Low efficiency of earth kilns used in the carbonising process of wood to make charcoal has been reported as one of the sources of increasing charcoal wastes in the global south. However, the potential link and approaches of converting charcoal wastes-to-valuable energy and for the environmental health is not well known in Africa. Promoting local community capacity engagement in the production and reutilisation of recycled charcoal wastes at the households’ level is one of important measures to maintain environmental services for sustainability since households make decisions on the type of energy used. This paper, presents an approach of converting charcoal wastes to fuel energy for rural households and environmental health in Kilosa District, Tanzania. To achieve the objective of this research, the primary data were collected through interviews held with 298 randomly selected households, Focus Group Discussions and observations. IBM SPSS statistics version 20 Cross tab tools were used in the data analysis. Results revealed that the conversion of charcoal wastes-to-fuel energy approach used in this research demonstrates the ability of recyclable briquettes made from the locally available charcoal pollutants collected at different stages from earth kilns, to selling centers, improves tree harvest behaviour, adds another fuel energy source through reutilisation, and ultimate reduces pollution at the local level. Thus, the study provides a basis for policymakers to adopt charcoal wastes recycling strategies to address matters related to energy and ultimately enhances environmental health for sustainable development in Tanzania and beyond.

Urban trees are valuable resources for urban areas as they have the capacity to reduce ambient temperatures, mitigate urban heat island effects and reduce runoff of rainwater playing an important role in mitigating the impacts of climate change by reducing atmospheric carbon dioxide (CO2). It also helps to reduce aerial suspended particulate matter, add visual appeal to the urban landscape sequestrating a significant amount of carbon from ambient atmospheric CO2. Carbon storage by urban trees in the ring road area of the Kathmandu Valley was quantified to assess the magnitude and role of urban forests in relation to mitigate the impact of global climate change. A total of 40 sample plots were placed randomly for the detailed carbon assessment. Aboveground and belowground carbon pools were considered in the detailed assessment. Furthermore, quality assurance (QA) and quality control (QC) were maintained through regular monitoring and capacity building of the field crews while collecting the bio-physical data. The assessment recorded a total of 33 different species of plants in the avenue’s plantation sites in ring road. The mean seedling, sapling, and tree density was found to be 2149585 and 185 per hectare. The mean carbon stock per hectare in the avenue plantation of the ring road area was 24.03 tC ha1 and the existing total carbon stock was 7785.72 tC in 2021. Likewise, the total baseline carbon dioxide equivalent (tCO2e) in the avenue plantation was found to be 28573.60 tCO2e. The carbon dioxide emission from the transport sector in the ring road area in a full movement scenario was 312888.00 tCO2e per annum, while the net emissions was 42547 tCO2e. There was a deficit of carbon dioxide in terms of stock by avenue plantations of 14000.8 tCO2e.This study indicates that the existing urban forest plantation is unable to sequestrate or offset the carbon dioxide that is emitted through the transportation sector. Consequently, open spaces like riverbanks and any other public lands, in which urban forests could be developed has to be planned for the green infrastructure and plantation of the multipurpose trees. The distinct values of forests in and around urban areas have to be recognized in the specific policies and plans for the sustainable management of urban and peri-urban forests to meet the adverse impact of global climate change. In addition, this study provides insights for decision-makers to better understand the role of urban forests and make sustainable management plans for urban forests in the cities like in Kathmandu Valley.

Delimiting ecological space scientifically and making reasonable predictions of the spatial-temporal trend of changes in the dominant ecosystem service functions (ESFs) are the basis of constructing an ecological protection pattern of territorial space, which has important theoretical significance and application value. At present, most research on the identification, functional partitioning and pattern reconstruction of ecological space refers to the current ESFs and their structural information, which ignores the spatial-temporal dynamic nature of the comprehensive and dominant ESFs, and does not seriously consider the change simulation in the dominant ESFs of the future ecological space. This affects the rationality of constructing an ecological space protection pattern to some extent. In this study, we propose an ecological space delimitation method based on the dynamic change characteristics of the ESFs, realize the identification of the ecological space range in Qionglai city and solve the problem of ignoring the spatial-temporal changes of ESFs in current research. On this basis, we also apply the Markov-CA model to integrate the spatial-temporal change characteristics of the dominant ESFs, successfully realize the simulation of the spatial-temporal changes in the dominant ESFs in Qionglai city’s ecological space in 2025, find a suitable method for simulating ecological spatial-temporal changes and also provide a basis for constructing a reasonable ecological space protection pattern. This study finds that the comprehensive quantity of ESF and its annual rate of change in Qionglai city show obvious dynamics, which confirms the necessity of considering the dynamic characteristics of ESFs when identifying ecological space. The areas of ecological space in Qionglai city represent 98307 ha by using the ecological space identification method proposed in this study, which is consistent with the ecological spatial distribution in the local ecological civilization construction plan. This confirms the reliability of the ecological space identification method based on the dynamic characteristics of the ESFs. The results also show that the dominant ESFs in Qionglai city represented strong non-stationary characteristics during 2003-2019, which showed that we should fully consider the influence of the dynamics in the dominant ESFs on the future ESF pattern during the process of constructing the ecological spatial protection pattern. The Markov-CA model realized the simulation of spatial-temporal changes in the dominant ESFs with a high precision Kappa coefficient of above 0.95, which illustrated the feasibility of using this model to simulate the future dominant ESF spatial pattern. The simulation results showed that the dominant ESFs in Qionglai will still undergo mutual conversions during 2019-2025 due to the effect of the their non-stationary nature. The ecological space will still maintain the three dominant ESFs of primary product production, climate regulation and hydrological regulation in 2025, but their areas will change to 32793 ha, 52490 ha and 13024 ha, respectively. This study can serve as a scientific reference for the delimitation of the ecological conservation redline, ecological function regionalization and the construction of an ecological spatial protection pattern.

