In the context of great power regional projection, countries surrounding the South China Sea have adopted uncertain hedging strategies based on their geographical environment and geopolitical relationships. These strategies manifest as fluctuations in conflict and cooperation with major powers, subsequently influencing regional geo-structures. This study constructs an analytical framework for regional geo-setting under national hedging behavior, aiming to quantitatively assess the stability of the South China Sea geo-setting and explore the hedging strategies of various countries and their influencing factors within the context of U.S.-China strategic competition. The findings are as follows: ① Based on the imbalance degree of the geo-setting calculated from the network structure imbalance, the study period can be divided into three phases: overall stability (2000-2011), deterioration of the situation (2012-2018), and volatility of the situation (2018-2023). Two key drivers shape the evolution of geo-setting stability: intensifying great power competition and growing hedging strategies adopted by smaller countries. ② Since 2000, both China and the United States have seen an upward trend in their geo-position in the South China Sea, with both countries continuously increasing their power investments in the region. ③ Through a corroborative analysis of the structural imbalance evolution curve and interactions among key geopolitical actors, this study demonstrates that the assessment results align with the security situation in the South China Sea. This alignment validates the applicability of the analytical framework and quantitative method for assessing geo-setting in regions characterized by geopolitical-strategic intersection. This study provides a novel quantitative approach for assessing and analyzing geo-structures in the South China Sea and other geopolitically intersecting regions, thereby contributing to an objective depiction of geo-setting evolution, a better understanding of security situations, and decision support for sustainable peace, security, and difference management among regional countries.

The China-India border conflict has exerted profound impacts on bilateral relations, regional security dynamics, and the broader global political landscape. Analyzing its evolutionary game and underlying mechanisms is therefore of great significance. Such analysis helps clarify China's neighboring geo-setting, safeguard its national security, and reveal how complex geographic contexts shape China-India strategic choices and interaction patterns. Based on the theory of country-specific geo-setting and game theory, this study constructs an analytical framework to examine the evolution of China-India border conflicts from the perspective of country-specific geo-setting. By examining typical conflict cases, it explores the evolutionary game process and seeks to reveal the underlying game mechanism. The results show that: (1) the evolutionary process of the game shows a trend of “zero-sum-positive-sum-zero-sum”, which coincides with the changes in the global geo-setting. ① In 1962, China and India formed a T-shaped geostructure with external geopolitical bodies. India adopted a tough “forward policy” by virtue of its geopolitical advantage, and China responded with military counterattacks, plunging China and India into a zero-sum game; ② In 1987, China and India formed a “bipolar linkage” structure with external geopolitical bodies, with India taking a tough stance, and China adopting a strategy of restraint and toughness, forcing India to back down. India's posture is tough, China adopts a restrained and tough strategy, forcing India to back down from the conflict and presenting a positive-sum game; ③ In 2020, China and the United States strengthened the game, India tends to cooperate with the United States, “leaning on the United States to fight against China”, and the interaction of multiple geopolitical bodies forms a “radial-enveloping” structure. India from the exploratory action to radical attack, China to take restraint and counterattack strategy, resulting in the conflict intensity increases and evolved into a zero-sum game. (2) The mechanism is roughly summarized as follows: the incomplete information resonance of cross-domain interaction, the dynamic synergy of cross-scale coupling and multi-actor game, and the feedback loop of geo-setting and game, which together create and nourish India's spatial dislocation of the scale of the China-India border conflict. India's miscalculation of China has increased, and India regards geo-setting factors as a tool to clamp down on China, and multilateralizes the China-India border issue by means of “upward scale shift-downward smoothness” reorganization, and keeps testing China's bottom line in strategic adjustments, thus forming a feedback loop of the game of geo-setting and conflict. Finally, we discuss how to understand the game of China-India border conflicts from the perspective of country-specific geo-setting and put forward countermeasures and suggestions for conflict control and peaceful resolution of the border game.

