The Longzhong region,a critical zone for ecological security within the upper reaches of the Yellow River,has historically been confronted with water scarcity and recurrent droughts,impeding its development.The elucidation of the mechanisms through which climatic factors and drought risk are associated is of practical signif-icance for the support of targeted drought mitigation,the optimization of water resource allocation,and the im-provement of the operation of water conservancy projects.This study utilized precipitation and potential evapo-transpiration(PET)data from 1980 to 2023 to systematically analyze the spatiotemporal evolution characteristics of drought and its coupled relationship with precipitation and PET.This analysis was conducted by applying methods such as the standardized precipitation evapotranspiration index(SPEI),climate tendency rate,and spatial interpolation.The results indicate that:(1)The drought evolution in the Longzhong region is characterized by three distinguishable stages.From 1980 to 1990,the frequency of droughts was 29.55%,from 1991 to 2010,it was 42.49%,and from 2011 to 2023,it was 23.72%.(2)From 1991 to 2023,the frequency of moderate-to-severe droughts during the spring and summer months reached 19.23%or higher,posing a significant threat to key agri-cultural periods.A notable finding was the highly significant increasing trend(P<0.01)exhibited by spring PET in Dingxi City,which served to exacerbate the ongoing drought conditions.(3)El Niño events increase the risk of drought,with the frequency of moderate-to-severe droughts rising 5.21 percentage points in El Niño years com-pared to non-El Niño years.The present study discloses the differential patterns between climatic factors and drought risk in the Longzhong region,thereby providing a scientific basis for regional drought mitigation strate-gies,optimization of agricultural planting structures,and informed scheduling of water conservancy projects.
The northern agropastoral ecotone serves as a critical ecological transition zone in China.The coordina-tion level between new-type urbanization development and agricultural ecosystem service influences regional re-source use efficiency and ecological stability,as well as its sustainable development potential.Focusing on 26 counties in the central northern agropastoral ecotone of China as the study area,this study constructs an evalua-tion system for new-type urbanization across four dimensions:population,economy,society,and agriculture.Based on land use data,an agricultural ecosystem service value assessment model is developed.Hotspot analysis,the coupling coordination degree model,and the geographical detector are employed to systematically analyze the spatiotemporal patterns and interaction mechanisms of new-type urbanization levels and agricultural ecosys-tem service values from 2010 to 2023.The results indicate that(1)The new-type urbanization level in the study area from 2010 to 2023 rose significantly,while agricultural ecosystem service values exhibited a fluctuating downward trend,with both variables maintaining a consistent"high in the east,low in the west"spatial distribu-tion.(2)The coupling coordination between new-type urbanization and agricultural ecosystem services is charac-terized by"low-level stagnation and intensifying polarization",with no counties yet achieving a state of coordi-nated development.(3)Geodetector analysis reveals that the driving mechanism is predominantly an"agricultur-al development-led"model,with per capita arable land and agricultural mechanization efficiency per unit area serving as the primary drivers.Interaction detection further shows an evolutionary shift in dominant factors from"economic-agricultural"to"intra-agricultural"synergies,ultimately resulting in a synergistic constraint driven by"resource-natural"factors.The results provide critical insights into the complex interactions between new-type urbanization and the agroecological environment,offering a scientific basis for formulating differentiated spatial governance policies that coordinately advance socio-economic development and agricultural ecological conservation.
Enhancing the livelihood resilience of poverty alleviation households is central to consolidating pover-ty reduction outcomes and preventing long-term poverty recurrence.Based on 2023 micro-survey data from 496 poverty alleviation households in Ulanqab,Inner Mongolia,China,this study measures farmers'livelihood resil-ience using the entropy method and the comprehensive index method.Multiple linear regression,mediation effect modeling,propensity score matching,and instrumental variable methods were employed to examine the effects and mechanisms of digital finance use and endogenous livelihood capital on household livelihood resilience.The findings are as follows:(1)Livelihood resilience reflects farmers'capacity to withstand risks and recover from livelihood shocks.Its key determinants include endogenous livelihood capital(personal health,household eco-nomic,human capital),as well as external support(digital finance).(2)Among the endogenous factors,better per-sonal health and stronger household economic conditions significantly improve livelihood resilience,whereas ad-vanced age significantly constrains it.(3)The use of digital finance significantly enhances livelihood resilience through two pathways:promoting agricultural technology adoption to improve production efficiency and facilitat-ing livelihood diversification to expand income sources.(4)The endogenous livelihood capital and digital finance operate synergistically,helping to overcome structural constraints associated with advanced age and low educa-tional attainment among poverty alleviation households.These results provide micro-level empirical evidence for optimizing livelihood support policies aimed at strengthening rural resilience and reducing the risk of poverty re-currence.
