its northernmost latitude and longest heating period, making its emission sources and meteorological conditions highly representative. This study focuses on Baicheng City, a plain-type city in Jilin Province, and utilizes multi-source data from 2015 to 2022, including air quality, meteorological, satellite, and remote sensing data. Through a systematic analysis of the underlying causes of severe pollution events, we identified the most effective machine learning algorithm for predicting PM2.5 concentrations during such events.The results indicate that, prior to 2017, Baicheng City experienced a high frequency of severe pollution events, primarily occurring in late autumn, early winter, and deep winter. However, after 2017, the number of severe pollution days significantly declined. Severe pollution events were classified into four primary types: local emission-driven, transmission-dominated, meteorologically-induced, and composite pollution, with composite pollution being the most prevalent. A machine learning-based prediction algorithm was developed using air quality, meteorological, and remote sensing data during severe pollution episodes to forecast PM2.5 concentrations in Baicheng. Among the tested models, the XGBoost algorithm demonstrated the best performance, with an R2 of 0.92 and a root mean square error (RMSE) of 24.6 µg/m3, significantly outperforming other algorithms such as Random Forest (R2=0.87) and Support Vector Machine (R2=0.67). This study provides a straightforward, accessible, and highly accurate process and algorithm for predicting severe pollution events in plain-type cities of northeastern China, offering valuable insights for the effective management of atmospheric environmental conditions.
Due to long-term overexploitation of groundwater and rapid urbanization, the Beijing area is experiencing severe land subsidence. Since the implementation of plain water replenishment and conservation projects such as the South to North Water Diversion Project, the problem of settlement has gradually been alleviated. At the same time, other problems such as ground rebound have emerged, making the uneven distribution of local spatial and temporal differences in ground subsidence increasingly significant. This study is based on Sentinel-1A data from 2018 to 2025, using SBAS InSAR technology to obtain InSAR deformation field data for the Beijing Plain. Combined with hydrogeological data, the study systematically analyzes the structural control laws of the current surface deformation and groundwater system in the Beijing Plain, as well as the response characteristics between artificial water diversion projects. The results indicate that: 1) The regional deformation pattern is jointly controlled by NE trending Huangzhuang Gaoliying Fault, Shunyi Liangxiang Fault, and NW trending Nankou Sunhe Fault, forming structurally constrained differential deformation units. The northern region exhibits obvious rebound characteristics, with the Houshayu in Shunyi District and the Pinggu Depression in Pinggu District being the most typical, with maximum uplift amounts of 127mm and 85mm for deformation units, respectively. The eastern Chaoyang Tongzhou district shows a continuous subsidence trend, with a maximum cumulative subsidence of 438mm, corresponding to the boundary of the Daxing uplift unit. The spatial distribution of the two is highly consistent with the boundary of the Daxing uplift tectonic unit. 2) The groundwater recharge caused by the South to North Water Diversion Project also exhibits structural zoning characteristics. The average rise of each aquifer in the Changping Shunyi Pinggu area on the north side of the Nankou Sunhe fault is 8.39-13.13m, significantly higher than the 0.75-2.37 m in the Chaoyang Tongzhou area of the Daxing uplift unit. In addition, based on gravity inversion data, it is speculated that the basement structure affects deformation differentiation by regulating groundwater transport. In the depression area (such as the Houshayu depression), due to the low bedrock terrain, it has a convergence effect on groundwater, resulting in a significantly higher rebound of soil foundation than in the uplift area (such as the Chaoyang Tongzhou subsidence area). The research results can provide guidance for the rational deployment of replenishment well groups and optimization of groundwater replenishment schemes for urban artificial water replenishment located in pressure bearing alluvial basins, in order to balance surface deformation differences and ensure regional geological environment safety.
