Analysis of spatial distribution characteristics and driving factors of ethnicminority villages in China using geospatial technology and statistical models

This study aims to reveal the spatial structural characteristics of 1,652 Ethnic-Minority Villages(EMV)in China and to analyze the mechanisms driving their spatial heterogeneity.EMV are a special type of settlement space that preserve a large number of historical traces of the ethnic culture of ancient China.They are important carriers of China’s excellent traditional culture and are key to the implementation of rural revitalization strategies.In this study,1652 EMV in China were selected as the research subjects.The Nearest Neighbor Index,kernel density,and spatial autocorrelation index were employed to reveal the spatial structural characteristics of minority villages.Neural network models,spatial lag models,and geographical detectors were used to analyze the formation mechanism of spatial heterogeneity in EMV.The results indicate that:(1)EMV exhibit significant spatial differentiation characterized by“single-core with multiple surrounding sub-centers,”“polarization between east and west,”“decreasing quantity from southwest to east coast to northeast to northwest,”and“large dispersion with small agglomeration.”(2)EMV are mainly distributed in areas rich in intangible cultural heritage,with high vegetation coverage and low altitude,far from central cities,and having limited arable land and an underdeveloped economy and transportation,particularly in shaded or riverbank areas.(3)Distance from the nearest river(X3),distance from central cities(X8),national intangible cultural heritage(X9),and NDVI(X10)were the main driving factors affecting the spatial distribution of EMV,whereas elevation(X1)and GDP(X5)had the weakest influence.As EMV are a relatively unique territorial spatial unit,the identification of their spatial heterogeneity characteristics not only deepens the research content of settlement geography,but also involves the assessment,protection,and development of Minority Villages,which is of great significance for the inheritance and utilization of excellent ethnic cultures in the era.

Analysis on the Spatial Agglomeration and Coupling of Socioeconomic Factors in Qinghai Tourism Under the Background of“Belt and Road”

Qinghai is the strategic base and important fulcrum of the Belt and Road Initiative while tourism is a strategic pillar industry in Qinghai Province.Due to its rich tourism resources and unique ecological environment,the integration of tourism in Qinghai into the Belt and Road has attracted great attention of the Asian Development Bank(ADB).With the spatial data of tourism elements POI and the statistical data of 44 counties in Qinghai to analyze the characteristics and influencing factors of the spatial agglomeration of tourism in Qinghai,the paper conducts research on spatial coupling and concludes with the following results:The spatial agglomeration of tourism in Qinghai presents the distribution pattern of“one circle and one belt”;economic density and population density play an important role in the formation of the spatial agglomeration pattern of tourism with some spatial spillovers;Belt and Road has a significant impact on the promotion of tourism agglomeration in Qinghai.The paper suggests that tourism in Qinghai should fully integrate into the Belt and Road,giving full play to the guiding role of Belt and Road in the allocation of social and economic resources,and optimizing the spatial layout.

Agricultural Non-point Source Pollution in China:Evaluation,Convergence Characteristics and Spatial Effects

In this study,an inventory analysis approach was used to investigate the intensity of agricultural non-point source pollution(ANSP)and its spatial convergence at national and provincial levels in China from 1999 to 2017.On this basis,spatial factors affecting ANSP were explored by constructing a spatial econometric model.The results indicate that:1)The intensity of China's ANSP emission showed an overall upward trend and an obvious spatial difference,with the values being high in the eastern and central regions and relatively low in the western region.2)Significant spatial agglomeration was shown in China's ANSP intensity,and the agglomeration effect was increasing gradually.3)In the convergence analysis,a spatial lag model was found applicable for interpretation of the ANSP intensity,with the convergence rate being accelerated after considering the spatial factors but slower than that of regional economic growth.4)The spatial factors affecting the ANSP intensity are shown to be reduced by improving agricultural infrastructure investment,labor-force quality,and crop production ratio,while the expansion of agricultural economy scale and precipitation and runoff have positive impact on ANSP in the study region.However,agricultural research and development(R&D)investment showed no direct significant effect on the ANSP intensity.Meanwhile,improving the quality of the labor force would significantly reduce the ANSP intensity in the surrounding areas,while the precipitation and runoff would significantly increase the pollution of neighboring regions.This research has laid a theoretical basis for formulation and optimization of ANSP prevention strategies in China and related regions.