Abstract: By studying the structural characteristics and carbon storage of the mangrove island ecosystem in the 
Beibu Gulf, this study provides a scientific basis for mangrove ecological compensation in the coastal areas of 
Guangxi, South China Sea. On the basis of the unmanned aerial vehicle remote sensing images and a sample plot 
survey, the object-oriented multi-scale segmentation algorithm is used to extract the mangrove community type information, and one-way analysis of variance is conducted to analyse the structural characteristics of the mangrove 
community. The carbon storage and carbon density of different mangrove ecosystems were obtained based on the 
allometric growth equation of mangrove plants. The analysis yielded four main results. (1) The island group covers 
about 27.10 ha, 41.32% (11.20 ha) of which represents mangrove areas. The mangrove forest is widely distributed 
in the tidal flats around the islands. (2) The main mangrove types were Aegiceras corniculatum, Kandelia obovata + 
Aegiceras corniculatum, Avicennia marina + Aegiceras corniculatum and Avicennia marina communities. (3) 
Amongst the mangrove plants, Avicennia marina had the highest biomass (18.52 kg plant–1), followed by Kandelia 
obovata (7.84 kg plant–1) and Aegiceras corniculatum (3.85 kg plant–1). (4) The mangrove carbon density difference 
was significant. Kandelia obovata had the highest carbon density (148.03 t ha–1), followed by Avicennia marina
(104.79 t ha–1) and Aegiceras corniculatum (99.24 t ha–1). The carbon storage of the mangrove island ecosystem 
was 1194.70 t, which was higher than in other areas with the same latitude. The carbon sequestration capacity of 
the mangrove was relatively strong.

The monitoring-evaluation-warning of territorial spatial planning is not only the key content of China Spatial Planning Observation Network (CSPON) but also an important mean to implement the people-centered development thought. However, existing studies predominantly emphasize spatial elements while overlooking resident well-being. The Capability Approach (CA) has been a powerful and more widely used evaluative framework for individual well-being and public policy. From the view of the CA, well-being is defined as capabilities and is the end for the human-oriented development. Inspired by the CA, this paper constructed an innovative conceptual model for well-being-oriented monitoring-evaluation-warning of territorial spatial planning. In this conceptual model, well-being is the final target instead of the spatial results, as well as a people-centered development ideology. The model is composed of three core elements: dynamic monitoring, accurate evaluation, and timely early warning. It is technologically underpinned by big data, artificial intelligence, and cloud computing, which together offer robust analytical capabilities. Compared to existing research, our monitoring, evaluation, and warning system not only focuses on territorial space and key technologies but also encompasses the well-being of residents and the relationship between territorial space and resident well-being. Thus, we extend the scope of traditional studies by integrating well-being into the implementation and supervision of the territorial spatial planning, ensuring a more holistic and inclusive assessment of the planning's impact. To support the evolution of smart planning, we proposed three smart model systems for dynamic monitoring, accurate evaluation, and timely early warning respectively. The results of the practical application in the built environment show the promise of applying the model system to CSPON. This paper enriches existing literature by incorporating the CA and well-being, offering a novel perspective on how to reconceptualize the monitoring, evaluation and warning of territorial spatial planning. This paper also illustrates the pathways on how to implement the well-being thought in the monitoring-evaluation-warning of territorial spatial planning and providing theoretical reference and method support for CSPON construction.

Normalised monitoring of natural resources plays a crucial role in regulating natural resources and guaranteeing the effectiveness of management policies, and it is a key support for achieving high-quality economic and social development in natural resources. In view of the challenges of natural resources monitoring in terms of rapid perception of natural resources information, comprehensive analysis of human-land relations in land space, and efficient support for the precise management of operations, the objectives and connotation of natural resources normalised monitoring was systematically analyzed. By integrating the requirements of contemporary land space monitoring and supervision, this study proposes the "intelligent perception-dynamic cognition-accurate control" framework for natural resources monitoring. This framework focuses on three key aspects: perception, cognition, and control. In the perception phase, we established an integrated data perception network to dynamically perceive and rapidly identify natural resources using multi-source data. Subsequently, through dynamic analysis incorporating indicators like implementation effectiveness, bottom line control, boundary control, and structural efficiency, we explored the correlation of natural resource elements, process coupling, trend prediction, and early warning. Utilizing national land spatial planning and control tools, our framework promotes proactive trends while controlling negative ones, facilitating comprehensive element coupling analysis, full-cycle process management, and spatial use regulation. To illustrate the practical application of our approach, we examined the supervision and protection of arable land, demonstrating how normalised monitoring enables comprehensive monitoring, dynamic assessment, and decision-making support. To ensure the effective application of monitoring results, it is necessary to clarify the legal status and usage methods of regular monitoring results from a policy perspective. This will also facilitate the promotion and application of regular monitoring. At the implementation level, it is recommended to establish a mechanism for results sharing and business collaboration, thus achieving the goal of "one monitoring, multiple topics, and numerous applications" in regular monitoring of natural resources. This study serves as a valuable reference for the monitoring and regulation of natural resources, offering insights into achieving full coverage, element inclusion, and process management.