The study of functional division within urban agglomerations holds paramount significance in optimizing the urban system and promoting the coordinated development of large, medium, and small cities. While existing research predominantly examines the pattern of functional division from the perspective of urban functional disparities, there is a notable dearth of studies focusing on the relational aspect of inter-city functional linkages. By integrating functional monocentric-polycentric theory, supply chain relationships, and urban network analysis, this paper establishes a functional division model and delineates partitioning methods alongside corresponding thresholds, and conducts empirical analysis of data from the supply chain of Chinese listed companies across 19 urban agglomerations in China, offering a comprehensive understanding of functional division within urban agglomerations. The main findings are as follows: 1) The functional division linkage patterns from the supply chain perspective can be divided into centrifugal monocentric pattern, centripetal monocentric pattern, and balanced polycentric pattern. Furthermore, these division linkage patterns effectively discern the structure of urban agglomerations in China, with each linkage pattern linked to the hierarchical structure of functional linkages and the stage of development within urban agglomerations. 2) The centrifugal monocentric pattern is dominated by urban agglomerations with sparse functional linkages and the stage of optimization and upgrading, such as Lanzhou-Xining, Ningxia along the Yellow River, and Huhhot-Baotou-Ordos-Yulin. The centripetal monocentric pattern is dominated by urban agglomerations with less-connected functional linkages and the stage of development and growth, such as the Pearl River Delta, Chengdu-Chongqing, and the Central Plain. The balanced polycentric pattern is dominated by urban agglomerations with well-connected functional linkages and the stage of optimization and upgrading, such as the Yangtze River Delta, the Shandong Peninsula, and the middle reaches of the Yangtze River. 3) Diverse urban agglomerations adhere to distinct evolutionary pathways in terms of functional division patterns, while most pattern evolution occur between centrifugal monocentric pattern and centripetal monocentric pattern, evolutions between monocentric pattern and polycentric pattern are relatively rare, indicating that the current functional division relationship in China’s urban agglomerations is primarily characterized by a core-city-led monocentric pattern, with the formation of polycentric pattern facing a certain threshold. By scrutinizing the functional division linkage pattern of China’s urban agglomerations through the lens of supply chain dynamics, this paper contributes to expanding the scope of regional division studies beyond attribute data and lays a solid foundation for subsequent research grounded in related data analysis.
This paper aims to evaluate the level and temporal and spatial pattern of the collaborative development of digital technology and cultural tourism integration in Chinese cities. The collaborative development of digital technology and cultural tourism integration is the advanced stage of the evolution of the relationship between digital technology and cultural tourism integration. It is clear that the collaborative stage and current level of the integration of digital technology and cultural tourism in Chinese cities are the prerequisite for promoting the high-quality development of digital technology and cultural tourism integration. Based on the analysis of the connotation of the collaborative development of digital technology and culture and tourism integration, this paper constructs a multi-dimensional evaluation index system of digital technology and culture and tourism integration development at the city scale, and depicts the process status and temporal spatial differentiation characteristics of the integrated development of digital technology and culture and tourism in 284 prefecture level cities in China from 2010 to 2020. The research shows that: 1) The overall level of collaborative development of digital technology and culture and tourism integration in China is in the middle and low range, showing a heterogeneous spatio-temporal pattern, with obvious gradient differentiation. The cities with good collaborative situation of digital technology and culture and tourism integration are mainly concentrated in the Pearl River Delta region, Jiangsu and Zhejiang regions and Shandong Peninsula, and the slow regions are mainly distributed in some cities in the northeast and western regions. 2) From high to low, there are four types of collaborative development: collaborative development, tending to synergy, synergy imbalance and synergy lag, and the transformation among the latter three types is more active. 3) The development trend of the collaborative integration of digital technology and culture and tourism is further presented from the dimensions of foundation, scale and structure. There are differences in the degree of collaborative development of digital technology and culture and tourism in each dimension. Finally, through the problem identification of different types of collaborative development areas, this paper discusses the path of collaborative development of differentiated digital technology and the integration of culture and tourism, which provides a reference for the city to formulate the collaborative development strategy of the two systems.
