Existing research on the effects of regional urbanization on elderly health often fails to account for key environmental variables and lacks comparative analyses across different spatial scales. To bridge these gaps, this study examines the relationship between regional urbanization and elderly health, identifies critical environmental determinants, and conducts a multiscale spatial analysis.Drawing on data from the seventh national population census, this study employs GIS spatial visualization and Tobit regression models to investigate spatial patterns of elderly health across regions with varying levels of urbanization. The analysis differentiates between city-level and urban district/county-level regions, highlighting disparities in the effects of urbanization and living environments on elderly health while accounting for the confounding influences of multi-dimensional environmental factors.The findings reveal a clear spatial gradient in elderly health, with higher health levels observed in southeastern urban agglomerations compared to central and northern urban clusters. Nationally, the average proportion of selfreported healthy elderly individuals is 87.25%, with only regions exhibiting an urbanization rate above 76% surpassing this benchmark. Additionally, at both city and district/county levels, urbanization rates show a significant positive correlation with elderly health. Several environmental factors, including NDVI, water coverage, land surface temperature, road density, and per capita building area, are identified as positive predictors of elderly health, whereas PM_2.5 concentration, the proportion of households without tap water, and the proportion of households without toilets exhibit significant negative associations. Notably, the impact of variables such as hospital bed availability, forest and grassland coverage, land surface slope, and the proportion of households without kitchens varies across spatial scales, underscoring the role of spatial granularity in shaping these relationships. Furthermore, the study finds that the relationship between urbanization and elderly health varies by urbanization threshold. In areas where the urbanization rate is below 45%, higher urbanization is associated with poorer elderly health, suggesting that less urbanized regions may provide more favorable conditions. Conversely, in areas with urbanization rates above 45%, greater urbanization corresponds with improved elderly health outcomes. The study also examines the moderating role of urbanization in the relationship between environmental factors and elderly health, revealing that higher urbanization rates weaken the positive effects of NDVI while mitigating the adverse impact of PM_2.5 concentration. The findings highlight the intricate interplay between urbanization, environmental conditions, and elderly health, emphasizing the need for tailored policy interventions. In highly urbanized areas (75%+), strategies should focus on balancing land-use efficiency with green space preservation while addressing housing density to prevent potential health declines among the elderly. In contrast, regions with medium to low urbanization rates should prioritize agefriendly environments by enhancing road infrastructure, improving housing conditions, and ensuring accessible living and transportation facilities for the elderly. This study provides a theoretical foundation and policy framework for fostering environments that promote elderly health.

To explore the variations of aeration zone soil specific yield under the condition of deep buried groundwater, The southern edge of Gurbantunggut Desert was taken as the research area by field in-situ observation.The complete specific yield under the condition of zero surface flux, the average releasing specific yield under the condition of evapotranspiration and the average charging specific yield under the condition of lateral leakage recharge were determined, and the effects of groundwater depth, infiltration and evapotranspiration on specific yield were discussed. Results showed that: 1) It is feasible to determine the soil specific yield under the condition of deep buried groundwater by the zone of aeration section water content method. 2) Under the condition of zero surface flux, the complete specific yield μ increases with the increase of groundwater depth H. When the groundwater depth exceeds the maximum rising height of capillary water, the change of complete specific yield is small and can be approximately regarded as a constant. 3) The average groundwater depth of interdune land in the southern edge of Gurbantunggut Desert is 8.80 m. The complete specific yield under the condition of zero surface flux is 0.36, the average releasing specific yield under the condition of deep buried groundwater evaporation is 0.13, and the average charging specific yield under the condition of lateral leakage recharge is 0.17. The results of this study can provide a new idea for the determination of soil specific yield under the condition of deep buried groundwater.