Continental chemical weathering is one of the key processes shaping the Earth's surface morphology, influencing the global material cycle and regulating the global climate. Effectively tracing surface weathering processes has consistently been a focal point within geosciences. Lithium and its isotopes, distinguished by their unique chemical properties, exhibit great potential in tracing continental silicate weathering. This article systematically reviewed the literature and analyzed the fractionation behavior and patterns of lithium isotopes during chemical weathering processes in experimental simulations, weathering profiles, and at the watershed scales. Based on this analysis, the following insights are obtained: 1) The continental weathering process in surface environments is complex, exhibiting a nonlinear relationship between chemical weathering intensity and the δ⁷Li value. 2) Integrative studies of published data indicate that the relationship between the δ⁷Li values of weathered materials and lithium content in highly weathered regions exhibits two patterns (The variation in Li content is limited, yet the δ⁷Li values exhibit significant differentiation; conversely, there is a certain degree of variation in Li content when the differentiation of δ⁷Li values is limited), with the underlying causes requiring further investigation. 3) The red earth region in southern China is an ideal area for weathering research, showing potential in exploring the mechanisms and patterns of lithium isotope fractionation. This article argues that there are still issues in using lithium isotopes as a tracer for chemical weathering, such as insufficient quantitative studies of complex processes, limited multi-scale integrated research, unclear mechanisms of lithium isotopes in highly weathered products, and the lack of a global weathering estimation model. Future efforts should focus on enhancing laboratory simulations, empirical studies, and multi-scale integrated research to further explore the potential of lithium isotope mechanisms in underexplored areas and validate the effectiveness of lithium isotope tracing in chemical weathering through the combined use of multi-isotope systems.

Territorial ecological restoration (TER) is vital for China to address land degradation challenges, achieve its carbon neutrality strategy, and build the Beautiful China. However, the current TER planning system needs enhancement in its systematic, holistic, and integrated approach to support the unified conservation and restoration of mountains, rivers, forests, farmlands, lakes, and grasslands. This paper draws on the Land Degradation Neutrality (LDN) concept proposed by the United Nations Sustainable Development Goal 15.3 to establish a logical framework for LDN-oriented TER planning in China, highlighting key research questions to achieve LDN. The findings are: (1) The evolution of LDN reflects the global shift from fragmented to integrated ecological restoration projects. Its conceptual framework and implementation logic offer foundational and universal aspects that can guide the exploration of systematic TER planning in China. (2) LDN-oriented TER planning focuses on addressing land degradation through a singular metric (the proportion of degraded land) to achieve one goal (LDN), following a planning logic of "status analysis-degradation identification-setting LDN goals-identifying LDN pattern-implementing LDN measures-monitoring LDN". (3) Key research questions for achieving LDN in TER include diagnosis of ecological problems, identification of ecological restoration priority area, delineation of TER implementation units, and design of TER monitoring mechanisms. To promote the localization of the LDN concept, it is recommended to establish a balancing mechanism for ecosystem degradation and restoration, targeting the avoidance, alleviation, and restoration of quantity, quality, and productivity degradation across all land-use types, so as to coordinate planning formulation and project implementation.

Whether and how the "dual-carbon" goals could be included in the territorial spatial planning law (TSPL) is a crucial issue in the construction of the rule of law for territorial spatial planning (TSP). By reviewing the existing legal documents and the practice of TSP, the legislative mode of "systematic integration+special embedding" can be adopted to integrate the "dual-carbon" goals into the TSPL in a comprehensive way. By clarifying the principles of periodicity and spatiality of the "dual-carbon" goals, a specialized system of "dual-carbon" regulations will be constructed. By proposing a legislative optimization plan that emphasizes both procedural and substantive aspects, improving the allocation of administrative powers of the relevant departments, scientifically setting up legal responsibilities, and making sure that the TSPL is well connected with energy legislation, the codification of ecological and environmental codes. The above measures provide a guarantee of TSP for the realization of the "dual-carbon" goals.

A watershed is a spatial carrier that integrates development and security, and is an important region for achieving harmonious coexistence between human and nature in modernization. As such, watershed spatial governance has become an important entry point and strategic project for current provincial and municipal spatial planning. To deepen the theoretical understanding of watershed spatial governance, this study established the fundamental framework of "scale connection, value realization, path optimization" and conducted empirical research using Hubei province as a case study. The results showed that: (1) Based on the theory of the relationship between human and water, watershed spatial governance should integrate natural and administrative boundaries. It should prioritize the coordinated management of ecological and economic functions in distinct zones, while also considering the objectives of ecological conservation and social advancement. (2) The spatial difference between economic value and ecological value of watershed in Hubei was obvious, and the ecological protection and economic development of some watershed units were relatively unbalanced. (3) The realization of spatial multi-value could effectively guide watershed zoning and classification management. In Hubei, the watershed governance zoning included five types: "four modernizations" complex type, livable town construction type, modern agricultural development type, ecological security protection type, and ecological security-economic development complex type. The research results can provide guidance for deepening the human-water relationship in watersheds and ensuring the implementation of watershed governance planning.

The meticulous construction of traditional village spaces has emerged as a pivotal direction for the protection and utilization of contiguous areas, imposing heightened demands on spatial cognition and revitalization. This research undertakes a comprehensive analysis at both regional and village levels: regionally, spatial analysis methods grounded in GIS geographic information systems are deployed to scrutinize the geographic distribution, density, and spatial differentiation characteristics of traditional Huizhou villages. At the village level, empirical investigations leveraging 3D scanning and virtual reality technologies are conducted to explore data channels and technical applicability in data acquisition and utilization. The findings reveal that traditional Huizhou villages exhibit a pattern of highly concentrated distribution in successive clusters, posing significant challenges related to homogeneous competition and development. Consequently, a collaborative interactive technology system has been established to analyze commonalities and distinctions among villages, enabling optimized spatial design. The developed technical system and methodology can refine regional resource allocation and dynamically elevate spatial quality, bearing substantial significance for the sustainable development of traditional regional villages.