Enhancing employment quality is a crucial pathway to achieving high-quality and full employment,which is vital to promoting economic development,maintaining social stability,and improving people's liveli-hoods.Using panel data on 29 Chinese provinces from 2011 to 2023,this study constructs an employment quality evaluation index system characterized by"one core with two wings".By employing methods such as the Dagum Gini coefficient,Markov chain,spatial convergence model,econometric regression models,and geographical de-tector,this study systematically examines the sources of disparities,dynamic evolution,spatial characteristics,and influencing factors of employment quality in China.The results reveal that(1)China's employment quality demonstrates an overall steady upward trend,with inter-regional disparities constituting the principal source of the overall variation in employment quality levels.Spatially,it exhibits a gradually increasing gradient from the northwest to the southeast,accompanied by significant spatial agglomeration.(2)As the duration of transition pe-riods extends,employment quality displays a tendency to shift toward adjacent levels,exhibiting characteristics of spatial convergence.(3)The improvement of employment quality exhibits a self-reinforcing cumulative effect.Factors such as transportation accessibility,industrialization level,and the degree of government intervention have relatively large coefficients,indicating their pronounced role in promoting employment quality.(4)The en-hancement of employment quality depends on the synergistic effects of multiple factors,among which transporta-tion accessibility and population density are identified as the core driving forces.The conclusions of this study can offer valuable insights for formulating differentiated and targeted policies for elevating employment quality.
Based on panel data from 30 provinces,autonomous regions,and municipalities in China from 2014 to 2023,this study employs the entropy weight method,social network analysis,and exponential random graph mod-els to systematically examine the structural characteristics and driving factors of the spatial correlation network of agricultural resilience in China.The results indicate that(1)Agricultural resilience shows a steady upward trend,although development across dimensions remains uneven.Economic and social resilience perform relatively well,whereas production and ecological resilience lag behind.(2)The spatial correlation network of agricultural resilience exhibits a flat development trend.Although the overall network remains highly accessible,close corre-lations have not yet formed,and most provinces,autonomous regions,and municipalities maintain one-way corre-lations.(3)The spatial correlation follows a"west-central-east"radiation path.Net spillover sectors are mainly concentrated in the central and western regions,whereas net benefit sectors are primarily distributed in the central and eastern regions,and the broker sector still requires substantial improvement.(4)The formation of spatially correlated networks of agricultural resilience in China results from the interplay of endogenous structures,actor attributes,and external environments.Endogenous structures such as reciprocity and circularity promote the for-mation of the agricultural resilience network.Economic level,production conditions,industrial structure,and ex-treme heavy rainfall are the core driving forces for the formation of the agricultural resilience network,while geo-graphical proximity and trade are important external driving forces.
Enhancing the coupling coordination between digital economy development and common prosperity is an important pathway for promoting high-quality economic development and social equity.This study examines the coupling coordination between the digital economy and common prosperity based on provincial panel data from China spanning 2013 to 2023.Composite indices for the digital economy and common prosperity were con-structed using the comprehensive evaluation method,and a coupling coordination model was applied to assess the interaction level between the two systems.Kernel density estimation and the Dagum Gini coefficient were fur-ther employed to analyze the spatiotemporal evolution and sources of regional disparities.The research results in-dicate:(1)The composite index of the digital economy increased by 2.067 times between 2013 and 2023,form-ing a"multi-center networked"spatial pattern driven by the core regions of the Beijing-Tianjin-Hebei region,Yangtze River Delta,and Pearl River Delta.Over the same period,the composite index of common prosperity in-creased by 0.975 times,showing a spatial gradient characterized by stronger development in eastern China and weaker development in western China.(2)From 2013 to 2023,the coupling coordination degree between the digi-tal economy and common prosperity steadily improved.Spatially,the eastern region maintained the highest level of coordination,followed by the central region,while the western and northeastern regions remained relatively lagging.(3)During the study period,overall regional disparities in coupling coordination showed a gradual con-vergence trend.Inter-regional differences were the main source of these disparities,with an average contribution rate of 66.20%.In particular,the gap between the eastern region and the central,western,and northeastern re-gions was substantially larger than that among the latter three regions,indicating persistent regional imbalances.