In the process of plant ecological construction in sandy areas, it is still necessary to conduct in-depth scientific research on what kind of herbaceous plants can achieve the best windbreak effect. This article uses a mobile wind tunnel to plant herbaceous plant communities (Astragalus laxmannii and Leymus chinensis “Zhongke No.1”) in the wild. The effects of two plant communities on sediment transport rate and wind speed profile were explored under four different vegetation cover levels (10%, 20%, 30%, and 40%) to clarify the windbreak and sand fixation ability The wind tunnel field test results show that Astragalus laxmannii has significantly stronger windbreak and sand fixation efficiency than Leymus chinensis, manifested as a significantly lower sediment transport rate than Leymus chinensis under the same vegetation cover and wind speed conditions, but a significantly higher wind speed reduction rate and wind erosion inhibition efficiency than Leymus chinensis. The optimal windproof coverage of Astragalus laxmannii is 30%, which can suppress about 90% of the sediment transport within 20 cm on the surface. When the vegetation coverage of Leymus chinensis is 32%, it can suppress 75% of the sediment transport within 20 cm on the surface. From the perspective of plant morphology and structure, plants with harder stems and multiple clustered stems have better windbreak and sand fixation effects.

Based on precipitation samples from Jinhua region (March 2022 to February 2023), this study combines meteorological data and the GLEAM dataset, to quantify the intensity of sub-cloud evaporation, the proportion of recycled moisture using the three-end d-excess method during different periods. The local meteoric water line in the study area is δD = 8.47δ¹⁸O +16.45, with both intercept and slope exceeding those of the global meteoric water line. The precipitation deuterium excess (d-excess) fluctuates between -3.76‰ and 31.02‰, showing significant seasonal differences. Specifically, the average d-excess values during the spring rainy period and plum rain period (March to June), the summer drought period (July to August), and the brief rain period (September to February of the following year) are 11.06‰, 7.32‰, and 18.76‰, respectively. The results indicate that the sub-cloud evaporation intensity is highest during the summer drought period, followed by the brief rain period, with the lowest intensity during the spring and plum rain periods. The proportion of recycled moisture shows a similar pattern, being 21.25% during the summer drought period, 14.02% during the brief rain period, and 6.25% during the spring and plum rain periods. Relative humidity is the primary factor influencing both sub-cloud evaporation intensity and recycled water vapor proportion during the spring and plum rain periods.

With the acceleration of urbanization, a large number of urban wetlands are disappearing and degrading, posing a threat to urban sustainability. Accurate and real-time spatial distribution information of wetlands is essential for sustainable urban wetland management and urban planning. In this study, the built-up area of Haikou City in Hainan Province, an international wetland city, was selected as the research area. Combined with Sentinel-1 radar and Sentinel-2 optical images, the object-oriented and random forest algorithm remote sensing classification method was adopted to finely classify and map urban wetlands. We compared the effectiveness of this method with other classification methods to explore its applicability in urban wetland classification. The results show that the classification accuracy is improved by 5.29% after adding the dual-polarized backscattering coefficients of Sentinel-1 images to the original set of feature vectors using the same classification method. We found taht the object-oriented classification method is more suitable for wetland classification than the pixel-oriented classification method. Furthermore, the random forest algorithm used in this study demonstrated higher accuracy in identifying land cover types compared to the CART decision tree algorithm. The overall accuracy of the interpreted results using the added backscattering coefficient and the object-oriented random forest method was 91.53%, with Kappa coefficient of 0.90, indicating a good classification performance. This study can provide reference for the rapid and accurate identification and mapping of small-scale urban wetlands, and offers a visual scientific basis for the protection and management of urban wetlands.

With the urban heat island effect increasingly exacerbated, understanding how urban wetlands regulate temperatures across different seasons is of significant importance. This study utilized Landsat-8/9 thermal infrared band data from 2015 to 2022 to retrieve the land surface temperature (LST) of wetlands within the built-up area of Harbin-a wetland city, using the split-window algorithm. By constructing buffer zones and calculating the Normalized Cooling Capability Index (NCCI) and the Normalized Cooling Efficiency Index (NCEI), we systematically investigated the thermal effects of wetlands under varying spatiotemporal conditions. The results show that during summer (June —August), wetlands exhibit the most pronounced cooling effect, with an average cooling of approximately 3.39℃ at the wetland boundary relative to the surrounding urban area, and a larger influence distance. In contrast, from November to the following February, wetlands demonstrate a heat-retention effect, most notable in December with an average temperature retention of 0.66℃ and a relatively smaller influence range. Moreover, the spatial configuration of wetlands significantly affects their temperature-regulating function: wetlands with larger areas, higher shape indices, and hydrological connectivity tend to have stronger cooling capability and efficiency, and can exert a cooling influence over broader areas. These findings contribute to the understanding of urban wetlands' temperature-regulating effects in different seasons and support the development of ecological cities.