China and Vietnam are geographically connected by mountains and rivers and culturally linked by shared traditions. Their close geographical proximity has fostered robust exchanges across political, economic, and cultural dimensions, while also being accompanied by complex emotional dynamics and geopolitical considerations. This study employs methods such as discourse analysis, eye-tracking experiments, and semi-structured interviews to construct a corpus of event reports on China-Vietnam relations from January 1, 2020, to April 30, 2024, sourced from four official media outlets of the two countries. The research explores how the audience's emotional geopolitical cognition is influenced by national discourse. Taking Vietnamese international students in China as the research subject and Chinese students as the control group, it analyzes the narrative logic of China-Vietnam geopolitical relations from the perspective of emotional geopolitics. The findings are as follows: ① At the national level, a macro-narrative of China-Vietnam geopolitical relations has been constructed with mainstream media as the medium, and the emotional expressions at the national level vary between the two countries. China tends to use language that reflects intimacy and cooperation, while Vietnam shows a more cautious attitude. However, the two sides share consensus on promoting the building of a China-Vietnam community and other key areas, which is evidenced by the continuous strengthening of China-Vietnam relations within the national discourse system. This macro-narrative, guided by the national emotional logic, is constantly transmitted to individuals, shaping the sense of identity among the audiences of both countries regarding the friendly and good-neighborly relations between China and Vietnam. ② Individuals are not passive recipients of the macro-narrative. In this process, influenced by their prior historical backgrounds and embodied practical experiences, individuals negotiate with the elite-led narrative and provide bottom-up feedback on online media platforms. ③ Through an analysis of the emotional perceptions of micro-level individuals, the study finds that groups with different social and cultural backgrounds develop differentiated emotional experiences. Narratives about state relations should pay greater attention to the audience's emotional feedback, further improve the transmission and feedback mechanism, and strengthen the development of public opinion domestically and internationally. Finally, based on the process of individual emotional occurrence and the knowledge production process of mainstream media, the study discusses the generation mechanism and characteristics of the narrative on China-Vietnam geopolitical relations from the perspective of emotional geopolitics. The conclusion section summarizes the research content and puts forward suggestions for improving exchanges between the two countries, aiming to promote the further harmonious development of China-Vietnam relations.

Unicorn enterprises, which are startups that show high valuations and rapid growth in the capital market, have emerged as significant elements within the realm of large-scale innovative technology. Therefore, they have become an increasing focus on theoretical research over recent years. Based on the analysis about characteristics of unicorn enterprises, this article systematically reviews the research progress of geography on these entities, focusing on the spatial pattern and mechanism of unicorn enterprises, as well as the process and mechanism of human environment interaction in unicorn enterprises. The literature review reveals that research on unicorn enterprises is gradually becoming a hot topic embedded in various branches of geographical science. However, there is also an over-reliance on structural factor analysis and single-dimensional regional effects studies, which may limit the comprehensive understanding of these enterprises. While highlighting the knowledge gaps in the study of this emerging economic element, the article, in conjunction with the cutting-edge theoretical research in geography, anticipates pivotal research issues in the study of unicorn enterprises from the perspectives of digitalization and platformization, global production networks and value chains, and assetization and financialization. A deep exploration of the relationship between unicorn enterprises and regional development, along with the complex human-geographic interaction mechanisms underlying it, holds significant importance. Such an explo-ration is crucial for achieving theoretical innovation in human geography in the new era and for devising more rational strategies of innovation-driven development.

The wide adoption of advanced manufacturing technologies (AMTs) in manufacturing industry has led to regional high-quality development, but the role of economic geography in the evolution of regional industrial paths under the application of AMT has received limited attention. Taking industrial robots as an example, this paper constructs a dataset of industrial robot applications in 130 3-digit industries based on the China Customs Database to explore the impact of AMTs on the evolution of industrial paths in Chinese cities. Our findings reveal that: (1) In China, the number of industries and cities adopting industrial robots has been increasing annually, yet there has been a marked slowdown in the rate of inter-industry diffusion. Spatially, a clustering trend is emerging in regions such as the Guangdong-Hong Kong-Macao Greater Bay Area, the Yangtze River Delta urban agglomeration, the Beijing-Tianjin-Hebei region, and parts of northeastern China. (2) The application of industrial robots supports the entry of new competitive industries, as industries with extensive robot adoption are more likely to achieve specialized development. (3) The adoption of industrial robots reinforces related diversification in regional industrial path evolution. Specifically, the positive effects of robot application on regional industrial expansion are more pronounced in industries closely connected to the local knowledge base. These findings offer important theoretical implications for understanding the role of technological shocks in regional industrial path evolution and provide policy recommendations for regional industrial transformation and upgrading in China within the context of intelligent manufacturing.

