Encryption serves as a safeguard against unauthorized access to data by unauthorized users. Reversible watermarking, on the other hand, can be employed to authenticate the integrity and origin of data, while enabling the lossless recovery of the original data. In light of the security requirements for vector map data protection, this study combines encryption and reversible watermarking techniques to present a novel reversible vector map watermarking algorithm within the asymmetric homomorphic encrypted domain. By capitalizing on the homomorphic characteristics of the encryption algorithm, the proposed approach devises a reversible watermark embedding mechanism grounded in an improved histogram shifting method, which is directly executed within the ciphertext domain. Upon decryption of the ciphertext map with a private key, the watermark can be retrieved from the resultant plaintext map. Subsequently, the original map can be restored through the implementation of inverse histogram shifting. The algorithm is implemented and evaluated using 3 distinct map datasets. The experimental results validate the feasibility and efficacy of the proposed algorithm. Through a comprehensive analysis of the watermarking performance on these 3 map datasets, along with a comparison with existing reversible watermarking algorithms in both the plaintext and ciphertext domains for vector maps, it is demonstrated that the proposed algorithm exhibits a larger payload capacity, higher imperceptibility, and a more secure encryption effect. Thus, it represents a practical and viable reversible watermarking solution in the asymmetric homomorphic encryption domain for vector maps.

As a leading area for the development of modern large-scale agriculture, northeast China needs to give consideration to enhancing both peasant household’s cultivated land management scale and cultivated land use efficiency, so it is necessary to research their relationship in depth. This study is based on the multi-objective collaborative perspective of economic, social and ecological benefits. Using the prefecture-level administrative regions in northeast China from 2010 to 2021 as samples, peasant household’s cultivated land management scale and cultivated land use efficiency were calculated, and their evolution characteristics and regional differences were analyzed. Then the relationship between peasant household’s cultivated land management scale and cultivated land use efficiency in northeast China was explored through regression analysis, and the moderate peasant household’s cultivated land management scale in northeast China at this stage was estimated. The results show that: 1) Both peasant household’s cultivated land management scale and cultivated land use efficiency in northeast China increased from 2010 to 2021, with larger peasant household’s cultivated land management scale and higher cultivated land use efficiency in Heilongjiang Province, smaller peasant household’s cultivated land management scale in Liaoning Province, and lower cultivated land use efficiency in Jilin Province and eastern Inner Mongolia. 2) During the period, regional differences in peasant household’s cultivated land management scale and cultivated land use efficiency in northeast China expanded and the dispersion was enhanced. Regions with smaller peasant household’s cultivated land management scale and lower cultivated land use efficiency still accounted for a large proportion. The polarization of peasant household’s cultivated land management scale was gradually obvious, and the polarization of cultivated land use efficiency was mitigated. 3) There is a significant inverted “U”-shaped relationship between peasant household’s cultivated land management scale and cultivated land use efficiency in northeast China. When peasant household’s cultivated land management scale is at a low level, its growth has a promoting effect on cultivated land use efficiency. However, after reaching a certain level, the effect of peasant household’s cultivated land management scale on cultivated land use efficiency changes from positive to negative. 4) Currently, the moderate peasant household’s cultivated land management scale in northeast China is 11.61-11.95 hm² without considering the interconnectivity of regions, while it is 10.04-10.10 hm² that considering the interconnectivity of regions.

This study defines and evaluates the level of urban economic high-quality development (UEHQD) under the goal of common prosperity, revealing its dynamic evolution and driving factors to foster spatial momentum for shared affluence. Using a longitudinal and transversal tiered evaluation method, we measure UEHQD levels and further analyze their distribution dynamics and driving forces. Key findings include: 1) The UEHQD level demonstrates an overall upward trend. Eastern high-performance cities in China exhibit “spillover effects” radiating to neighboring areas, central cities show significant “catch-up effects”, western cities remain in a fluctuating phase, while northeastern cities urgently require revitalization to reverse developmental stagnation. 2) The transfer probability of the whole country and the four major regions has changed from upward to downward within the relative UEHQD level [0.93,0.99]. Eastern cities demonstrate strong resilience against downward trends, western cities lag slightly in upward transition potential, and northeastern cities show weak upward momentum. The spatial imbalance pattern is projected to persist which is characterized by “eastern superiority over western regions, southern strength versus northern weakness”. 3) Innovation vitality directly drives UEHQD, with industrial coordination and service sharing serving as key channels. Ecological preservation and open connectivity play secondary roles, while income growth exerts indirect effects, with factor interactions collectively propelling development. Regionally, innovation vitality and industrial coordination dominate UEHQD dynamics: eastern and central regions prioritize innovation, western regions emphasize innovation vitality-service sharing synergy, and northeastern regions highlight industrial coordination’s positive impacts on ecological and service systems. Across city scales, innovation remains paramount: megacities rely on innovation-ecology-industry synergies, large cities on innovation-ecology collaboration, while small-medium cities depend on innovation-service-industry interactions.