Investigating the coupling coordination relationship between new urbanization and high-quality devel-opment of tourism is crucial to the steady advancement of Chinese-style modernization.Building on the coupling coordination mechanism between new urbanization and high-quality development of tourism,this study utilizes provincial panel data on China from 2014 to 2023 and employs the coupling coordination degree model,the ob-stacle degree model,and the geodetector to analyze the spatiotemporal evolution,obstacle factors,and driving forces of their relationship.The results indicate that(1)From 2014 to 2023,the levels of both new urbanization and high-quality development of tourism exhibited a significant overall upward trend,and their evolutionary tra-jectories demonstrated high consistency from 2014 to 2019.(2)The coupling coordination degree between the two systems experienced a volatile rise,characterized by substantial regional differences that formed a decreasing spatial pattern from the eastern coast to the central and western inland regions.(3)Regarding the obstacle factors,economic urbanization and tourism innovation development were the primary obstacles at the criterion layer for the new urbanization system and the high-quality development system of tourism,respectively.At the indicator layer,GDP per capita and the number of tourism students were the core obstacles.(4)Among the driving factors,the level of economic development and the capacity for government intervention had the strongest explanatory power for the coupling coordination degree,whereas the influence of scientific and technological innovation was relatively limited.
With the development of the tourism industry and the increasingly fragile ecological environment,the issue of ecological security in tourism has attracted attention.Using 277 domestic and international studies on tourism ecological security from the Web of Science and the China National Knowledge Infrastructure,a knowl-edge graph was developed using CiteSpace visualization analysis software.The results show that(1)From 2000 to 2024,the number of published papers on tourism ecological security,both domestically and internationally,has generally been increasing.(2)Among foreign research organizations,Australia and the USA have published a rel-atively large number of papers.Among domestic research organizations,the Tourism College of Hunan Normal University has published the largest number of papers.(3)Foreign research tends to apply interdisciplinary meth-ods,such as deep learning and internet of things technology,to explore global issues,such as climate change,sus-tainability,and ecological integrity,with a relatively broad research scale.Domestic research focuses on the appli-cation of methods such as geographic detectors and driving factors-pressure-state-impact-response models,focus-ing on multi-dimensional issues such as the evaluation of tourist destinations,spatiotemporal evolution,and sus-tainable development.The research scale has a more detailed regional division.(4)Keyword emergent analysis re-veals that foreign countries pay more attention to the interactions and influencing mechanisms between tourism activities and the ecological environment,as well as in-depth discussions on sustainable development.Domesti-cally,the assessment focused on the ecological security of the entire tourist city,and factors hindering tourism ecological security,sustainable development,and spatiotemporal patterns are emphasized.Future studies on do-mestic tourism ecological security should focus on broadening research perspectives,innovating research indica-tors and methods,and strengthening international cooperation and exchanges to achieve harmonious coexistence between the tourism industry and the ecological environment.
To identify ways to reduce urban-rural income-quality disparity,this study examines digital technology as a means of accelerating the achievement of common prosperity.Using panel data from 2018,2020,and 2022 China family panel studies,we empirically analyze the mechanisms through which digital technology influences household income quality,apply spatial and income-level heterogeneity tests,and uncover relative advantages of rural households through urban-rural comparisons.This study find that:(1)Digital technology use significantly improves income quality for both urban and rural households,with stronger effects in rural households,particular-ly in terms of stability,structure,and knowledge.(2)Mechanism analysis shows that digital technology use by ur-ban-rural households enhances income quality by promoting household entrepreneurship,with a stronger effect in rural areas.(3)The positive effect of digital technology use on household income quality in both urban-rural ar-eas follows a gradient pattern of"west>central>east".(4)Income level heterogeneity shows that the positive ef-fect of digital technology use on income quality is stronger for low-income households compared with non-low-income households within rural areas,whereas the opposite pattern is observed within urban areas.These find-ings suggest that digital technology use has certain advantages in improving the income quality of rural areas,un-derdeveloped regions,and disadvantaged groups,demonstrating its inclusive potential.