Based on the diverse nexus between humans and nature, exploring innovative pathways and regional models for rural revitalization stands as a strategic cornerstone and a cutting-edge focus within rural studies. Following a systematical review on the shift of rural development paradigms, we in this paper propose an innovative pathway of rural neo-endogenous development driven by knowledge through the integration of concepts such as social innovation and rural transformation. Essentially, "knowledge-driven" can be understood as a process-based innovation, wherein various stakeholders participate in the generation, dissemination, feedback, and regeneration of scientific knowledge and local wisdom. This process ultimately precipitates shifts in behaviors and attitudes of both local and extra-local actors, thereby giving rise to collective insights and solutions for rural development. Regarding the functioning mechanisms, "knowledge-driven" typically facilitates the iteration of technological paths for rural development via four interconnected means: constructing novel discourses for rural transformation, empowering local communities, forging connections between local and extra-localities, and innovating rural governance. In practice implementation, "knowledge-driven" engages multiple stakeholders and unfolds across three sequential stages, they are, knowledge/experimentation searching, diffusion and expression of interest, collective learning and co-ordination. In conclusion, we contend that transcending the urban-centric "core-periphery" mindset, broadening the initial impetus and the cohort of pioneer actors, and streamlining the channel from "niche innovation" to "collective learning" hold significant promise for expediting the comprehensive revitalization of rural areas.

A key approach to improving the predictive capability of territorial space planning is to effectively analyze the common challenges and governance experiences of pioneering countries. China serves as a notable example, with its increasing emphasis on integrating rational evolution of territories into spatial planning. In this study, we examined the spatiotemporal structure of Japan's territorial space, spatial transformation, and the spatial and temporal evolution of spatial conflicts from 1976 to 2021 on a national scale. We also simulated the future spatial evolution of Japan's territorial space based on the identification of the key driving factors. The results reveal the following: (1) Over the past 45 years, approximately one-quarter of Japan's territorial space has undergone structural transformation. Considerable urban space expansion and continuous ecological environment optimization have been accompanied by a marked decline in agricultural space and food production. This has created substantial food security challenges due to the degradation of agricultural production capacity. Concentration of the population in economically developed plains and topographically flat bay areas has exacerbated conflicts.(2) Japan's territorial space evolution exhibits distinct stages. Although national economic fluctuations and demographic changes do not substantially affect the overall trajectory of territorial space evolution, they can influence the rate and process of evolution. At the late stage of urbanization, the driving forces of spatial evolution are expected to be more concentrated on demographic, economic, and natural background factors. (3) Simulation results across various scenarios suggest no major structural changes in Japan's future territorial space pattern. Agricultural areas will continue to be encroached upon, exacerbating the national food security crisis as the challenges of rural depopulation and aging population deepen. In the next 10 to 15 years, Japan may form a world-class mega-aging urban agglomeration by linking the three major metropolitan areas of Tokyo, Nagoya, and Kansai.

With the rapid development of the digital economy, it is of great significance to explore the impact of digital technology innovation networks on regional economic resilience. Taking 41 cities in the Yangtze River Delta as the example, this study used the data of digital technology innovation cooperation patents and economic and social development from 2010 to 2021, and the social network analysis method and economic resilience measurement index, to describe the temporal and spatial change characteristics of digital technology innovation networks and economic resilience in cities in the Yangtze River Delta, and empirically test the influence of the structural characteristics of digital technology innovation networks on urban economic resilience. The results show that: 1) The cooperation degree of digital technology innovation in the Yangtze River Delta was constantly increasing, and it has gradually evolved into a core-periphery structure and a cohesive subgroup structure. The economic resilience of the cities in the Yangtze River Delta has been steadily increasing through the study period, but the spatial differences were gradually increasing. 2) Degree centrality and closeness centrality of digital technology innovation networks in Yangtze River Delta cities had a significant positive effect on the promotion of urban economic resilience, while betweenness centrality had a negative impact on economic resilience. Robustness test also showed that this conclusion is valid. 3) Compared with the central cities, the digital technology innovation network in peripheral cities had a greater impact on their economic resilience, and the degree of intermediary centrality was more significant, which was quite different from that in core cities. This study is useful for clarifying the relationship between digital technology innovation networks and economic resilience, and exploring the path to enhance regional economic resilience.

[Significance] As a representative of new-quality productivity, the low-altitude economy is gradually emerging as a new engine for economic growth. This economy is based on the development and utilization of low-altitude airspace resources. While bringing development opportunities to geospatial information technology, it also poses entirely new challenges. [Progress and Analysis] In this paper, we introduce the division of low-altitude airspace resources and highlight typical drone application scenarios in the context of the low-altitude economy. Subsequently, we analyze the broad application prospects of geospatial information technology in key areas of the low-altitude economy, including the refined utilization of airspace resources, the construction of low-altitude environments, the planning, construction, and operation of new air traffic infrastructure, as well as the safe and efficient operation and regulatory oversight of drones. We emphasize that the geospatial information industry will benefit from development opportunities such as the integration and innovation of emerging scientific and technological advancements, growing market demand, policy support, industrial guidance, and industrial upgrading and transformation. [Prospect] Finally, we briefly address the challenges geospatial information technology must overcome to meet the development needs of the low-altitude economy. These include advancements in spatio-temporal dimension elevation, map and location-based services, high-frequency and rapid data acquisition systems, all-time and all-domain capabilities, and ubiquitous intelligent technologies. These areas will also serve as future directions for development and breakthroughs in geospatial information technology.