Underdeveloped regions are an important manifestation of unbalanced and insufficient development, as well as an outstanding shortcoming facing the advancement of Chinesestyle modernization. Based on the scientific understanding of underdeveloped regions, this study identified the spatial distribution and regional types of underdeveloped counties in China in 2022, and proposed development paths for underdeveloped counties, with a view to providing references for establishing and improving regularized support mechanisms for underdeveloped regions. Essentially, underdeveloped regions stem from the shortcomings of humanearth system and the incoordination and inadaptability among its elements, which include not only lagging economic development, but also shortcomings such as insufficient public service and lack of infrastructure. Therefore, it is it is appropriate to adopt the “1+N” program for the spatial identification of underdeveloped regions, i.e., to diagnose different sectoral underdeveloped regions based on the identification of economically underdeveloped areas, and then to designate the types of underdeveloped regions. Spatially, county economic development level in 2022 showed obvious clustering characteristics, in which high-value counties were mainly distributed in the Yangtze River Delta, the Pearl River Delta, the periphery of provincial capitals and the energy-resource-rich areas in the Northwest. The estimation results of SDM and Geodetector show that the proportion of land used for transportation, years of schooling, urbanization rate, and the proportion of added-value of primary industry in GDP were the dominant factors affecting the regional differentiation of county economic development level. Therefore, sectoral underdeveloped counties include transportation-underdeveloped counties, education-underdeveloped counties, urbanization-underdeveloped counties and industrializationunderdeveloped counties. In accordance with the dominant constraints, their negative effects on county socio-economic development should be scientifically analyzed to propose countermeasures for different types of sectoral underdeveloped counties. In addition, the study identifies 695 economically underdeveloped counties, mainly in the former concentrated and contiguous areas with special difficulties. Based on the identified dominant constraints, these counties can be classified into five categories, i.e., economically underdeveloped counties constrained by industrialization and urbanization, industrialization-constrained economically underdeveloped counties, economically underdeveloped counties constrained by education and urbanization, multifactor relatively constrained economically underdeveloped counties, and multi-factor strictly constrained economically underdeveloped counties. The regularized support strategies for different types of underdeveloped counties should be based on the combination of their dominant constraints, should be implemented in accordance with local conditions, classified guidance, and regional implementation.

Agricultural and rural modernization constitutes a crucial part of Chinese moderniz- ation and represents the envisioned goal for the future rural development. It is a transformative process wherein productive elements such as urban science and technology, along with social concepts and governance methods, are transferred to rural regions, facilitating a comprehensive upgrade of rural areas from traditional to modern society. Additionally, the spatial reconstruc- tion of rural settlements is a significant aspect of rural reconstruction. It is a superimposed pro- cess that combines the adaptive adjustments of rural settlements in response to alterations in rural development factors and the structural reconstructions for specific developmental object- ives. There is a close relationship between agricultural and rural modernization and the spatial reconstruction of rural settlements, as the former offers the impetus and target framework for the latter. The spatial reconstruction of rural settlements can be achieved through adaptive re- modeling to synchronize with the progression of rural modernization and via in-depth restruc- turing to expedite the attainment of rural modernization goals. Presently, Chinese rural settle- ments exhibit prominent characteristics of spatial restructuring. For instance, first, there is a multiplicity in goal orientations, encompassing food security, augmentation of farmers’ income, sustainable agricultural development, and high-quality rural development. Second, due to vari- ances in rural regional patterns, resource environments, and development determinants, there is complexity in functional types and spatial organization. Third, different rural settlement levels have disparities in the key aspects they emphasize regarding policy formulation, spatial organiz- ation, and facility allocation during spatial reconstruction. The paper further elaborates that the spatial reconstruction of rural settlements in China confronts the following tasks: 1) relying on agricultural development models like large-scale agriculture, urban agriculture, and leisure agri- culture, to accelerate the appropriate scale operation of agriculture and drive the modernization of rural industries; 2) considering the current situation of rural contraction and the future struc- tural traits of rural settlements, to reconstruct the rural settlement pattern that aligns with the co- ordinated development of human-land-industry and steers rural modernization; 3) with the ob- jective of narrowing the urban-rural development gap, to construct a novel urban-rural integ- rated development pattern, to formulate a multi-level governance model that transcends admin- istrative boundaries, and to realize the modernization of rural governance; 4) leveraging the ad- vantages of rural resources, industrial characteristics, and the trend of functional differentiation, to reshape novel rural functions and propel rural transformation. Finally, this paper proposes that the spatial reconstruction of rural settlements should focus on the following aspects: 1) the- oretical framework of spatial reconstruction of rural settlements under the concept of urban-rur- al parity; 2) mechanism of spatial reconstruction of rural settlements under the influence of new quality productive forces; 3) types of settlement development and regional spatial organization guided by diversified and characteristic rural functions; 4) research methodologies of spatial re- construction of rural settlements supported by disciplinary integration and technological conver- gence; 5) scale and spatial organization of settlement reconstruction within the target scenario of rural modernization. In doing so, it endeavors to attain the objective of bolstering a powerful agricultural nation and realizing Chinese modernization.