Spatial Spillover and the Factors Influencing Public Service Supply in Sichuan Province, China

This article examines the spatial characteristics of public service supply and the factors influencing such supply in cities of Sichuan Province, China using spatial-autocorrelation and spatial econometric models with statistical data in 2012. The results demonstrate that expenditures on different types of public services present different spatial autocorrelation patterns. Although the spatial differences in basic public service expenditures are relatively small, a clear fan-shaped spillover to the east can be seen in Chengdu City. Chengdu also shows high clustering of advanced public service expenditures, being a typical core-periphery pattern. Post-earthquake reconstruction expenditures are clustered in the "5.12 Wenchuan earthquake" region and spill over toward cities to the east. The efficiency of public services in the mountainous areas in western Sichuan is low and exhibits a pattern of low-low spatial autocorrelation. The efficiency of public service supply is affected by economic, social, political and geographical factors. Based on the results of this analysis, we recommend a supply strategy that incorporates different types of public services and a specialized public service supply strategy for mountainous areas. Overall public service efficiency should be enhanced by focusing on narrowing the gap in farmers' income among regions and accelerating urbanization. Decision-makers should consider moresupportive policies with regard to providing basic public services in mountainous areas to ensure an equalized supply of basic public services. To enhance the efficiency of advanced public service supply, additional growth pole should be encouraged and incentivized; however, investments are required to drive the development of the peripheral regions through regional economic integration. Both software and hardware types of infrastructure are required to supply services efficiently during post-disaster reconstruction.

Urban Agglomerations in China: Characteristics and Influencing Factors of Population Agglomeration

Urban agglomeration(UA)is an advanced spatial economic form formed and developed in the process of rapid industrialization and urbanization,and an important carrier of urbanization and economic development.The economy has developed rapidly in the recent decades of China,and the UAs have also developed rapidly.However,as a large population country,the population distribution and changes of UAs in China has unique characteristics.Using the fifth,sixth and seventh population census data,spatial auto-correlation and spatial econometric models,we analyzed the spatial-temporal evolution characteristics and influencing factors of population agglomeration in China’s UAs.Results revealed that:1)from 2000 to 2020,the population gradually converged into UAs,and the characteristics of population agglomeration in different development degree of UAs differ.The higher the development degree of UA,the higher the population agglomeration degree.Besides,UAs are the main area with the most significant population agglomeration degree,and the spatial autocorrelation show that the cities with similar degree tend to be concentrated in space.The urban population gathering in UAs has a certain positive spillover effect on population size of neighboring cities.2)Economic development and social conditions factors are important factors affecting population agglomeration degree in UAs.The main factors of population gather into UAs are similar with the outside UAs,but the positive promotion of urbanization rate and proportion of tertiary industry in GDP on population agglomeration of UAs in China are enhancing from 2000 to 2020.Meanwhile,the other factors,such as high-quality public services,good urban living environment conditions,high-quality medical and educational resources,are also important factors to promote urban population gather into UAs.This study provides a basis for formulating the development planning of UAs in China,and enriches the relevant theoretical research of population evolution and influencing factors of UAs.

Assessing the dynamics of human activity intensity and its natural and socioeconomic determinants in Qinghai-Tibet Plateau

Investigating the spatiotemporal variation of human activity intensity and its determinants is a crucial basis for further revealing the mechanism of human-environment interaction and optimizing the human development mode.In this study,the human activity intensity on the Qinghai-Tibet Plateau(QTP)from 1990 to 2020 was measured based on the quantitative model of land use data and the actual regional background,and the under-lying natural and socioeconomic determinants were investigated using spatial econometric methods.The results demonstrate that(1)the human activity intensity in QTP has increased by 11.96%,and there are differences in different spatial scales;the areas with high human activity intensity are distributed in the Hehuang Valley where Xining City and its surrounding areas are located,as well as the One-River and Two-River Area where Lhasa City and surrounding areas are located.(2)Human activity intensity has significant positive spatial spillover,suggesting that local changes will cause changes in the same direction in adjacent areas.(3)The human activ-ity intensity in QTP is affected by various determinants.Concerning socioeconomic factors,the economic level has no significant impact on the human activity intensity in QTP,which differs from the general regional law.Both urbanization and traffic conditions have a significant positive effect,and the impact intensity continues to increase.Concerning natural factors,topographic relief has a significant positive effect;the impacts of temper-ature and vegetation coverage have changed from insignificant to a significant positive effect;the impacts of precipitation and river network density have not been verified;there is no linear relationship between altitude and human activity intensity in the entire QTP,while it exists in local regions.Finally,this study proposes three policy implications for the realization of a more harmonious human-environment relationship in QTP.