The integration of large-scale Low Earth Orbit satellite constellations (hereinafter referred to as "LEO constellations") and artificial intelligence (AI) technology presents a historic opportunity for a paradigm shift in geography research, heralding a new era for geography to evolve from qualitative geography, quantitative geography, and digital geography into the "LEO constellation-AI-driven Geography". Under this framework, future geographic research can rely on the high spatio-temporal resolution monitoring data provided by LEO constellations to accurately capture the high-frequency dynamic changes of geographic elements at multiple scales, particularly at the global scale. By coupling physical models with AI, it becomes feasible to conduct simulation experiments on the complex interactions between natural and human elements, system states, and interface changes. This will facilitate a deeper understanding of core geographic issues such as variable coupling, multi-process cascading effects, and teleconnection mechanisms. To propel "LEO constellation-AI-driven Geography", there is an urgent need to establish a new-generation data acquisition and sharing platform relying on LEO constellation, seamlessly creating a "dynamic map" of global geographic resources and elements. Additionally, a geographic process simulator that couples physical models and AI needs to be developed to intelligently simulate and predict changes and impacts of geographic elements and landscapes.

[Objectives] To systematically review recent advancements in text-to-image generation technology driven by large-scale AI models and explore its potential applications in urban and rural planning. [Discussion] This study provides a comprehensive review of the development of text-to-image generation technology from the perspectives of training datasets, model architectures, and evaluation methods, highlighting the key factors contributing to its success. While this technology has achieved remarkable progress in general computer science, its application in urban and rural planning remains constrained by several critical challenges. These include the lack of high-quality domain-specific data, limited controllability and reliability of generated content, and the absence of constraints informed by geoscience expertise. To address these challenges, this paper proposes several research strategies, including domain-specific data augmentation techniques, text-to-image generation models enhanced with spatial information through instruction-based extensions, and locally editable models guided by induced layouts. Furthermore, through multiple case studies, the paper demonstrates the value and potential of text-to-image generation technology in facilitating innovative practices in urban and rural planning and design. [Prospect] With continued technological advancements and interdisciplinary integration, text-to-image generation technology holds promise as a significant driver of innovation in urban and rural planning and design. It is expected to support more efficient and intelligent design practices, paving the way for groundbreaking applications in this field.

Runoff observation uncertainty is one of the key unresolved issues in the field of hydrology. Current studies mainly focus on the uncertainty sources and their impacts, but the effects of observation uncertainty on changes of entire flow regime characteristics are still rare. This study collects daily runoff observation series from 1971 to 2020 at five hydrological stations in the water conservation zone of the Yellow River (Huangheyan, Tangnaihai, and Lanzhou stations in the Yellow River Source Region, Xianyang Station in the Weihe River, and Heishiguan Station in the Yiluo River). Changes in 16 metrics from five main flow regime characteristics (magnitude, frequency of events, variability, duration, and timing) are detected by the trend tests, and the effects of observation uncertainty on trends of flow regime metrics are evaluated by adopting a normal distribution error model and some metrics, i.e., the uncertainty width, significance change rate of slopes, coefficient of variation, and degree of deviation. Results showed that: (1) At all the stations, flow regimes showed significant increases in the low flow magnitude, and significant decreases in the high and average flow magnitude, variability and duration. At the Heishiguan Station, the magnitude, variability and duration metrics significantly decreased, while the frequency metrics significantly increased. At the Xianyang Station, the low flow magnitude and timing metrics significantly increased, while the high flow magnitude, frequency and variability metrics significantly decreased metrics. In the Yellow River Source Region, the low flow magnitude and high flow timing metrics significantly increased, while the low flow frequency, high flow magnitude and variability metrics significantly decreased. (2) Observation uncertainty considerably affected the trend changes of 28.75% of total flow regime metrics at all the five stations. Among these, the trends of 11.25% of total metrics changed from significance to insignificance, and those of 17.5% of total metrics changed from insignificance to significance. For the rest metrics, the trends remained the same, i.e., significant trends (18.75%) and insignificant trends (52.50%). (3) Observation uncertainty had the greatest impacts on frequency metrics, especially at the Xianyang Station, followed by the duration, variability and timing metrics. The magnitude metrics were impacted least.

[Objectives] All meaningful forms of human discourse are rhetorical, and the purpose of rhetoric is to enable communication and foster sympathy between parties with certain views. Narrative maps are essentially a discursive practice for communicating information and exchanging ideas, characterized by the strategic use of rhetoric to construct persuasive discourse and achieve the goal of "agreement" or "persuasion". In the current era, where visual dominance is increasingly prominent, rhetoric has garnered growing attention in cartography. This turn not only addresses core issues in narrative map research but also provides a realistic path for enriching and reconstructing the existing knowledge of modern cartography. However, the academic community has yet to establish a systematic framework, leaving three key issues unresolved: (1) How to conceptualize the rhetoric of narrative maps? (2) How to categorize the rhetoric of narrative maps? (3) What is the working mechanism of rhetoric in narrative maps? [Methods] To address these research gaps, this article, firstly, follows the research paradigm of rhetoric to clarify the essence of rhetoric in narrative maps, and defines it as: "During the design process of narrative maps, cartographers use certain visualization strategies to facilitate the representation of events, thereby weaving explicit narrative intentions into the mapping space in an implicit way to create persuasive discourse or emotional agreement for viewers." Secondly, a classification criterion is proposed based on the differences between content semantic representation and logical semantic representation. Two major categories, semantic rhetoric and structural rhetoric, along with 24 minor classes, are divided for rhetoric of narrative map. Semantic rhetoric mainly focuses on enhancing the understanding of content, expressing the connotation and imaginative tension of map "text". Structural rhetoric aims to emphasize the logic semantic relationships in narrative discourse, presenting the narrative logic of events. Semantic rhetoric often manifests as the design of visual symbols to describe events, serving as the "visual punctum" of narrative maps. Structural rhetoric typically involves adjusting the arrangement and structure of different event units, functioning as the "visual stadium" of narrative maps. Next, the mechanism of rhetoric in narrative maps is explored from four aspects: the dimensions of rhetoric, the hierarchy of rhetoric, the integrated use of rhetoric, and the applicability principles of rhetoric. Finally, this study demonstrates the applicability of the proposed theoretical framework through a case study of "Jiangnan Canal", illustrating how the framework can facilitate narrative map design. [Conclusions] This paper lays a theoretical foundation for narrative map research and contributes to the theoretical innovation of contemporary cartography.