The externalities of urban networks have gradually become a significant focus in literature. Most existing studies examine the economic effects of urban network externalities from a static perspective. However, the development of urban industrial networks are dynamic processes. A single city typically starts by interacting with nearby cities and then gradually expands its economic ties to more distant ones. Thus, the spatial form of urban networks may initially be localized before evolving into a more comprehensive network. The impact of urban networks on regional economic growth and technological progress can vary at different stages of evolution. Existing literature has not adequately addressed this question. Moreover, urban network research has developed several main lines, including transportation networks, knowledge information networks, personnel flow networks, goods trade networks, and producer service networks, but there is limited research on manufacturing networks. Therefore, this article focuses on manufacturing networks to explore the phased changes in the evolution of urban network space and their impact on regional economic growth. We first construct a theoretical framework for the evolution of urban network space, elucidate the logical mechanisms by which regional policy coordination influences urban network evolution, and propose two spatial forms of urban network evolution called localized and globalized networks. Then, using data from 19 urban agglomerations, the study calculated the internal and external network centrality indicators of cities, providing a statistical description of the characteristics of China’s urban networks. Based on this, it examined the impact of localized and globalized network externalities on regional economic growth. The findings are as follows: 1) The scope of urban network space depends on the trade-off between urban interaction costs and network externalities. Initially, a single city interacts economically with nearby cities, forming a local network. As urban interaction costs decrease and the economic interaction space expands, the urban network evolves into a global network stage. 2) Regional policy coordination enhances market integration, reduces urban interaction costs, and strengthens urban economic interactions, significantly influencing the evolution of urban network space and the external economic effects. 3) There is a significant disparity in the development levels of urban networks across different regions in China. In most areas, urban network evolution remains at the localization stage, while the development of global networks is still relatively low. Although both localization and globalization can significantly boost regional economic growth, the external effects of local networks currently have a greater impact on China’s regional economic development. These findings have strong policy implications, suggesting that future efforts should focus on promoting dual policy coordination within and between urban agglomerations to facilitate the evolution of urban networks and fully leverage their external effects.
Based on the investment sample of China’s new outbound investment enterprises from 2011 to 2021, this article reconstructs the factor system affecting China’s new foreign investment enterprises in the new era from the perspective of objective condition combination. And a binary choice model is established to demonstrate the system of factors affecting the location choice of China’s new investment enterprises in the new era. The empirical results show that the host country’s (region’s) innovation resources and investment restrictions are the key factors affecting the location choice of China’s new foreign investment enterprises. However, relatively speaking, the influence of investment restrictions in the host country (region) is greater, and the innovation resource factors in the host country (region) need to meet the investment restrictions to exert a significant impact. In general, in the new era, the location choice of China’s new foreign investment enterprises tends to be the host country (region) with low investment restrictions and available innovation resources. Based on the changes in factors affecting the location selection of China’s new outward investment enterprises under the new international and domestic environment of great power competition, this article finally proposes policy recommendations on how China can stabilize its economic and technological external circulation by promoting its own enterprises to go global under the new development pattern of dual circulation.
Since the 2008 financial crisis, the process of financialization of Chinese cities and regions has accelerated, becoming a new driving force for local governments to influence the development of industrial diversification. Based on the panel data of 243 prefecture-level and above cities in China from 2011 to 2019 and by employing the fixed effect model, this paper focuses on the two key government financing modes of urban investment bonds and PPP projects, and discusses the impact of local governments on industrial diversification and how this differs by region. The conclusions include: Firstly, local government financing in the eastern region has significantly promoted the development of industrial diversification and unrelated variety, whereas the central region has a certain inhibitory effect on related variety, and the western region has no significant impact. Secondly, local government financing mainly promotes unrelated variety of the industry. PPP is the main mode of local government financing to promote unrelated variety in the eastern and central regions, while urban investment bonds have a greater impact on unrelated variety in the western region. Thirdly, the scale, modes and expenditure structure of local government financing differs by region, which have contributed to different effects of local government financing on industrial diversification in different regions. When local governments use financial instruments to promote industrial development, local comparative advantages and industrial bases should be taken into account considerably. On the basis of strengthening industrial unrelated variety, related variety needs to be developed according to local conditions so as to take advantages of the externality of industrial diversification.