Using Baidu migration data from 2019 to 2023,networks of labor migration in China were constructed in this study.Social network analysis methods,a temporal exponential random graph model(TERGM),and a spa-tial econometric model were employed to examine the influences of urban amenity on the probability and strength of relationships within labor migration networks,further exploring their spatial interaction.This study re-vealed:(1)China's interurban labor migration network exhibits temporal binary stability,forming a diamond-shaped structure centered on the urban clusters of Beijing-Tianjin-Hebei,the Yangtze River Delta,the Pearl River Delta,and Chengdu-Chongqing.Dual-high node cities such as Guangzhou,Shanghai,and Dongguan are concen-trated in the Pearl River Delta and Yangtze River Delta regions,and the attractiveness of other urban clusters has also been increasing.The labor migration networks that were formed from 2019 to 2023 have shown distinct sub-group structures,and there has been frequent population movements between cities within subgroups.(2)The ex-istence of urban amenity preferences has been proven during labor migrations,especially where greater man-made amenities have increased the probability of forming interurban labor migration networks,significantly im-pacting both population inflows and outflows.(3)The influence of urban amenities on the strength of labor migra-tion path relationship leads to spatial spillover effects,and this impact also acts on other cities.This study ex-pands the understanding of noncompensatory factors of regional disparity and mechanisms driving labor migra-tion networks,which forms a significant scientific contribution to the evolution and driving forces of China's la-bor migration networks.
As a crucial ecological functional zone in northwest China,the ecosystem service functions of the Tarim Basin Economic Belt are vital for regional sustainable development.Based on meteorological,topographic,and remote sensing data from 2000 to 2023,this study utilizes the revised wind erosion equation model and the InVEST model to quantitatively evaluate the spatiotemporal evolution patterns of five ecosystem services in the region,including windbreak and sand fixation,soil conservation,carbon storage,water yield,and habitat quality.Furthermore,spatial overlay analysis and bivariate spatial autocorrelation methods were employed to investigate the trade-offs and synergies among these services at multiple scales.The results indicate that(1)From 2000 to 2023,soil conservation and carbon storage generally increased,whereas windbreak and sand fixation and water yield decreased overall;habitat quality remained relatively stable.Spatially,all services exhibited significant het-erogeneity,with notable improvements concentrated in the western and southern regions.(2)Spatial overlay anal-ysis based at a 1 km×1 km grid scale reveals that the correlations among ecosystem services are predominantly characterized by low synergies and strong trade-offs,with a shift in 2005 from dominance of strong trade-offs to prevalence of low synergies.(3)At the 10 km×10 km grid scale,bivariate spatial autocorrelation analysis re-vealed that most pairwise service correlations were synergistic,except for windbreak and sand fixation versus wa-ter yield,which exhibited a dominant trade-off.
Due to global warming,regional glacier retreat has become significant,and the consequent expansion and outburst of glacial lakes seriously threaten public safety and property.The factors affecting glacial lake out-bursts are numerous and interact in complex ways,making their prediction challenging.Using glacial lakes in the Poiqu River Basin in the semi-arid region of Xizang in China as an example,the key indicators of glacial lake out-bursts were identified using statistical analysis,and the outburst susceptibility was predicted using coupled model intercomparison project phase 6 data(CMIP6).The main conclusions are as follows:(1)In 2024,there were a to-tal of 143 glacial lakes in the Poiqu River Basin,approximately 50%of which decreased in area,and approxi-mately 29%increased in area,the latter being mainly moraine-dammed lakes.(2)Regional glacial lake outburst susceptibility evaluation models were established based on multilayer perceptron(MLP),support vector machine(SVM),and extreme gradient boosting(XGB)models with significant differences,with evaluation accuracy rang-ing from 67%to 79%.(3)The black kite algorithm(BKA)was introduced to train and generate base models,in-cluding BKA-MLP,BKA-SVM,and BKA-XGBoost,and their predictions were used as the training set for the meta model,which was then optimized to establish a stacking model.After optimization,the accuracy of the tradi-tional machine learning models improved to 79%-82%,and the stacking model's accuracy increased to 83.03%with an area under the curve of 0.84.(4)The stacking model's susceptibility prediction indicates that under differ-ent models and scenarios,the probability of glacial lake outbursts shows a fluctuating upward trend,and highly susceptible glacial lakes are concentrated in Chongduipu,Keyapu,Rujiapu,and the Zhangzangbu Gully.The re-sults of this research provide a scientific basis for predicting glacial lake outburst disasters caused by climate change.