[Objectives] The outdoor pedestrian navigation road network is a vital component of maps and a crucial basis for outdoor activity route planning and navigation. It plays a significant role in promoting outdoor travel development and ensuring safety management. However, existing research on road network generation mainly focuses on the construction of urban vehicular navigation networks, with relatively less emphasis on hiking navigation road networks in complex outdoor environments. Moreover, existing methods primarily emphasize the extraction of two-dimensional geometric information of roads, while the reconstruction of real three-dimensional geometric and topological structures remains underdeveloped. [Methods] To address these limitations, this study proposes a method for constructing the three-dimensional outdoor pedestrian navigation road network maps using crowdsourced trajectory data. This approach leverages a road network generation layer and an elevation extraction layer to extract the two-dimensional structure and three-dimensional elevation information of the road network. In the road network generation layer, a trajectory density stratification strategy is adopted to construct the two-dimensional vector road network. In the elevation extraction layer, elevation estimation and optimization are performed to generate an elevation grid raster map, which is then matched with the two-dimensional road network to produce the three-dimensional hiking navigation road network. [Results] To demonstrate the effectiveness of the proposed approach, experiments were conducted using 1 170 outdoor trajectories collected in 2021 from Yuelu Mountain Scenic Area in Changsha through an online outdoor website. The constructed outdoor three-dimensional hiking road network map achieved an average positional offset of 4.201 meters in two-dimensional space and an average elevation estimation error of 7.656 meters. The results demonstrate that the proposed method effectively handles outdoor trajectory data with high noise and varied trajectory density distribution differences, generating high-quality three-dimensional hiking road network maps. [Conclusions] Compared to traditional outdoor two-dimensional road networks, the three-dimensional navigation road networks constructed this study provide more comprehensive and accurate map information, facilitating improved pedestrian path planning and navigation services in complex outdoor environments.

Skilled migration is a pivotal phenomenon underpinning globalization that has attracted widespread scholarly interest; a nuanced understanding of the patterns and mechanisms of skilled migration is considered essential for fostering coordinated regional development and enhancing labor market allocation. To compare the domestic and international talent mobility research in the 21^st century and advance China's talent mobility theory, In this paper, we reviewed Chinese and English literature from fields such as geography, urban planning, demography, economics, and management since 2000 via quantitative and qualitative analysis. Initially, we conducted bibliometric and keyword co-occurrence analyses using CiteSpace to identify research hotspots and trends; subsequently, we performed Qualitative Data Analysis Miner qualitative analysis as a supplementary approach to derive in-depth insights and determine connections between literature sources. Herein, we summarize the research hotspots regarding skilled migration, domestically and internationally. We found that concerning research hotpots, domestic research emphasizes the spatial distribution of different types of talent, the impact of urban factors on skilled migration, and the interplay between talent and urban innovation. In contrast, international research emphasizes more on the mobility decisions of highly skilled migrants within a globalization context, focusing on the impact of international high-skilled migration on the destination and origin countries, the micro-level mechanisms of migration decision-making (such as family dynamics, gender roles, and early career stages), and social adaptation in destination countries (including identity, sense of belonging, and related factors). Theoretically, both domestic and international studies are based on labor migration theory, examining skilled migration mechanisms from macro-regional and micro-individual perspectives, and expanding theoretical frameworks to include amenities and the creative class. However, owing to differences in social, economic, institutional, and developmental contexts among countries, these theories are not entirely applicable in practice, particularly regarding their explanatory power in the Chinese context, which requires further examination. Furthermore, in terms of research progress, we found that international studies are increasingly highlighting the life course of migrants and the socio-cultural micro-mechanisms influencing skilled migration, emphasizing the adoption of a combination of quantitative and qualitative analytical methods. Conversely, domestic research predominantly focuses on the spatial patterns of skilled migration and the effects of macro-urban factors, relying on quantitative analyses. Future research in China should aim to examine micro-mechanisms, develop indigenous theoretical frameworks to foster theoretical innovation, and enhance the integration of qualitative and quantitative methods. Moreover, exploiting the potential of big data and emerging technologies could contribute towards overcoming limitations associated with data acquisition. On the basis of our survey of current theories and methods, we propose the following four directions for future research: (1) strengthening investigations into the micro-mechanisms of skilled migration; (2) developing indigenous theoretical frameworks to support theoretical innovation in China; (3) promoting the integration of qualitative and quantitative research methods; and (4) enhancing data acquisition and exploiting big data and advanced technologies to overcome the current limitations associated with acquiring data.