Urban wetland parks are essential infrastructures of Chengdu’s efforts to construct a blue-green park system and to facilitate the development of park city demonstration zone. They play a crucial role in alleviating urban heat and providing cooling services to the public during summer. This study initially utilized the GEE platform, Landsat data, and an empirical statistic- al single-window algorithm to evaluate the summer land surface temperature (LST) of 42 urban wetland parks in Chengdu. Subsequently, the study investigated the relationship between water body, vegetation landscapes within the parks, landscape indicators outside the parks, and the land surface temperature within the parks. Finally, a potential heat-avoidance index for urban wetland parks was constructed from 3 aspects: park accessibility, park capacity, and park thermal cooling effect, to assess potential ability of an urban wetland park in heat alleviation. The results indicate: 1) The average land surface temperature of urban wetland parks within the Chengdu No.3 Ring Road to the Chengdu Ring Expressway is the highest, at 33.45℃, while those outside the Chengdu No.2 Ring Expressway have the lowest average land surface temper- ature, at 30.81℃, showing a difference of 2.64℃. 2) External heat environments have a posit- ive impact on the land surface temperature within the parks, while the proportion of water bod- ies and the density of vegetation negatively affect the land surface temperature within the parks. 3) The top 5 urban wetland parks with the highest potential heat avoidance index are the Qin- glong Lake Wetland Park, the Dong’an Lake Park, the People’s Park, the Wangjianglou Park, and the Xinglong Lake Wetland Park, while the bottom 5 urban wetland parks with the lowest heat avoidance potential are the Guanghua Park, the Dayuan Central Park, the Chuangzhi Park, the Jiaozi Park, and the Xinchuanzhixin Park. The study suggests that water bodies in urban wetland parks should be dispersedly distributed, and vegetation should be more densely and concentratedly distributed to enhance the potential ability of an urban wetland park in heat alle- viation.

The impact of geopolitics on patterns of global flows of critical resources is an im- portant issue for the economic geography. Many countries with high dependence on crude oil import regard crude oil as their key strategic resource, and give priority guarantee in national security strategy. As the most serious geopolitical conflict in Europe since the Cold War, the Russia-Ukraine conflict has exerted a significant influence on the global crude oil transporta- tion pattern. This paper quantitatively analyzes the spatio-temporal characteristics of global oil transport pattern before and after the outbreak of the Russian-Ukraine conflict. Based on the global AIS ship track data from January to June 2019, 2020 and 2022, this paper presents a method of ship trajectory identification including data pre-processing, trajectory identification and flow calculation. By combining the time, speed, longitude and latitude coordinates and oth- er constraints, the starting and ending points of the route can be determined, and the complete navigation trajectory can be identified. The crude oil transportation volume is calculated by the maximum weight ton of the ship, which includes the transportation volume, the transportation distance and the turnover volume. The results are: 1) Before and after the Russia-Ukraine con- flict, the global crude oil shipping flow decreased significantly, and the global crude oil turnover fell by 24% in the short term. This negative effect has a one-month lag, which is re- lated to the time of a single crude oil shipment. 2) There is spatial heterogeneity in global crude oil shipping flow. The variation of shipping flow occurs only in a few specific regions, and the trend is different. On the demand side, Western Europe increased crude imports from North America and the Middle East, while India and East Asia increased their imports from the Medi- terranean. On the supply side, the Middle East have increased their crude exports to western Europe while reducing their crude exports to East Asia; and the Mediterranean region, crude oil exports increased both to Europe and to Asia. 3) The spatial distribution of global crude oil pro- duction and consumption level is extremely unbalanced, forming 21 major global crude oil shipping routes, where Russia to Europe route traffic reduced, Russia to India route and the Middle East, the United States to Europe route traffic grew. The pattern of global oil transporta- tion shows a trend of restructuring, showing a “Trans-Atlantic route” dominated by Western Europe and the United States, and a “Asian route” dominated by Russia. This pattern will have an impact on energy security, energy industry and related industries in countries with high de- pendence on oil imports. This paper helps to enrich the study of the relationship between geo- politics and global resource flow patterns and deepen the theoretical understanding of the im- pact of geopolitics on global resource flow patterns.