Energy and environmental conservation industries (EECIs) are crucial parts of the green industrial system. They also serve as catalysts for the greening of current industrial systems. The geographical agglomeration of EECIs can promote green innovation. However, it is not well known that how the agglomeration of EECIs contributes to green innovation. Does it depend on the technology push from the relatedness between EECIs or the market pull from the relatedness between EECIs and emission-intensive industries? This question stems from the nature of EECIs, and its answer determines the spatial planning of EECIs. This study applies the theory of agglomeration externalities and related variety to investigate this question. It collects the data of green patents and firms in EECIs from 41 prefecture-level cities in the Yangtze River Delta region from 2003 to 2019. On this basis, this study establishes the “industrial space” of these cities and measures the level of specialization, related variety, and supply-demand relationships. This study then examines the impact of different agglomeration patterns on green innovation. The empirical results show that: ① The development of EECIs in the Yangtze River Delta region has experienced a turning point since 2015. The spatial distribution of EECIs has shifted from a monocentric pattern to a polycentric pattern. A development corridor consisting of Shanghai, Suzhou, Wuxi, Changzhou, Hangzhou, Jiaxing, Huzhou, Nanjing, and Hefei is gradually emerging. ② the agglomeration level of related industries continues to increase. The relatedness between EECIs and emission-intensive sectors grows and dominates first, followed by the growth of the specialization and related variety of EECIs. ③ the agglomeration of industries related to EECIs can promote green innovation. It is driven by technology push rather than market pull. That is, the agglomeration of related and diverse EECIs can lead to the bricolage of different knowledge and contribute to green innovation. At the same time, the specialization of EECIs can lead to the risk of development lock-in, which should be avoided. ④ the effect of agglomeration on green innovation is spatially heterogeneous and stage-dependent. In the early stages of industrial development, related diversification is more conducive to enhancing innovation complexity. However, as EECIs mature, the role of specialization and the supply-demand linkage become more significant. In peripheral regions, promoting supply-demand linkages and related diversifi-cation can enable latecomer catch-up. The findings support the development path of establi-shing industrial clusters and parks of EECIs. They also offer insights into the orientation of developing EECIs.

The formation of industrial clusters is a pivotal topic in evolutionary economic geography (EEG). Drawing upon Generalized Darwinism, EEG conceptualizes cluster formation as a process involving the replication of firm routines, the increase in firm numbers, and spatial agglomeration. However, this theory neglects the specific spatial and temporal contexts in which clusters emerge. This paper argues that cluster formation is not spontaneous but rather contingent upon particular spatial and temporal conditions. Building on Generalized Darwinism, we emphasize the spatio-temporal context of firm spin-offs and propose an analytical framework integrating firm spin-offs, local capabilities, and market demand to explain cluster formation. Utilizing the automotive parts industry cluster in Yuhuan, Zhejiang Province as a case study, this paper conducts an empirical analysis. Our findings indicate that continuous firm spin-offs depend on both supportive local capabilities and external market demand during cluster formation. The former provides a knowledge channel and resource support necessary for replicating firm routines, while the latter acts as a driving force for the increase in firm numbers. We conclude that cluster formation is a collaborative process jointly shaped by enterprises, localities, and market, rather than merely the spatial outcomes of firm spin-offs. This research contributes to refining the EEG perspective on cluster formation and offers valuable insights for local strategies in nurturing emerging industrial clusters.