Regional industrial renewal has been considered as an important factor for regional economic development. Currently, evolutionary economic geography has pay much attention to the role of technological relatedness in the entry of new industries in regional industrial renewal studies, while the role of technological relatedness in the exit of incumbent industries has often been neglected. One of the reasons for this neglection is the lack of method to identify related and unrelated industries which exit from regions. This paper develops a new method to identify related and unrelated exit industries. Based on this method, we first analyze the number and spatial distribution of related and unrelated exit industries and then further investigate the relationship between (un)related exit and the level of regional economic development. The findings are shown as follows. First, compared with related exit industries, the number of unrelated exit industries are much larger. The number of unrelated exit industries account for about 65% in the total number of exit industries from 1998 to 2012, while the figure for related exit industries is at about 35%. This means that technological relatedness play an important role in the exit of industries in regions. This finding is in line with the previous studies. Second, the spatial distribution of unrelated and related industries varies. Regions in eastern and central China has more related exit industries while the regions in western China has more unrelated exit industries. Third, technological related play a decreasing role in the economic development process. We find that the share of unrelated exit industries in regions is positively associated with the level of regional economic development while there is a negative relationship between the share of related exit industries in regions and the level of regional economic development. The findings of this paper have important implications for policymakers in pursuit of eliminating backward production capacity and promoting industrial renewal.

The supply-and-demand of urban industrial and residential spaces determines the commuting behaviors. With the emergence of the stock-renewal era, the dual pressure of industrial upgrading and rising housing prices pose severe challenges to achieving jobs-housing balance and high-quality commuting in megacities. By integrating theories and methodologies from spatiotemporal behavioral geography and evolutionary economic geography, this study utilizes mobile phone signaling data and micro-level enterprise data, and investigates the causal relationship between urban industrial dynamics and changes of commuting patterns with a sample of 164 subdistricts within exurban ring in Shanghai. The changing commuting patterns are measured through workers’ average commuting distance and entropy index of residential distribution, while industrial evolution dynamics (path-dependence vs. path-breaking) is characterized using industrial relatedness density metrics. The results reveal that: 1) From 2017 to 2023, commuting pattern changes exhibited distinct core-periphery differentiation in Shanghai, with subdistricts demonstrating path-dependent and path-breaking industrial evolution characteristics forming spatially interlocked mosaics. 2) Subdistricts with a path-dependent industrial evolution feature might experience a decrease of the average commuting distance and a more concentrated spatial distribution of employees’ residences. This is mainly because that the table industrial development in those subdistricts requires a consistent set of skills from employees, who in turn actively strive to improve their commuting conditions. 3) Subdistricts with a path-breaking industrial evolution feature might experience an increase of the average commuting distance and a more dispersed spatial distribution of employees’ residences. This is attributed to the significant changes of industrial development in those subdistricts lead to a demand for diverse skill sets, thereby attracting a wider range of worker and bridging the local labor gap. This study highlights the existence of conflicting tensions and potential reconciliations between urban industrial transition and improvements in commuting efficiency. To tackle this challenge, coordination, mutual support, and flexible management of the policy instruments such as urban planning, transportation planning, and industrial planning is urgently needed.