Planting industry in China is in a critical period of transitioning from a production- oriented to a quality-oriented presently. Therefore, it is of great significance to analyze the spa- tiotemporal differentiation and driving mechanisms of ecological efficiency in planting in- dustry, such as achieving agricultural quality and efficiency improvement, promoting its eco- nomic ecological coordinated development, and enhancing people’s well-being. DEA-SBM model, carbon emission model, non-point pollution method, spatial analysis technology of GIS and geographical detector model were used in this study, and the conclusions were as follows: From 2010 to 2020, 3 trends of increasing, decreasing, and stabilizing coexisted in the input, and an upward trend in the expected output, while increasing and decreasing trends in non-ex- pected output. The administrative units with low levels of ecological efficiency for planting in- dustry continuously transformed to higher levels, and the hierarchical structure was optimizing; The ecological efficiency for planting industry was higher in the east and lower in the west, and the “upward” and “unchanged” regions alternated from east to west. The changes of ecolo- gical efficiency in the east-west and north-south were mild, there were multiple core areas and had a “center-periphery” feature; 3) The ecological efficiency for planting industry in the study area was influenced by multiple factors. Natural conditions are the foundation to affect its pat- tern and evolution, agricultural technologies are the driving forces, the impact of agricultural economic development has 2 sides, and the product market plays a decisive role; 4) In the fu- ture, the planting industry in the study area should focus on the issue of carbon emissions, im- prove the utilization efficiency of agricultural chemicals, strengthen environmental education and pay attention to the radiation and driving role of the central areas. This study has used in- dicators such as geographical indications of agricultural products and green foods that reflect the contemporary characteristics of the planting industry to improve the existing evaluation sys- tem. It helps to improve the research methods and techniques, provide scientific basis for optim- izing agricultural policies, and assist in the strategies of rural revitalization and agricultural high- quality development.

There has long been a discursive separation between workspace and home. Based on the geography of home theory, this article explores the process of constructing home within the livelihood space of operational migrants through in-depth interviews and participatory observation. The findings reveal that the home-making practices of business migrants illustrate the coexistence of workspace and home. Firstly, a stable business location is central to the home-making efforts of business migrants, providing them with a sense of ontological security and belonging. Secondly, the practice of domesticating business space is crucial for the construction of a “livelihood home”. Through self-employment and family management, business migrants can flexibly navigate their business and family responsibilities,thereby integrating the boundaries between work and life. Thirdly, through their business activities, migrants develop a local network of business relationships, express a positive local identity,and integrate into their new environment. Business cooperation reinforces existing kinship and geographic networks, thereby maintaining close ties to their original home. This paper enriches the study of the geography of home, enhances our understanding of the multiple functions and scales of home, and constructs a theoretical framework for the “ home of livelihood” contributing to the comprehension of business-oriented migration from a geographic perspective.