The number of highly educated individuals continues to grow, and the internal heterogeneity of this group is becoming increasingly evident. Examining these differences in location selection mechanisms from the perspective of heterogeneity is crucial for optimizing talent distribution. In this study, we used population census data from 2010 and 2020, along with 1% population sampling survey data from 2015 across various provinces. We employed the Gini coefficient and visualization methods to depict the spatiotemporal patterns of talent distribution at college, undergraduate, and graduate education levels in Chinese prefecture-level administrative regions. Employing a Beta regression model, we identified the factors that influence talent distribution across four dimensions: spatial sorting, spatial selection, spatial agglomeration, and comfort preferences. The key findings were as follows: 1) From 2010 to 2020, regional disparities in educational talent were ranked as postgraduate > undergraduate > college, with a decreasing trend in disparities for all three categories. 2) The proportion of college-, undergraduate-, and graduate-level educated individuals exhibited a clear administrative hierarchy, with the proportion of highly educated individuals decreasing from capital cities to provincial capitals (vice-provincial cities), prefecture-level cities, and regions. Hierarchical differentiation was most pronounced for graduate-level individuals, and was least pronounced for college-level individuals. 3) The Hu Huanyong Line serves as a dividing line for spatial structural differences in the distribution of highly educated individuals. To the southeast of the line, the spatial structure follows a pattern from the center (provincial capitals) to the periphery (general prefecture-level regions), with graduate-level individuals demonstrating the most characteristic spatial structure. Northwest of the line, a high-talent area for college and undergraduates extends from the Daxinganling Forest region in the east to Hami in the west. 4) Urban agglomerations and metropolitan areas are gradually becoming important spatial carriers of highly educated individuals, with the most typical examples being national-level urban agglomerations, especially the Yangtze and Pearl River Deltas. 5) From 2010 to 2020, dynamic changes in the concentration of talented individuals at the associate degree, undergraduate, and graduate levels exhibited a reverse core-periphery spatial structure. Specifically, the location quotient for talented individuals in capital and provincial-level cities (including sub-provincial cities) decreased, whereas it increased in prefecture-level cities and regions. Additionally, the dynamic changes in the concentration of talented people demonstrated regional differentiation; the location quotient for talented people in areas northwest of the Hu Huanyong Line showed an upward trend, whereas it decreased southeast of the line. Similarly, the location quotient for talented people in the eastern region declined, whereas it increased in the central and western regions. 6) In terms of spatial sorting, talented people at different educational levels tended to prefer prefecture-level administrative regions with higher incomes, higher administrative ranks, and larger urban populations, with the order of preference being graduate > undergraduate > college. Regarding spatial selection, higher housing costs and more competitive job markets in prefecture-level administrative regions generally demand higher educational qualifications, following the trend: graduate > undergraduate > college. In terms of spatial agglomeration, urbanization levels in prefecture-level regions foster clustering of talented people at all educational levels, with the effect being strongest for college-educated people, followed by undergraduate and graduate people. With regard to comfort preferences, regions with higher levels of social environmental comfort are more attractive for the aggregation of highly educated individuals. Our research findings will be helpful for different cities and regions in formulating differentiated talent recruitment policies.

In recent years, the number of Chinese university graduates has been progressively increasing, and their employment situation has become increasingly poor under the influences of the COVID-19 epidemic and downward economic pressure. The employment issue of university graduates has attracted considerable attention. The migration of university graduates is synthetically affected by multiple factors including individual-, family-, and city-level factors. A systematic theoretical framework of the influencing mechanism of the migration of university graduates, which combines these factors, is lacking. Moreover, extant studies have scarcely investigated the migration of university graduates from the overall perspective of family capital, let alone different factors considered by graduates with different family capital levels in the migration decision-making process. The role of human capital in the relationship between the family capital and migration of graduates still remains unknown. To address this gap, based on first-hand survey data on the migration of new graduates from 78 universities in eight cities in 2022, this study employs a nested logit model to examine the influencing factors on the intercity migration of university graduates from both the individual and city levels, and reveals the dual influencing mechanism of family capital (economic, cultural, and social capital) and human capital (education qualification, university type, student cadre status, academic records, certificates, and internship experience). The results demonstrate that: 1) Family capital exerts a significantly positive impact on the intercity migration of university graduates. Graduates with higher levels of family capital are more inclined to move to higher-level cities. Compared with graduates whose parents have an annual income level below 90 thousand RMB and highest education qualification below a college degree, graduates whose parents have an annual income level above 90 thousand RMB and highest education qualification above a college degree are more likely to flow to first-tier and second-tier cities. 2) The influence of family capital on the migration of graduates presents significant heterogeneity. When choosing employment cities, graduates with a higher level of family capital pay more attention to urban economic and amenity factors. Compared with graduates with lower levels of family capital (represented by lower parental income levels, lower educational qualification levels, and parents' non-managerial or professional occupations), graduates with higher levels of family capital (opposite to their counterparts) are more affected by income levels, living costs, environmental quality, medical resources, and cultural resources, in selecting employment cities. 3) The human capital of graduates plays both a positive mediating role and a certain degree of a negative moderating role in the impact of family capital on the migration of graduates. All the variables of human capital play a positive mediating role, that is, family capital positively influences the migration of graduates by affecting their human capital; however, some variables of human capital (student cadre status, academic records, certificates, and internship experience) play a negative moderating role, that is, the human capital accumulated in the university can weaken the impacts of family capital on the migration of graduates. By introducing a spatial perspective, this study provides not only empirical evidence for the response to the social concern about whether getting good jobs depends on family background or personal efforts, but also scientific references for promoting the full employment of graduates and guiding the rational talent flows.