Under the background of carbon peak and carbon neutrality, data centers with high energy-consumption characteristics are facing a huge challenge of energy saving and emission reduction, which is related to the achievement of the goal of green and high-quality development of new infrastructure. To address this challenge, the national level has formulated the “East Data and West Calculation” Project to leverage the advantages of resource endowment in the west and alleviate the pressure on resources and the environment in the east. The carbon emission reduction effect and spatial transfer law resulting from this strategy are scientific issues worth studying. To investigate these issues, this study constructs a carbon accounting framework based on the fine-grained data of data centers in each region of China. It simulates and predicts the amount of carbon emissions and the scale of spatial transfer of data centers in 2 scenarios: with or without the implementation of the “East Data and West Calculation” Project in 2020—2030. The study also analyzes the potential of energy saving and emission reduction associated with the strategy. The results of the study demonstrate that the “East Data and West Calculation” Project can achieve energy saving and emission reduction in data centers by optimizing the spatial distribution of computational resources. In the context of the strategy, the total carbon emissions of national data centers in 2030 are expected to reach 2.11×10⁸ t, which is a reduction of 22.74×10⁶ t compared to the scenario without the strategy. Specifically, the strategy effectively relieves the pressure on carbon emissions in the regions of the Beijing-Tianjin-Hebei Hub and the Yangtze River Delta Hub, resulting in a reduction of 55.45×10⁶ t of CO₂ in the east. Additionally, the project facilitates the transfer of 17.89×10⁶ t of CO₂ to the central region and 13.33×10⁶ t of CO₂ to the western region, thereby slowing down the rate of increase of carbon emissions in high-carbon regions. The conclusions of this study provide data support for understanding the scale and spatial transfer pattern of carbon emissions from data centers, a new type of infrastructure, in the context of the east data and west calculation strategy.

The reconstruction of digital technology-driven urban scenarios has profoundly transformed traditional human-environment interaction patterns, with the place embeddedness of mobile talents exhibiting multi-dimensional spatial effects. Based on China’s Migrant Population Dynamic Monitoring Survey (CMDS) data and urban digital economy indices, this study employs the entropy weighting method to construct an indicator system encompassing three dimensions—economic embeddedness, cultural embeddedness, and emotional embeddedness—systematically investigating the mechanisms and spatial heterogeneity of the digital economy’s impact on talent localization. Key findings include: 1) A 1-unit increase in the urban digital economy index enhances overall talent embeddedness by 0.155 units (P<0.01), with the most significant effect observed on economic embeddedness (β=0.323), primarily driven by job creation in digital industries and improvements in social security. 2) Spatial effects display gradient disparities: second- and third-tier cities demonstrate the strongest promotion effect (β=0.145), significantly exceeding that of first-tier cities (β=0.054), while fourth- and fifth-tier cities show no statistically significant impact. 3) Mechanism analysis reveals that the digital economy elevates embeddedness by 0.051 units for socially isolated groups (those limited to hometown connections or lacking offline social networks) through a “virtual social compensation”mechanism, effectively expanding their online social capital acquisition channels. This study uncovers three mechanisms through which digital economy development reshapes talent embeddedness: First, the digital economy fosters an “economic-amenity synergy”: It generates high-quality employment through industrial upgrading (economic embeddedness) while optimizing public services like healthcare and commuting via smart city initiatives (cultural/emotional embeddedness), creating a virtuous cycle between digital competitiveness and talent attraction. Second, family-oriented mobility emerges as a critical pathway. Digital technologies enhance urban settlement capabilities for migrant families through remote employment and online services, though institutional barriers to welfare access tied to household registration (hukou) persist. Recommendations include implementing gradient household registration reforms and tailored family service packages. Third, digital media reconfigures social network dynamics. Online communities and virtual interactions compensate for offline social deficiencies, significantly improving embeddedness efficiency for weak-tie groups. Proposed solutions include“digital community” initiatives to foster social capital accumulation.