High-quality development of ecotourism is a key lever for easing resource constraints,optimizing na-tional territorial space,and advancing green development.Using panel data from 278 prefecture-level cities in China from 2015 to 2024,this study constructs multidimensional composite index systems for new quality pro-ductive forces and high-quality development of ecotourism.We examine the effect of new quality productive forc-es on the high-quality development of ecotourism in China using a combination-weighting approach,a two-way fixed-effects model,and a mediation-effect model.The results show that(1)New quality productive forces signif-icantly promotes the high-quality development of ecotourism,and this finding is robust.(2)The new quality pro-ductive forces can promote the high-quality development of ecotourism through three paths:green technological innovation,optimization of the tourism industry structure,and institutional innovation.(3)The effect of new qual-ity productive forces on the high-quality development of ecotourism is stronger in nonresource-based areas and ecological security barrier areas than in resource-based areas and non-ecological security barrier areas.By focus-ing on emerging ecotourism business forms,this study clarifies the mechanisms through which new quality pro-ductive forces drives high-quality development of ecotourism and provides theoretical implications for policies aimed at promoting high-quality development of ecotourism.
High-quality development of the planting industry is a fundamental support and key pathway for build-ing an agricultural powerhouse in China.Assessing how agricultural water price reform influences the industry's high-quality development can provide evidence to guide the further deepening and effective implementation of re-form policies.From an input-output perspective,this study examines the effects and mechanisms of agricultural water price reform on the high-quality development of China's planting industry and measures the level of high-quality development of planting industry.We construct an index to measure the level of high-quality development and employ a staggered difference-in-differences model to test the policy's impacts,mechanisms,and regional heterogeneity.The results show that(1)From 2011 to 2022,the level of high-quality development in China's planting industry increased overall,with clear spatial disparities:eastern coastal provinces and northern ma-jor grain-producing areas performed better,and a stepwise decline is observed from central to western re-gions.(2)The findings also suggest that agricultural water price reform significantly promotes high-quality devel-opment,but the effects vary across regions,with stronger effects in major grain-producing areas and southern re-gions.(3)The reform advances high-quality development by encouraging agricultural water conservation,opti-mizing cropping structures,and increasing the adoption of water-saving irrigation technologies;these mecha-nisms also exhibit marked regional heterogeneity.These findings suggest that future reforms should adopt a differ-entiated framework for deepening implementation,tailored to regional conditions,to better support high-quality development of the planting industry.
Clarifying the evolution process and influencing factors of rural"production-living-ecological spaces"conflict patterns in the metropolitan coordinating regions is a theoretical prerequisite for achieving high-quality synergistic development.Considering the Yinchuan metropolitan coordinating region,a cultivated metropolitan coordinating region in northwest China,as an example,this study integrates spatial conflict measurement models,hotspot analysis(Getis-Ord G*i),and the geographical detector model to analyze the spatiotemporal evolution process,mechanisms,and driving factors of rural"production-living-ecological spaces"conflicts since the urban-rural integration development stage.The results reveal that(1)Since the urban-rural integration stage,rural"pro-duction-living-ecological spaces"in the Yinchuan metropolitan coordinating region have maintained a long-term trade-off relationship.The conflict patterns exhibit significant"urban-rural differentiation"clustering characteris-tics in spatial dimensions and follow a"spatiotemporal alternation"evolution in temporal dimensions.(2)Differ-ences in"natural endowments,urban-rural relationships,and development stages"dimensions are identified as core factors driving the formation and evolution of these conflicts.The study proposes that in the post-urban-rural integrated development phase,optimizing conflict patterns requires policy interventions as catalysts,supported by"terrain,geographic location,and transportation accessibility",to achieve effective coordination among"re-source endowment,population scale,and industrial structure".This framework aims to deepen the optimization of rural"production-living-ecological spaces"conflicts in the Yinchuan metropolitan coordinating region.