Geo-economy is an important factor affecting the global political and economic landscape, and the industrial chain is an important foundation for the formation of geo-economic relationships. China and India are respectively at the core of the East Asian and South Asian industrial chains. Against the backdrop of the continuous development of industrial chain specialization, it is imperative to clarify the competition and cooperation dynamics between China and India in key industry sectors. This study uses the export similarity index, revealing comparative advantage index, trade complementarity index, and intra industry trade index to analyze the competition and cooperation between the main industrial chain links of China and India. The research results reveal three key insights: 1) The economic partnership between China and India is mainly concentrated in the chemical and equipment manufacturing industrial chains, exhibiting distinct collaborative dynamics. In the chemical industry, upstream cooperation is underdeveloped, while midstream cooperation is the closest. In terms of equipment manufacturing, India still heavily relies on China’s industrial chain contribution; 2) The chemical cooperation between China and India presents distinct industrial chain characteristics formed by complementary advantages. Although the upstream departments have shown strong complementarity, competition in the midstream departments is becoming increasingly fierce. The current cooperation model has not fully utilized the potential of both parties in the industrial chain. This highlights the inherent complementarity in bilateral cooperation and the coexistence of unrealized cooperation dividends; 3) The industrial chain of equipment manufacturing in China and India is mainly competitive, showing structural competition concentrated in upstream industries. Both sides have a relatively small market share in each other’s export market, highlighting the misalignment of industrial policies and the lack of coordination in industrial chain positioning in this competition. By analyzing the current situation of industrial chain cooperation in detail, this study provides actionable insights for deepening China and India cooperation. These measures can transform the current paradigm of “asymmetric competition” into a mutually reinforcing geo-economic partnership.
As migration patterns continue to evolve, population mobility has emerged as a core driving force behind regional demographic changes. Based on the theory of new economic geography, this article employs spatial mixed regression models and geographically weighted regression models to investigate the temporal and spatial evolution of economic and social migrants. The research findings indicate significant spatial heterogeneity in the impact of economic and social factors on population mobility, demonstrating a gradient difference that increases from north to south. The population attractiveness of economically developed southern regions (such as the Yangtze River Delta and the Pearl River Delta) is markedly higher than that of the north, further highlighting the close relationship between economic development levels and population mobility. Although the eastern coastal regions continue to attract a large number of migrants, improvements in the economy of the central and western regions are gradually leading to increased inflow, reflecting new trends in regional development in China and the synergistic effects of economic and social environments. Notably, both economic and social factors exhibit stronger spatial heterogeneity in their effects on economic migrants. Economic migrants tend to be more mobile, with their migration decisions directly influenced by economic fluctuations and industrial restructuring. In contrast, social migrants are more concerned with factors such as healthcare security and public services, exhibiting relatively less spatial heterogeneity in their influence. As economic development and regional balance progress, the impact of social factors on both types of migrants has surpassed that of economic factors, with the driving forces gradually shifting from economic incentives to the pursuit of a higher quality of life. In summary, the patterns of population mobility are shaped by the interaction of economic and social factors, exhibiting complex heterogeneity across different temporal and spatial dimensions. Therefore, in the governance of migrant populations, it is essential to comprehensively consider multiple factors such as economic vitality, public services, and regional planning, and to adopt targeted measures that promote rational mobility and balanced regional development. This study not only provides theoretical support and empirical evidence for understanding the dynamic characteristics of population mobility in China but also offers important references for policymakers in optimizing social governance and regional development strategies.