China’s innovative network exhibits high productivity combined with high volatility. While existing research has focused on the generative mechanisms of the network, the process of maintaining or dissolving innovative relationships and the underlying causes of high volatility remain unclear. Based on the “generation-maintenance” perspective, this study constructs a national innovative network using collaborative invention patents from 2001 to 2019, explores its evolutionary characteristics, and employs a separable temporal index random graph model to reveal the mechanisms of generating and maintaining innovative relationships. The results show that: 1) The scale of China’s innovative network is expanding, and the spatial pattern is evolving from a triangle to a “diamond + cross” shape. The innovation network maintenance process presents an evolutionary path of “upper triangle-full triangle-diamond-diamond+cross” in four stages. The formation process presents a spatial pattern similar to the maintenance process in the next stage, and it changes from the north-to-Shenzhen dominant to the urban agglomeration as the main body, reflecting the path-dependent effect. The unwinding process is dominated by the core nodes in the generating network, as well as cities in the northeast, southwest. 2) The evolutionary mechanisms of the innovative network show stage-dependent differentiation. The agglomeration effect has changed from inhibiting to promoting innovative relationships, while the intermediary effect has shifted from promoting to inhibiting innovative relationships. The effects of transmission, GDP, innovation level, geographic proximity, and organizational proximity on urban innovative relationships have continued to decline. 3) The evolutionary mechanisms of generating and maintaining innovative relationships have differences. Economic scale and innovation level have become ineffective in maintaining innovative relationships, while the effect of geographic proximity on generating innovative relationships has continued to decline but has increased in maintaining innovative relationships. This study addresses the lack of exploration into the mechanisms of maintaining innovative relationships in existing research and provides theoretical and methodological support for improving the growth and reducing the volatility of the innovative network, thereby optimizing the regional innovation system.

The urban system in China is essentially a multilayer network composed of evolving and interacting single-layer relational networks. Understanding how the embedded characteristics of cities in these multilayer networks influence energy utilization efficiency is crucial for effectively balancing economic growth and sustainable development in China. This article sets out to empirically investigate the impacts of multilayer network embeddedness on energy utilization efficiency based on a panel data set covering 282 prefecture-level and above cities in China in 2005, 2010, 2015, and 2020. To this end, three single networks, i.e., network of top 500 public companies, network of patent transfer, and network of flight, are used to construct the edge-colored multigraph. Three main findings stand out. First, both multilayer degree centrality and multilayer PageRank centrality have a significant positive impact on the energy utilization efficiency of Chinese cities, which is still valid after a series of robustness and endogeneity tests. Second, urban absorptive capacity acts as a positive moderator between multilayer network embedding and energy utilization efficiency, with energy efficiency effects increasing alongside improvements in urban green innovation, entrepreneurial incubation, industrial structure upgrading, and digital economy development. Third, the energy efficiency effects of multilayer network embedding demonstrate multidimensional heterogeneity, with non-resource-based cities benefiting more from multilayer PageRank centrality and resource-based cities from multilayer degree centrality. In addition, central and western cities experience greater energy efficiency gains from multilayer network embedding compared to eastern cities. The results underscore the significance of a city’s integration into extensive networks for its energy performance, highlighting network capital as a crucial component of urban energy utilization efficiency. The paper also fills the gap in the juxtaposition between agglomeration and network economies, by clarifying that city network capital and local agglomeration factors have an interactive and complementary relationship in enhancing urban energy utilization efficiency. This results highlight the need for Chinese government to promote multilayer urban networks, enhance urban absorptive capacity, and consider the differing impacts of network embedding for better and coordinated development of urban energy utilization efficiency.

Under the “dual carbon” goals, conducting in-depth research on the role of the digital economy, in improving carbon emission performance and its impact mechanism on promoting the low-carbon transformation of the socio-economic structure, is beneficial for carbon reduction and helps to achieve the “dual carbon” targets on time. Based on the theoretical mechanism of how the digital economy affects carbon emission performance, this article calculates the development of the urban digital economy and carbon emission performance, visualizes the spatial-temporal evolution trends of digital economy development and carbon emission performance, and empirically tests the impact mechanism and spatial effects of the digital economy on the carbon emission performance of Chinese cities. The results show that: 1) The overall development level of the digital economy continues to improve, and the digital divide phenomenon has been alleviated to some extent. However, the overall level of carbon emission performance remains relatively low, with significant room for improvement. 2) The digital economy can significantly improve urban carbon emission performance, and the results remain robust after a series of sensitivity tests. The impact mechanism results reveal that the digital economy positively influences carbon emission performance mainly through advancements in green technologies, industrial agglomeration, and improvements in energy efficiency. 3) Heterogeneity analysis reveals that the impact of the digital economy on urban carbon emission performance varies by region and resource endowment. It can significantly improve the carbon emission performance in eastern regions and non-resource-based cities, but its impact on central and western regions and resource-based cities has yet to be seen. 4) Spatial spillover effect analysis shows that the development of the digital economy not only significantly improves local carbon emission performance but also promotes the improvement of carbon emission performance in neighboring regions through spatial spillover effects. This reflects its important role in regional green transformation. However, its spillover effect is highly sensitive to distance, and the spillover effect under the economic geography nested weight matrix and the inverse distance weight matrix is significantly lower than that under the geographical distance weight matrix.