New quality productive forces are a crucial pillar to achieve high-quality development,providing fresh momentum for the high-quality development of tourism economy in China.Focusing on new quality productive forces and the high-quality development of the tourism economy,this study employs panel data from 30 provinc-es(autonomous regions and municipalities)(excluding Xizang,Hong Kong,Macao,and Taiwan)in China span-ning 2012-2022.Two corresponding indicator systems are constructed to empirically analyze the inherent mech-anisms and spatial effects through which new quality productive forces drives high-quality development of tour-ism economy.The results show that:(1)New quality productive forces significantly promote the high-quality de-velopment of tourism economy in China.Regional heterogeneity is evident:while pronounced positive effects are observed in the eastern and western regions,with stronger impacts in the latter,the effects in central and north-eastern regions remain statistically insignificant.(2)The findings also highlight that industrial structure upgrading and marketization serve as critical mediating pathways for the influence of new quality productive forces on the high-quality development of the tourism economy.Notably,industrial structure upgrading makes a greater contri-bution than marketization.The findings can provide data support for relevant theoretical studies and offer theoreti-cal guidance for advancing the high-quality development of the tourism economy.
Based on a Bayesian ensemble change detection algorithm,this study integrates passive microwave da-ta,MODIS products,and meteorological and hydrological variables to comprehensively analyze lake ice phenolo-gy and its driving factors for seven large lakes in the arid region of northwest China over the period 1978-2022.The results are summarized as follows:(1)Cross-validation between passive microwave remote sensing data and Landsat observations yields a mean coefficient of determination of 0.86,with a mean absolute error of 1.56 days and a root mean square error of 2.52 days.These results indicate that passive microwave data provide a feasible and reliable approach for extracting lake ice phenology,despite minor local discrepancies.(2)Across the seven lakes in the arid region of northwest China,the average onset of ice formation occurred between November 17 and January 19 of the following year,while complete ice-off dates ranged from July 11 to October 25.The mean ice-covered duration was 143 days.All lakes exhibited a shortening trend in ice duration,with Bosten Lake showing the smallest reduction rate(0.24 days per decade)and Sayram Lake the largest(0.55 days per decade).(3)Lake freeze-onset dates displayed both advancing and delaying trends,whereas ice-off dates predominantly advanced in the arid region of northwest China from 1978 to 2022.For most lakes,the onset and complete freeze dates were de-layed at rates of 0.09-0.38 days per decade and 0.24-0.29 days per decade,respectively.In contrast,a few lakes,including Jili Lake and Bosten Lake,exhibited advancing freeze-onset trends.In high-latitude regions(excluding Ebinur Lake),ice-off dates advanced significantly at rates of 0.27-0.48 days per decade,whereas high-altitude lakes exhibited weaker trends ranging from 0.12 to 0.27 days per decade.(4)Lake ice freeze-thaw cycles in the arid region of northwest China are jointly controlled by meteorological factors(wind speed,snow cover,precipita-tion,and near-surface air temperature)and hydrological characteristics(lake area and water transparency).Near-surface air temperature directly governs the timing of lake ice freezing and melting,whereas lake area and trans-parency indirectly influence ice phenology by regulating water heat capacity and solar radiation absorption.
Ice and snow tourism has emerged as a crucial driving force for regional economic and cultural revital-ization.This study employs accessibility measurement,hotspot analysis,and geographic detectors to evaluate the accessibility of ice and snow tourism destinations in the Yellow River Basin.We also examine their spatial distri-bution characteristics and influencing factors.The main findings show that:(1)Ice and snow tourism destinations in the Yellow River Basin exhibit an uneven spatial distribution characterized by a"dense east and sparse west"pattern.Moreover,clustering tendencies are apparent,wherein the downstream region contains the highest num-ber of destinations,whereas the upstream region has the fewest.At the provincial scale,Shandong,Shanxi,and Henan have relatively more destinations,and at the municipal scale,Jinan,Zhengzhou,and Qingdao lead in the number of destinations.(2)Accessibility to ice and snow tourism destinations in the Yellow River Basin reveals a spatial gradient,described as"convenient in the downstream,moderate in the midstream,and restricted in the up-stream areas".The experiential tourism destinations dominate numerically;however,their overall accessibility re-mains relatively weak.(3)Hotspots and subhotspots of accessibility to ice and snow tourism destinations in the Yellow River Basin are concentrated in cities within Shandong and northern Henan.In contrast,cold spots and subcold spots mainly occur in cities located within the upstream and midstream regions.(4)A combination of so-cial,economic,and ecological factors jointly influences accessibility to ice and snow tourism destinations in the Yellow River Basin.Specifically,road mileage,urbanization rate,and annual average snowfall comprise the pri-mary determinants.These findings provide a scientific reference for optimizing resource allocation and promot-ing coordinated regional development in the Yellow River Basin's ice and snow tourism sector.