Understanding the factors influencing the return of high-level scientific and technological talent from outside China's customs borders is important for optimizing the policy practice of introducing high-level talent from abroad. Based on the biographical information of 1,248 high-level scientific and technological talents who had studied or worked outside China's customs borders and then returned to China to obtain the National Outstanding Young Scientist Fund from 2009 to 2020, this study analyzes the characteristics of the spatial pattern of the return of high-level scientific and technological talents from outside China's customs borders and their influencing factors using social network analysis and a nested logit model, respectively. The results reveal the following: The outflow city network for talents from outside China's customs borders centers around Hong Kong (China) and Cambridge (USA), while the inflow city network is centered on Beijing and Shanghai. There are notable regional differences in the distribution of cities where these talents return.Cambridge (USA) is the primary source of returning talents to Beijing and Shanghai, while Singapore is the main source of returning talents to Nanjing. For Guangzhou and Wuhan, Hong Kong (China) serves as the main source of returning talents.At the individual level, academic ties and the level of talent introduction programs significantly influence the choice of cities for returning talents. At the macro level, high salaries, significant investment in science and technology, and a high concentration of top-tier scientific research platforms in Chinese cities are the primary factors attracting high-level talents from outside China's customs borders. Additionally, the quality of educational service facilities and favorable climate conditions also play a significant role in influencing city choices.Individual heterogeneity exists in the influence of urban macro-factors on location choices for talent return. Male talents, those with mobility experience, or those who have resided outside China's customs borders for an extended period tend to place greater emphasis on academic and social ties as well as support from high-level talent introduction programs. Conversely, talents returning later are more influenced by higher salary levels and the availability of top-tier scientific research platforms in the city.Compared with existing studies that primarily focus on analyzing the influence mechanisms of talent return driven mainly by policy factors, this study contributes to revealing the joint impact of government policy factors and market-oriented factors on the return of high-level scientific and technological talents.

In the knowledge economy era, technological innovation has become increasingly crucial in forming international competitive advantages and driving national economic development. However, the global distribution of technological innovation remains uneven, with a sustained "core-periphery" structure. From the perspective of evolutionary economic geography, technological development paths are closely linked to the local knowledge base, making it generally difficult to overcome spatial constraints. Consequently, the path-dependent nature of national technological development may reinforce the disadvantageous position of late-developed countries in global technological progress, further widening the technological development gap. In this context, exploring how latecomer countries can achieve innovation breakthroughs spatially becomes essential. From the viewpoint of talent mobility, we employ a global patent database and data on the stock of highly skilled mobile talent to construct a country-time-level econometric model to analyze the impact of birthplace diversity among highly skilled talent on the ability of destination countries to achieve place-breaking innovations. Additionally, we conduct group regression based on multidimensional proximity (geographic, cultural, and institutional) to analyze the varying roles of different talent groups. Our findings reveal that greater diversity in the birthplaces of mobile talent significantly increases the likelihood of destination countries accessing new technological fields unrelated to their existing knowledge base. This suggests that the diversity of talent's country of origin positively influences place-breaking innovations in the destination country. Moreover, we find that multidimensional proximity affects the mechanism by which talent diversity drives place-breaking innovations. Specifically, talent diversity has a stronger impact on breakthroughs between geographically and culturally distant countries, while institutional distance appears less significant. This is likely because mobile talent from geographically distant countries brings more differentiated knowledge and skills, helping destination countries overcome geographical constraints on technological development. In contrast, between culturally closer countries, mobile talent faces fewer communication and integration barriers, which enhances the positive effects of their birthplace diversity. The results suggest that, when introducing highly skilled migrants, countries should focus not only on the scale and quality of talent but also the diversity of talent origins. Actively recruiting highly skilled individuals with diverse skills and differentiated knowledge can foster technological development, help overcome geographical constraints, and achieve technological catch-up. Additionally, countries should cultivate supportive linguistic, cultural, and social environments to ease the cross-cultural adaptation challenges faced by highly skilled immigrants. Simultaneously, countries should promote interaction among diverse talent groups, facilitate communication with local talent, and build affiliation networks to better leverage the benefits of talent diversity. These insights provide important guidance for latecomer countries in designing immigration and innovation policies and offer a new direction for future research. Future studies should explore non-proprietary innovation behaviors, delve into the integration and exchange among different talent groups at the micro level, and examine the underlying mechanisms using both quantitative and qualitative methods.

For a long time, regional economic resilience research has been rooted in the European evolutionary economic geography paradigm, which is suitable for explaining the endogenous adaptation process, capabilities and mechanisms of regional economy in the context of shocks. However, the evolutionary paradigm lacks a multi-scale correlation perspective and is difficult to explain the exogenous problems of regional economic resilience. Currently, the global geopolitical economy is facing reconstruction, and the global supply chain, industrial chain and value chain are being reorganized. Regions embedded in the Global Production Network cannot remain unaffected, and the explanatory shortcomings of evolutionary resilience have become prominent. This paper combines the literature on supply chain resilience, industrial chain resilience and value chain resilience, proposes a "chain resilience" perspective, distinguishes the differences between it and the evolutionary resilience perspective in terms of problem focus, research scale, influencing factors and method selection, refines the perspective advantages of "chain resilience", and constructs a new framework for regional economic resilience research under the "chain perspective". This framework emphasizes: (1) It is necessary to analyze the presupposed role of shock attributes on regional economic resilience; (2) For specific shock situations, the ability, object, goal and approach of regional economic adaptation can be analyzed from two dimensions: structural and agency factors, and regional and external factors; (3) Taking the place and the various economic chains and networks it is embedded in as the core object and logical starting point for analyzing regional resilience, focusing on understanding the positionality, opportunism and agency of the local economy in the chain/network before and after the shock.