Underdeveloped regions are an important manifestation of unbalanced and insufficient development, as well as an outstanding shortcoming facing the advancement of Chinese-style 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 human-earth 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 industrialization-underdeveloped 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 co-unties, economically underdeveloped counties constrained by education and urbanization, multi-factor 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.

The impact of geopolitics on patterns of global flows of critical resources is an important 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 transportation 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 other 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 conflict, 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 related 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 Mediterranean. 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 production 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 transportation 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 dependence on oil imports. This paper helps to enrich the study of the relationship between geopolitics and global resource flow patterns and deepen the theoretical understanding of the impact of geopolitics on global resource flow patterns.

Using the Mann-Kendall method, the growth rate of China’s urbanization since the reform and opening up was divided into 2 stages, 1978—1994 and 1995—2020, and the pattern of China’s provincial urbanization in different stages was analyzed. Using panel data, the dynamic mechanism of this pattern was discussed from the intra-regional and inter-regional levels. The results show that: 1) The spatial and temporal dynamic differences of China’s provincial urbanization are significant. In 1978, China’s regional urbanization pattern showed a pattern of high in the north and low in the south, and high in the east and low in the west. In 1994, the pattern of urbanization presented the urbanization rate of the provinces in the north and southeast coasts is relatively high, and southwestern provinces are relatively low. The urbanization level in 2020 has formed a pattern of gradual decline from east to west. 2) The estimation results of spatial Durbin model show that labor demand as a pulling force has a stronger effect on the urbanization rate between regions than within regions; The effect of the income gap between urban and rural areas on urbanization rate is firstly suppressed and then promoted, and the intensity of the effect between regions is always stronger than that within regions. The regional economic development disparities, acting as an inter-regional push factor, have a significant positive effect on urbanization only in the initial phase; the income gap between urban areas, serving as an inter-regional pull factor, overall shows an effect that initially suppresses and then promotes urbanization rates, with the impact shifting from being stronger inter-regionally to being stronger intra-regionally. 3) The results of Geographically Weighted Regression model show that, in economically developed regions, labor demand and urban-rural income gap, as regional push and pull forces, have a positive driving effect on the urbanization of each province. The positive effect of regional economic development differences and inter-regional urban income gaps on urbanization has obvious fluctuations in space. But the change has become stronger over time, indicating that the development gaps between regions and between urban and rural areas are constantly promoting the urbanization development of various provinces as a push and pull force between regions.

This study aims to examine the similarities and differences between Chinese and international geographical research by comparing and analyzing research hotspots from the 35th International Geographical Congress (35th IGC) and the 2024 Annual Meeting of the American Association of Geographers (AAG-AM), to provide insights for Chinese geographical research. We employed a Python-based web scraping program to extract and analyze report data from various countries’ conference websites. Our study reveals commonalities in Chinese and international geographical research concerning global issues such as tourism, leisure and global change, and future Earth. However, some disparities exist in research foci and methodologies. At the 35th IGC, international research emphasized socio-cultural dimensions, including gender and geography, and cultural approach, while Chinese scholars focused more on areas closely aligned with national development strategies, such as land use and agricultural geography. Moreover, the 2024 AAG-AM data indicate that international research excels in environmental and Earth Sciences, GeoAI, and deep learning, whereas Chinese research concentrates on geospatial solutions for major challenges and human dynamics. This study suggests that Chinese geographical research could draw upon international experiences, adopt interdisciplinary research methods, utilize advanced technological tools, focus on social justice and cultural diversity, strengthen research in political geography and area studies, and enhance international cooperation. These efforts will elevate the international standing of Chinese geographical research and amplify its role in the global geographical arena.