Spatiotemporal Dynamics of Green Total-factor Water-use Efficiency and Its Influencing Factors in China

In this study,we developed an evaluation index system for green total-factor water-use efficiency(GTFWUE)which reflected both economic and green efficiencies of water resource utilization.Then we measured the GTFWUE of 30 provinces/municipalities/autonomous regions(hereafter provinces)in China(not including Tibet,Hong Kong,Macao,Taiwan as no data)from 2000 to 2018 using a minimum distance to the strong frontier model that contained an undesirable output.We further analyzed the regional differences and spatial correlations of GTFWUE using these values based on Global and Local Moran’s I statistics,and empirically determined the factors affecting GTFWUE using a spatial econometric model.The evaluation results revealed that the GTFWUE differed substantially between the regions.The provinces with high and low GTFWUE values were located in the coastal and inland areas of China,respectively.The eastern region had a significantly higher GTFWUE than the central and western regions.The GTFWUEs for all three regions(eastern,central,and western regions)decreased slowly from 2000 to 2011(except 2005),remained stable from 2012 to 2016,and rapidly increased in 2017 before decreasing again in 2018.We found significant spatial correlations between the provincial GTFWUEs.The GTFWUE for most provinces belonged to the high-high or low-low cluster region,revealing a significant spatial clustering effect of provincial GTFWUEs.We also found that China’s GTFWUE was highly promoted by economic growth,population size,opening-up level,and urbanization level,and was evidently hindered by water endowment,technological progress,and government influence.However,the water-use structure had little impact on GTFWUE.This study fully demonstrated that the water use mode would be improved,and water resources needed to be used more efficiently and green in China.Moreover,based on the findings of this study,several policy recommendations were proposed from the aspects of cross-regional cooperation,economy,society,and institution.

Can Talent Policies Attract Population Inflows?—An Empirical Analysis Based on Spatial Panel Modeling

To analyze the spatial influence mechanism of talent policy on population flow, this study compares the government work reports of 31 provinces between 2008 and 2020, and quantifies regional talent policies in nine aspects, including talent evaluation and incentives, utilizing a comprehensive, standardized, and continuous approach. Additionally, this paper develops a spatial econometric analysis model and expands on the conventional neighborhood, distance, and economic matrices by constructing a spatial weight matrix that reflects talent flow. The findings indicate that population movement exhibits spatial clustering patterns. The regional government's talent policy, primarily based on talent evaluation and incentives, positively influences population inflow. Moreover, during the implementation of talent policies, local governments demonstrate cooperative relationships. The inter-regional spillover effect between talent evaluation and talent incentives is significantly positive. In other words, a stronger local talent evaluation policy, along with robust talent incentives, encourages population inflow from neighboring provinces. However, this conclusion may vary in different regions and over time. Recently, the spatial spillover effect of population inflow and the impact of talent policies have not shown significant results. Additionally, the attractiveness of talent evaluation in the eastern region surpasses that of talent incentives, while the opposite holds true for the central and western regions. This study investigates the impact of local government talent policies on population inflow and its spatial spillover effect, offering theoretical support for intergovernmental cooperation.

Contributions of Social-ecological Drivers to Land Use Transitions in Protected Areas on the Tibetan Plateau:Shifting from Strong Intervention to a New Balance

The establishment and management of protected areas(PAs)often involve modifying traditional land use rights and changing the production and living activities of locals,which can lead to changes in the factors that drive land use transitions.Our understanding of the spatiotemporal patterns of land use transition and the contributions of social-ecological drivers remains incomplete.In this study,we focused on the Yarlung Zangbu Grand Canyon National Park and examined how social-ecological factors influence land use transitions by developing a theoretical model of land use transitions within PAs.Our findings revealed that cropland,shrubland,grassland,and wetland experienced net losses in area,while forestland,water,ice/snow,barren land,and impervious land exhibited fluctuating growth patterns from 1985 to 2020.The net decrease in grassland was 157425.60 ha,while the net increase in forest was 140709.20 ha.The quality of land habitat increased from 0.5158 to 0.6656.Land use dominant and recessive transitions displayed varying spatial characteristics and scales across different time periods.In particular,the degree of influence of policy factors on land use dominant transition declined from 0.0800 in 1985-1990 to -0.0432 in 2010-2020,while its influence on land use recessive transition declined from 0.00058 in 1985-1990 to 0 in 2010-2020.The results show that social-ecological factors intricately influenced different types of land use transitions,leading to a shift from a balanced state to a new equilibrium.These results enhance our understanding of the spatiotemporal patterns and complex dynamics of land use transitions within PAs,providing insights and practical implications for effective land management in PAs by considering the land-human relationships.

Green development and economic resilience:Evidence from Chinese resource-based cities

Resource-based cities are currently facing challenges due to ecological pollution and an unbalanced industrial structure,which hinders sustainable economic growth.The focus on green development as a strategy for economic growth and environmental protection is becoming increasingly popular.This study employs a spatial econometric model to explore the effect of green development on economic resilience in Chinese resource-based cities from 2011 to 2019,revealing a positive correlation between green development and economic resilience.For each 1 unit increase in green development,economic resilience increases by an average of 0.512 units.Furthermore,the analysis of heterogeneity reveals differences in the factors influencing various resource-based cities.In addition,provincial green policies bolster economic resilience by encouraging green development.This research aids in comprehending the balance between the economy and the environment.