Border regions are becoming open gateways and cross-border channels for bilateral exchanges and cooperation between China and Russia. This paper takes Hunchun City, Jilin Province, on the China-Russia-DPRK border as an example, and combines field research and in-depth interview research methods to explore the making process and mechanism of the cross-border medical tourism landscape in the study area. Based on the perspective of border social construction, it examines the production and reconstruction of medical tourism borderscapes from the interactive relationship between tourism and bordering. The study finds that the development of cross-border medical tourism is influenced not only by interstate political collaboration and bilateral agreements but also by the bordering practices of local actors and the embedded official narratives between nations. By constructing an analytical framework of “structure-action-borderscapes”, this paper argues that the permeable borders shaped by the geopolitical and economic structures of China and Russia are the driving conditions for the development of cross-border medical tourism, and that the process of bordering is linked to the cross-border spatial practices of place actors. Cross-border tourism is both a representation and a driving factor of the bordering process. Place actors promote the making of medical tourism borderscapes through the commodification of the border and as agent in cross-border interactions and cooperation. This leads to the social construction of specific border spaces by tourism, performing the making of medical tourism landscapes through the physical environment and simulacrascape, as well as the emotional meaning and sense of place. On one hand, the study expands the dynamic understanding of tourism and borders by analyzing the production process of medical tourism landscapes under multi-scalar integration. It examines how the bordering process in cross-border medical tourism is jointly shaped by multiple actors. On the other hand, it provides a case reference for bilateral tourism development and cooperation between China and Russia, as well as border governance, deepening the multi-scale interactive understanding of Sino-Russian geopolitical relations.

In the process of Chinese-style modernization, significant transformations have occurred in the natural, social, and cultural landscapes of rural areas. Internet-famous rural tourist destinations now serve dual functions as daily living spaces for local residents while simultaneously becoming objects of visual consumption for external visitors. Digital media plays a pivotal role in constructing the landscape and shaping destination image formation of these viral rural tourism sites. This study selects Taipan Village in Qiandongnan Prefecture, Guizhou Province as a case area, developing a theoretical model and framework for landscape production in internet-famous rural tourist destinations through the research logic of “landscape composition - landscape dynamics - landscape production” under the guidance of spatial production theory. The findings reveal that: (1) The spatial structure of viral rural tourist destinations on digital media platforms is characterized by a dual interactive coupling of real and virtual space networks. During the transformation from “ordinary village” to “internet-famous village”, cultural tourism practices achieve material landscape construction and social scenario interaction in real space, while virtual space manifests unique media landscapes through multi-platform content creation and network community perception reconstruction. (2) Following the triple dialectical framework of spatial production theory, rural tourism landscape production operates through a mechanism where “capital drives spatial practice, power dominates spatial representation, and local communities co-create representational spaces”. Particularly, the communication storm formed by Douyin platform's technological empowerment, catalytic dissemination of key events, and local cultural innovation drives continuous flows of spatial elements across real-virtual dimensions, ultimately realizing sustainable value production in internet-famous rural landscapes. This research interprets innovative spatial production patterns of digital media-embedded viral rural tourist destinations through Lefebvrian spatial production theory, providing significant referential value for Chinese-style modernization and cultural tourism practices in ethnic regions in the new era.

This paper constructs a detailed classification scheme for population urbanization types and a corresponding indicator system for urbanization rate at the county level by using the 2010 and 2020 censuses data. It categorizes local urbanization, in-situ urbanization, nearby urbanization and inter-provincial urbanization into four regional patterns: HH (High-High), HL (High-Low), LH (Low-High), and LL (Low-Low). By employing descriptive statistics, multinomial Logit model, and multiple linear regression model, this paper reveals the spatio-temporal characteristics and influencing factors of these regional patterns. The main findings are as follows: (1) From an administrative perspective, municipal districts and ordinary counties dominate across different regional patterns, underscoring their pivotal role in the urbanization process. (2) In terms of spatial distribution, the HH and HL types exhibit significant spatial agglomeration and form a distinctive pattern; apart from in-situ urbanization, the LH and LL types of the other three urbanization types, while widely distributed, all show specific regional directionality. (3) The analysis of driving mechanisms indicates that gentle terrain and non-agricultural industrial development are the core driving forces behind the formation of regional patterns of population urbanization types. Multiple variables, including government intervention, the urban-rural income gap, transportation accessibility, regional policies, and public services, also have a significant impact on the evolution and differentiation of these regional patterns.