Wetlands play an important role in flood regulation, water purification, and biodiversity maintenance, etc., which are closely related to human well-being and survival. Wetland Science is an important part of geographical science and is of great significance in supporting scientific development and serving the construction of national ecological civilization. The National Natural Science Foundation of China (NSFC) is the main channel to fund basic research of Wetland Science, and the funding status can reflect the research hotspots and development directions in Wetland Science. In this study, 519 projects related to Wetland Science funded by the discipline of Geographic Sciences (application code D01) in 1986—2023 were covered by titles or keywords including “wetland”“marsh”“peatland”“mangrove” or “mudflat”. The systematic analysis was conducted from the perspectives of application code, research area, research content and keywords. The results show that the funded projects in Wetland Science have experienced two “decade” of rapid and steady growth from 2002 to 2012 and from 2013 to 2023; these projects are mainly concentrated in landscape geography and integrated physical geography (D0105), remote sensing science (D0113) and biogeography and soil geography (D0103). In terms of research objects, inland marsh wetlands and coastal wetlands are the main focus; in terms of research contents, “remote sensing monitoring”“process”“climate change”“vegetation” and “function” appeared more frequently. The keyword network relationship shows that “remote sensing and spectrum”“remote sensing and vegetation” and “landscape and pattern” co-occur more frequently, which characterizes the geographical features of the current development of wetland science and the changing research methods. Currently, the Geographical Sciences discipline of NSFC is further optimizing the branch discipline layout and keywords, strengthening the cross-field and cross-disciplinary interactions and fusions, guiding focus on the fundamental theories and frontier hotspots of Wetland Science, and promoting the high-quality development of wetland science research in China.

Methane emissions from floodplain wetlands are an essential component of the global methane budget. A comprehensive understanding of these emissions is crucial for accurately quantifying regional methane budgets. This study reviews the primary processes involved in methane production, oxidation, and transport within floodplain wetlands. It systematically examines the impacts of hydrological dynamics, vegetation, soil characteristics, temperature, human activities, and climate change on methane emissions from these ecosystems. Additionally, the study summarizes the wetland methane process models utilized in global carbon projects and traces their historical development. This study identifies the challenges associated with simulating methane emissions from floodplain wetlands, including dynamic hydrological processes, variations in soil properties, and the development of vegetation. Furthermore, the study suggests that future research should enhance the understanding of the mechanisms by which complex hydrological processes influence methane emissions in floodplain wetlands. This involves integrating periodic hydrological fluctuations, alternating wet and dry soil conditions, and dynamic changes in vegetation into wetland methane process models. Furthermore, it is necessary to strengthen the establishment of methane flux observation stations in floodplain wetlands to provide long-term, continuous data support for calibrating methane process model parameters, thereby improving the accuracy of regional methane emission assessments. By integrating these factors, methane process models for floodplain wetlands can be enhanced, providing robust scientific support for achieving global carbon neutrality goals.

Based on discussing the significant spatial heterogeneity of the three components of productive forces, this paper systematically analyzes the changes of regional attributes and spatial structure brought about by the emergence of new quality productive forces. Then, the basic law of the distribution of new quality productive forces is discussed from three aspects, such as new factors of new quality productive forces, territorial production complexes and national network systems. Subsequently, the evolution trends of new quality productive forces distribution is revealed. It is concluded that the mechanism of new transformation of production relations lies in the realization of the value of knowledge and the rationalization of benefit sharing, the changes and adaptive management of labor relations caused by digital intelligence, and the tradeoff between regional disequilibrium and spatial fairness caused by scientific and technological innovation ability. Repositioning the regional major functions, re-examining the regional comparative advantages and development paths, and re-constructing the interaction between different major functional zones are the main aspects of constructing the institutional system adapting to the new production relations based on the strategy of the major functional zones. The key points of supporting reforms to develop new quality productive forces according to local conditions are as follows: Focusing on improving scientific and technological innovation capacity, forming a mechanism and institution for the integration of science, technology, education and talents with local characteristics; focusing on scientific and technological innovation-driven development, forming a mechanism and institution for the spatial coupling and coordinated development of innovation chain and industrial chain; focusing on the systematic planning of a coordinated national response, forming a mechanism and institution for the production network and system for the formation of new quality productive forces by giving full play to the comparative advantages of different regions; focusing on open economic patterns, forming a mechanism and institution for new quality productive forces with competitive security and resilience.