Promoting the coordinated development of different elderly care models is an effective way to opti-mize the allocation of elderly care service resources in our country.Based on panel data from 2018 to 2022,this study empirically analyzes spatiotemporal coupling coordination and influencing factors of home community el-derly care and institutional elderly care in China using a coupling coordination model,a geographic detector,and other methods.The results indicate that(1)The coupling coordination degree and relative development degree be-tween home community elderly care and institutional elderly care are generally on the rise.The coupling coordi-nation degree has shown a continuous improvement trend over time.The relative development degree of home community elderly care is gradually becoming clear with the trend of"synchronous development＞advanced de-velopment＞lagging development".(2)The number of provinces entering the coordination stage(III and IV)con-tinues to increase and shows an evolutionary pattern of gradually spreading from the central and eastern regions to the western and northeastern regions in space.The phenomenon of stage transition in relative development is more pronounced,and the western region has significantly more provinces in transition than the central and east-ern regions.(3)The coupling coordination degree has a positive spatial correlation and a fluctuating upward trend.The correlation strength shows a spatial pattern of"western＞eastern＞central＞northeast",with mostly HH-type and LL-type clustering.(4)Organizational strength,elderly care demand,and technological level are the main influencing factors of the coupling coordination degree.This study's findings can provide a theoretical ba-sis and policy recommendations for addressing structural contradictions in China's elderly care service supply and for innovating the development of the elderly care policy system.
With the acceleration of global urbanization,the severe PM2.5 pollution in arid zone cities,owing to their unique geographical and climatic conditions,exhibits strong non-stationarity and complex spatiotemporal characteristics,making it difficult for traditional prediction models to effectively capture its dynamic patterns.To address this challenge,this study proposes a hybrid prediction framework of an"adaptive noise complete ensem-ble empirical mode decomposition-Ivy optimization algorithm-Kolmogorov Arnold network-bidirectional long short-term memory neural network"(CEEMDAN-IVY-KAN-BiLSTM),aiming to enhance the prediction accura-cy of PM2.5 concentrations.This framework jointly extracts multi-scale features through noise reduction decompo-sition as well as parameter optimization and integrates the strong nonlinear fitting and bidirectional time series modeling capabilities of the KAN-BiLSTM model,effectively improving the prediction performance.The results reveal that the PM2.5 concentration in Urumqi City from 2021 to 2024 shows significant seasonal fluctuations,with an average of 41.97 μg·m-3 in winter due to coal heating and the influence of the inversion layer and drops to 14.04 μg·m-3 in summer due to enhanced atmospheric convection.Moreover,it shows an overall decreasing trend annually.Moreover,the importance ranking of the data indicates that PM2.5 is significantly positively corre-lated with air quality index,PM10,CO,and NO2,and negatively correlated with temperature and dew point tem-perature,suggesting that coal emissions,vehicle exhaust,and meteorological diffusion conditions are the main in-fluencing factors.Moreover,the model effectively separates the high-frequency fluctuations(such as sandstorm events)and low-frequency trends(seasonal changes)in the PM2.5 sequence,reducing the impact of data non-sta-tionarity.Finally,the experiments were based on daily air quality data in Urumqi City from 2021 to 2024,results of which demonstrate that this model achieves the coefficient of determination,mean absolute error,and root mean square error values of 0.991,1.391,and 1.881,respectively,significantly outperforming conventional ma-chine learning and common deep learning models.This verifies the applicability of the"decomposition-optimiza-tion-integration"deep learning framework in the prediction of arid zone cities.