Prefecture-level cities serve as the fundamental geographical units for labor migration decision-making and employment location choices. However, existing studies on migration patterns and mechanisms predominately focus on interprovincial scales, neglecting intercity migration. From the perspective of labor skill heterogeneity and based on data from the Seventh National Population Census (2020), this study constructs intercity migration networks for highly-and general-skilled labor. Using complex network analysis methods and a Poisson Pseudo-Maximum Likelihood gravity model, we examine the structural characteristics and driving factors of China's intercity labor migration networks from 2015 to 2020. The findings are as follows: ① Two types of labor exhibit differences in migration scale, both primarily migrate, on one hand, to economically developed regions along to the eastern coast, and on the other, to gateway cities in the central and western regions, with inland small and medium-sized cities being the main places of origin. In large cities (type Ⅰ& Ⅱ), the migration scales of the two types of labor diverge significantly, but in other city scales, they show similarities, both exhibiting a tendency to migrate toward coastal city clusters and away from inland ones. ② The migration network structure of highly-skilled labor is more heterogeneous, with community structures charact-erized by predominantly zonal flow, breaking through the “Bole-Taipei Line” from north to south; the migration network of general-skilled labor is more fragmented, with migration unfolding along the Yangtze River Economic Belt and characterized by predominantly meridional flow. Both types of labor are shaped by provincial administrative boundaries in secondary community structures. ③ Hierarchical differentiation, employment opportunities, regional guidance, quality of place, and transportation network structure play critical roles in shaping the migration patterns of both labor groups.

Based on CMDS, this study employs spatial analysis techniques such as trend surface analysis and spatial autocorrelation to explore the spatiotemporal evolution characteristics of the willingness for agricultural migrant populations to achieve urban citizenship at the prefecture-level city scale. Additionally, the spatiotemporal heterogeneity of the driving factors influencing this willingness is analyzed using a spatiotemporal geographically weighted regression model. The findings reveal the following: ① During the study period, the willingness of agricultural migrant populations to achieve urban citizenship exhibited a “U” shaped distribution along the east-west axis, while a “north-high and south-low” pattern was observed along the vertical axis. ② Statistically significant positive spatial autocorrelation was identified in the willingness for urban citizenship. Local spatial autocorrelation analysis showed that “low-low” agglomeration areas transitioned from scattered distributions to contiguous clusters in eastern coastal cities, while “high-high” agglomeration areas shifted from concentrated clusters in the Shandong Peninsula to a more dispersed distribution nationwide. Both “low-high” and “high-low” agglomeration areas demonstrated a decreasing trend over time. ③ Over the study period, the positive driving factors ranked by their average influence strength were: educational resources > social security > employment flexibility > ethnic identity > commercial housing prices > migration duration > per capita GDP. The negative driving factors ranked by their average influence strength were: marital status > migration range > wage levels > employee identity > average age > population density. ④ Both demographic and urban characteristics jointly influenced the willingness for urban citizenship among agricultural migrant populations, with the driving factors exhibiting dynamic changes over time and space. Specifically, the central region transitioned from a “security-economic oriented” to a “security-inclusiveness oriented” model; the western region shifted from an “employment-economic oriented” to a “security-economic oriented” model; whereas the eastern and northeastern regions maintained “resource-opportunity oriented” and “multi-factor driven” models, respectively.

Migrants between urban and rural areas has always been an important topic in population geography and urbanization research, but there are relatively few studies focusing on population migration from urban to rural areas. Based on the data of the 7th National Population Census in 2020, this study explores the spatial patterns of the urban-to-rural migrants and their influencing factors through spatial autocorrelation analysis and spatial econometric models. The main findings are as follows: (1) The core areas of the Yangtze River Delta and the Pearl River Delta, the provincial capitals of the central and western regions, central and western Inner Mongolia and its surrounding areas, as well as Northeast China are the most attractive destinations for the urban-to-rural migrants. Among them, the provincial capitals in the central and western regions and Northeast China are mainly attractive to intra-provincial urban population, the core area of the Yangtze River Delta mainly attracts inter-provincial urban population, the core area of the Pearl River Delta as well as the central and western parts of Inner Mongolia have a stronger attraction to both intra-provincial and inter-provincial urban population. (2) The spatial distribution of urban-to-rural migrants is shaped by both economic and amenity factors, with economic factors generally playing a more dominant role. The urban-to-rural migrants tend to cluster in rural areas with higher levels of income, more non-farm employment opportunities, better development of the tourism industry, better air quality, more convenient transportation, and closer proximity to provincial capitals. For these migrants, economic factors are the primary driver of intra-provincial movement, whereas inter-provincial migrants are additionally and significantly shaped by amenity factors.