Bike-sharing is a new urban infrastructure with low-carbon and environmentally friendly pratices, directly contributing to the sustainable development of cities. However, most existing studies overlook both the distributed agency of bike-sharing and the dynamic ralational networks and operational logics underpinning it. Agency, as emphasized in assemblage theory, is not exclusive to humans but extends to non-human entities. Therefore, this paper adopts the urban assemblage perspective as its methodological freamework to analyze how bike-sharing is em-bedded into the fabric of everyday urban life and to uncover the theoretical logic behind this phenomenon. Urban assemblage provides a lens to navigate the complexity of urban systems, charac-terized by entangled materiality, emotions, governance, and non-linear causality. This study in-corpoates two axes of material/expressive and territorialization, and two core concepts, distributed agency and relations of exteriority, to reveal the “blackbox” of bike-sharing through qualitative research methods. First, it examines the temporarily stabilized, multidimensional relational network of “human-technology-bike-space”, explaining the daily practices of bike-sharing in urban public spaces through a dynamic and non-linear perspective. The findings highlight that bike-sharing emerges as a product of continuous negotiation between human and non-human elements. Second, the paper reflects on urban ontology, social-technological interaction and techno-logy influence on subjectivity, aiming to inspire social and cultural geographers to generate geo-graphical knowledge aligned with the global trends of urbanization and intelligence. Finally, through the interpretive framework of multiple power game and spatial evolution, the research broadens the scope of society-technology interactions, offering novel insights into the transforma-tion and sustainable development of Chinese cities from a new perspective.

Optimizing land use objectives offers effective tools for judicious resource allocation. Simulating future land use and carbon stock changes is vital for formulating regional sustainability policies and enhancing terrestrial ecosystem carbon storage. This paper analyzed the spatial and temporal differences in land use and carbon storage from 2000 to 2020, predicted the spatial and temporal differences in land use changes and car-bon storage under four development patterns, namely, “natural development pattern (BAU), urban develop-ment pattern (RED), cultivated land protection pattern (CPS), and ecological protection pattern (EPS)” in 2030 by constructing the coupled land use model (PLUS-InVEST), and estimated the economic value of the carbon storage by combining the formula of compounded present value and compounded terminal value in Lanzhou City from 2000 to 2030. The results showed that land use changes were dominated by the decrease of grass-land area and the increase of building land area in Lanzhou City from 2000 to 2020, with a loss of 61.77×10⁴t of carbon storage during the 20-year period. With the exception of the EPS, in which the carbon storage in-creased by 5.09 ×10⁴t, all other scenarios showed different degrees of carbon loss compared to the 2020, with the largest loss of carbon in RED at 56.46×10⁴t. In this study, the economic value of carbon storage increased by 10.3×10⁸yuan in Lanzhou City from 2000 to 2020 through the compound present value method, which is mainly attributed to the significant increase in carbon price on the time scale. Compared to the economic value of carbon storage in 2020, the EPS has the highest economic value of carbon storage at 34.58×10⁸yuan, which is the optimal development model for the study area. This study has important practical significance for the low carbon development of land resources and scientific decision-making of ecosystem management in Lanzhou.

Return migration has become a notable socio-economic trend in the new stage of China's urbanization, and the analysis of its driving mechanism has received extensive academic attention. As a micro behavior, the return of migrants is not only affected by personal and family factors, but also closely related to external environment. However, existing studies have focused on the role of individual factors, but not enough research has been conducted on the relationship between regional contexts and return migration. We introduce a gradient boosting decision tree model in the field of machine learning, based on the data from the 2017 China Migrants Dynamic Survey, with the return intention as the response variable and the regional contexts—Both in the place of origin and destination—As well as migrants' personal and household factors as the explanatory variables, focusing on the non-linear influence of the regional contexts on the return migration intentions and the threshold effect. The results show that: 1) The total contribution of the local contexts of the place of place of the origin and destination to the intentions of the migrants to return is 44.1%, which is an important factor influencing the return intentions, and the contributions of the two places is roughly equal. Among these, medical and health resources and air pollution are extremely important in both places. In addition, economic growth in the place of origin is also important for the return intention of migrants, while the climatic condition in the place of destination is more important; 2) There are both non-linear and linear relationships between local contextual factors and migrants' intention to return. Among them, medical and health resources, basic education resources, air pollution have obvious non-linear effects on the return intention, while economic growth and temperature conditions have mainly linear effects; 3) The influence of individual factors on return intention is mainly nonlinear effect. There is an irregular U-shaped relationship between age, migration duration and return intention, and the non-linear influence of household income is more complex. There is an obvious threshold effect between household housing expenditure and return intention, and a negative correlation between migrant's education level and return intention. This study incorporates the local contexts of the place of origin and destination into the analytical framework for the mechanism of return migration, identifies the relative importance of the local context and individual characteristics of the two places on the return intention of the migrants, and reveals the specificity and complexity of internal return migration in China, which contributes to deepening the research on migration in the new era and provides scientific reference for policy makers.