Has Transport Infrastructure Promoted Regional Economic Growth?——With an Analysis of the Spatial Spillover Effects of Transport Infrastructure

Taking full account of the synergistic effects of multidimensional factors on regional economic growth in China, this paper constructs a model of the spatial spillover effects of transport infrastructure on regional economic growth. Using provincial panel data from 1993 to 2009 and employing spatial econometric techniques, our empirical analysis comes to the following conclusions. （1） The total output elasticity of transport infrastructure for regional economic growth varies between 0.05 and 0.07, indicating its important role in such growth. （2） Transport infrastructure has very clear spatial spillover effects on regional economic growth; its role in regional economic growth will be overestimated if these are neglected. （3） For a specific region, transport infrastructure in other regions has mainly positive spillover effects on economic growth, but there is also evidence of negative spillover effects. （4） Among multidimensional factors contributing to regional economic growth, labor pluscapital stock from other parts of the public sector make the greatest contribution to regional economic growth in China, followed by the new economic growth factors and new economic geography.

Study of spatial patterns and spatial effects of energy eco-efficiency in China

Energy eco-efficiency is a concept integrating ecological and economic benefits arising from energy utilization and serves as a measure of efficiency in the energy-environment-economy system. Using the slacks-based measure （SBM） model considering undesirable output, this study first measures the energy eco-efficiency of provinces in China from 1997 to 2012. It then analyzes the spatial distribution and evolution of energy eco-efficiency from three aspects： scale, intensity, and grain of spatial patterns. Finally, it examines the spatial spillover effects and influencing factors of energy eco-efficiency in different provinces by means of a spatial econometric model. The following conclusions are drawn： （1） The overall energy ecofficiency is relatively low in China, with energy-inefficient regions accounting for about 40%. Guangdong, Hainan and Fujian provinces enjoy the highest energy eco-efficiency, while Ningxia, Gansu, Qinghai, and Xinjiang are repre- sentative regions with low efficiency. Thus, the pattern of evolution of China＇s overall energy eco-efficiency is U-shaped. Among local regions, four main patterns of evolution are found： increasing, fluctuating, mutating, and leveling. （2） At the provincial level, China＇s energy eco-efficiency features significant spatial agglomeration both globally and locally. High-high agglomeration occurs mainly in the eastern and southern coastal regions and low-low agglomeration in the northwestern region and the middle reaches of the Yellow River. Changes in spatial patterns have occurred mainly in areas with high-low and low-high agglomeration, with the most remarkable change taking place in the Beijing-Tianjin-Hebei region. （3） There exist significant spatial effects of energy eco-efficiency among provinces in China. For the energy eco-efficiency of a given region spatial spillovers from adjacent regions outweigh the influence of errors in adjacent regions. Industrial structure has the greatest influence on energy eco-efficiency.

Quantitative measuring and influencing mechanism of urban and rural land intensive use in ChinaQuantitative measuring and influencing mechanism of urban and rural land intensive use in China

Land use issue is an important constraining force to limit economic sustainable development of China. Urban and rural rapid expansion depletes valued land resources under the background of rapid urbanization. An extensive use pattern might cause a serious waste of land resources. The study on influencing mechanism of land intensive use （LIU） in China at the county level is a key tool for effective LIU practice and policy-making. This paper uses OLS model, Spatial Panel Lagged model and Spatial Panel Error model to quantitatively analyze the influencing mechanisms of five class factors and 17 variables supported by GIS （Geographic Information System） and MATLAB. And a comprehensive data set was devel- oped including physical geography and socio-economic information of 2286 counties. Meanwhile, the spatiotemporal pattern of LIU has discussed by means of GIS. The results show that Spatial Panel Data models are slightly superior to OLS model in terms of signifi- cance and confidence level. Regression results of these models indicate that industrialization, urbanization, economic development level, location, transportation and policy have significant impact on LIU of counties. The variables of physical geography are less significant than socio-economic variables. An ignored variable of historical factor, however, became the best significant factor. In the future, the LIU at the county level should take advantage of the new situation by enhancing favorable factors and reducing disadvantageous ones, which can be acquired by improving the entire level and quality of industrialization and urbanization. We argued that an efficient and complete land market and operating system should be built to reflect market-oriented activities at the first place, then, differential LIU regulation policies and measurements should be optimized according to regional differences. In the meantime, we should pay close attention to the carrying capacity of local resources and environments when conducting LIU practices.