Material has a profound effect on the local practice of migrants, and the interweaving, penetration and interaction of migrants, material and place in regional space show strong and complex tension. “Jing Piao” (Jingdezhen migrants) has become a typical group of immigrants due to its unique ceramic cultural and economic attributes. This paper responds to the trend of material turn in the human-land relationship, scientifically combines the perspective of material turn with the theory of migrant place integration, constructs the theoretical framework of migrant place integration from the perspective of material turn through the multi-subject interaction of “migrant-material-place”, and explores and deconstructs the dimension and core mechanism of “Jing Piao” in Jingdezhen. The results show that the local integration of “Jing Piao” operates on two levels: the construction of a shared “field” (Ci Chang) and the cultivation of individual “aura” (Ci Qi). The spatial layering based on material functions and the emotional iteration based on material relationships are the core mechanisms for the “Jing Piao” place integration. The relationship between Jing Piao and Jingdezhen is a diversified interactive pattern with ceramics as the core, which has a profound and far-reaching effect in promoting and building each other, which verifies the applicability of the analysis framework of this study at the micro level. This study provides a beneficial supplement for understanding and exploring the multiple interaction mechanism between people and land, and has broad practical reference value in the study of place integration and man-land relationship.

Long-term parent-child separation and left-behind children in migrant families profoundly affect family reproduction and urbanization quality. Focusing on the parent-child companionship status of migrants, this study examines migrant families from Shouxian County, Anhui Province as the research subject. Based on family panel data from 1995-2020, it systematically investigates the evolutionary characteristics and influencing mechanisms of migrant family mobility patterns during children's 0-15 age period. The findings reveal that: (1) Migrant families exhibit ten distinct organizational patterns. Although nearly one-third of families experienced “complete family migration”, the dominant patterns remain the separation-based “both-parent migration” and “father-only migration”, with significant differences across population characteristics and spatial distributions. (2) In terms of temporal evolution, family migration patterns have undergone three stages—child-left-behind, polarized development, and reverse companionship—indicating a shift from economically motivated to family-oriented migration strategies. (3) At the micro level, the transition of migration patterns has become more dynamic. Early stages show dual tendencies of intensified parent-child separation and increased family reunification, while recent stages are characterized by parental return as the main approach to enhancing companionship. Importantly, the mitigation of parent-child separation primarily depends on parents returning home, rather than children migrating to cities. (4) Family migration patterns are shaped by a combination of child characteristics, parental and household attributes, migration experiences, and destination features. Families are more likely to undertake complete migration when associated with factors such as intergenerational change, raising sons, engaging in professional or managerial work, homeownership, accumulated migration experience, and migration to top-tier cities (e.g., Beijing, Shanghai, Guangzhou, and Shenzhen). In contrast, children's educational transitions, heavy caregiving burdens, longer migration distances, high living costs, and intra-provincial migration constrain family reunification. This study deepens the understanding of the organizational dynamics and adaptive strategies of migrant families and offers new empirical evidence and analytical insights for promoting equitable public service provision and building child-friendly cities.