Under the background that China has entered a new stage of development, the national red tourism classic scenic spots, as an important carrier of inheriting the red gene and carrying forward the revolutionary spirit, have become important resources to promote the development of red tourism in the old revolutionary base areas. Based on the quasi-natural experiment of establishing national red tourism classic scenic spots and the county data of
Taking the State-Level Xiangjiang New Area, a typical case of deepening reform in China, as the research area, using rental housing data from household surveys and POI network data, combined with the geographically weighted regression model (GWR), this article constructs a rental intensity index for exploring the spatial distribution characteristics of rental housing in study area, the factors affecting spatial structure and it’s spatial heterogeneity are analyzed. It is found that: 1) The rental intensity generally decays from the core area to the peripheral area, and at the same time has obvious directionality to the landscape, transportation nodes, university cities and industrial parks; 2) There is obvious spatial heterogeneity in the factors affecting rental intensity. University facilities, landscape parks, housing quality, park distance, and rental factors have a low impact within the second ring, and the further away from the central city district the greater the intensity. The opposite is true for subway and high school facilities, where the intensity of impact is higher in the core area and decreases with distance; 3) The rental intensity and factor intensity show non-consistency in terms of location conditions, reflecting different trade-offs among heterogeneous groups of tenants in terms of location maturity, living quality and employment commuting. In the context of “sale and rental developing simultaneously”, in order to promote the development of the rental market, it is recommended to dynamically adjust the supply on demand, focusing on increasing the effective housing supply in high-density demand areas such as the core area, supporting the development of diversified market entities and large-scale professional long-term rental institutions, refining the rental security policy, implement differentiated and graded subsidies for migrant workers, graduates, multi-child families and other groups, guiding tenants to flow to areas with sufficient supply, easing the pressure on the core area, accelerating digital governance, building an information platform covering housing verification, contract filing, and credit evaluation to improve supervision and service efficiency. The findings of this article can guide the construction of rental housing and the spatial layout of related public service facilities, and provide reference for promoting the balanced development of sale and rent in new urban areas.
Based on the theory of geoscience information Tupu, this paper defines the spatial units of tourism resources from a multi-scale perspective, constructs a multi-scale tourism resource ontology value evaluation Tupu, deeply explores the relationships between tourism resources of different scales, and conducts an empirical analysis using Hainan Island as a case study to evaluate the ontological value of multi-scale tourism resources. The results show that: 1) A conceptual model for the ontology value of tourism resources was proposed based on quantitative and spatial characteristics, and an information Tupu for the evaluation of ontology value was constructed, including aggregation, agglomeration, and combination area. This model provides a comprehensive framework for understanding the intrinsic value of tourism resources across different spatial scales, offering insights into their distribution and potential for development. 2) The evaluation Tupu of tourism resource aggregation illustrates that high-quality aggregation on Hainan Island are predominantly concentrated in the Haikou and Sanya regions, with a greater number found on the eastern coast compared to the western coast, and a higher concentration in the northern plain area than in the southern mountainous region. This spatial distribution highlights the diverse geographical features influencing tourism resource aggregation and suggests targeted strategies for resource management and development. 3) The evaluation Tupu of tourism resource agglomeration reveals that high-quality clusters on Hainan Island radiate outward from Sanya and Haikou as the southern and northern centers, respectively. The central region has a slightly lower density of clusters, primarily diffusing in the form of single core points. This pattern of agglomeration underscores the importance of central nodes in the spatial organization of tourism resources, which could inform infrastructure planning and investment decisions. 4) The evaluation Tupu of tourism resource combination area indicates that Hainan Island’s composite areas are divided into four levels. Level 1 clusters have a higher intrinsic value of urban tourism resources than Level 4 clusters, and their development potential is consequently greater. This hierarchical classification of combination areas provides a strategic framework for prioritizing tourism development initiatives, ensuring that resources are allocated efficiently to maximize economic and cultural benefits.
Chinese Academy Sciences
Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences
Science Press