In the study of telecom network fraud, traditional perpetrator-focused research approaches face significant challenges due to the high level of concealment of offenders, the difficulty in tracking their whereabouts, and the low case resolution rates. Conversely, a victim-centered research perspective proves to be more feasible. This paper takes Xiaoshan District, Hangzhou City, Zhejiang Province, as a case study, using data from all telecom network fraud victim cases reported in the district in 2021. Focusing on the severity of fraud victimization as the research subject, a generalized hierarchical linear regression model with a two-level nested structure (individual victim and community) is constructed. The model analyzes the relationships among individual characteristics, case attributes, and community environmental factors with the probability of individuals experiencing large-amount fraud. The findings are as follows: ① The hotspot regions of fraud cases with varying financial losses largely overlap, while those involving large-scale losses are more concentrated. ② There are significant inter-community differences in the severity of fraud victimization. ③ Age and case duration (time between the initial contact with the perpetrator and reporting to authorities) show a significant positive correlation with the probability of large-scale fraud victimization. Women and permanent residents are more likely to experience large-scale fraud compared to men and migrant populations. Cases involving credit and investment schemes have a higher likelihood of large-scale fraud victimization than other case types. ④ Community environmental variables moderate the impact of individual factors on victimization severity. Specifically, an increase in the proportion of migrant populations within a community significantly raises the likelihood of large-scale fraud victimization among women and younger individuals and increases the probability of large-scale fraud in recruitment, part-time job, and romance-related scams. A higher proportion of rental housing in a community enhances the impact of case duration on the probability of large-scale fraud victimization. An increase in the proportion of people aged 19-45 in a community significantly raises the likelihood of men experiencing large-scale fraud, amplifies the impact of case duration, and decreases the probability of large-scale fraud in shopping and romance-related scams. The conclusions of this study provide valuable insights for the situational prevention of victimization in telecom network fraud.

The Lancang-Mekong River Basin (LMRB) is a significant transboundary basin in Asia, and frequent droughts have exerted profound impacts on the socio-economic conditions and transboundary water resources cooperation in the basin. Current studies on the spatiotemporal evolution and characteristics of drought events in the LMRB primarily rely on ground-based observations or reanalysis data, with limited application of near-real-time satellite precipitation products. This constraint hinders real-time drought monitoring and early warning capabilities across the basin. This study utilizes the PERSIANN-CDR remote sensing precipitation product (1983-2020) and ground-based observational precipitation data (1983-2015), combined with the 3-month Standardized Precipitation Index (SPI3), to identify drought events through run theory and analyze the variation trends and characteristics of drought events in the LMRB. The results indicate that: ① The PERSIANN-CDR remote sensing product exhibits excellent performance in precipitation monitoring during the dry season in the LMRB, with an average correlation coefficient of 0.91 and a root mean square error of approximately 37 mm/month compared to ground observation data. ② Over the 38-year period from 1983 to 2020, the LMRB showed an overall wetting trend, with the wetting area accounting for approximately 80.2% of the basin, primarily concentrated in the upstream regions of the Lancang River Basin (LRB) and the downstream areas of the Mekong River Basin. Conversely, the mid-lower LRB displays a trend of aridification, with only 1.9% of the area showing a significant drying trend. ③ The PERSIANN-CDR satellite precipitation data demonstrate certain applicability in monitoring drought events. However, except for the 1992 drought event, the satellite data generally underestimated drought severity by an average of 10%. This study provides valuable reference information for drought monitoring and assessment in the LMRB.

Green spaces serve as a critical means to alleviate the urban heat island effect. Under the current planning trend toward miniaturized and anisotropic urban green spaces, an in-depth exploration of the cooling effects and underlying drivers of micro green spaces in different sub-centers holds significant practical value. Taking Hangzhou—a typical polycentric city as the case study, this research leverages multi-source remote sensing data and employs boosted regression tree (BRT) analysis to evaluate the cooling effects and influencing factors of micro green spaces in three major sub-centers: Linping, Xiasha, and Jiangnan. The results show that: (1) The cooling effect of micro green spaces is significant but varies regionally. Their cooling capacity is primarily affected by the landscape characteristics of the green space patches themselves. It is also correlated with these characteristics of the surrounding urban areas. (2) The three sub-centers have different threshold values for the marginal effects of the influencing factors of green space cooling capacity, including NDVI (0.58), patch perimeter (1,600 m and 1,450 m), and surrounding building density (0.26-0.31). (3) The differences in the cooling effect of micro green spaces among sub-regions are the result of the comprehensive formation of the functional positioning, development model and land use of each sub-center. This paper compares the cooling effect of micro green spaces in different regions of a polycentric city, offering a reference for the fine planning and design of urban green space landscapes.