Do companies influenced by smart cities pay more attention to green governance?Mechanism and optimal spatial correlation

Smart cities are a way for China to construct an innovative and environmentally conscious nation.The paper examines the impact of smart cities on corporate green governance and provides a theoretical foundation for formulating and executing smart city policy in China.Based on panel data from Chinese A-share listed companies in Shanghai and Shenzhen from 2008 to 2020,this study constructs a multiperiod double-difference model to examine the influence of smart cities on corporate green governance.Additionally,it uses a spatial double-difference model to investigate the spatial spillover effect of smart cities on neighboring areas.The findings indicate that smart cities effectively enhance corporate green governance.Analyzing the influencing mechanisms reveals that resource allocation efficiency,technological innovation,management environmental awareness,and regional environmental enforcement efforts act as mediators.Furthermore,the study reveals that the impact of smart cities on promoting corporate green governance is more pronounced in regions with lower levels of marketization and resource-based cities.Moreover,the research explores the spatial spillover effects of smart cities,with an effective radius of approximately 350 km.The optimal spatial correlation zone for green governance of businesses in neighboring areas in relation to smart cities is within a range of 250-350 km.This is manifested by the significant promotion of green governance in neighboring area businesses facilitated by smart cities.

Structural Characteristics and Influencing Factors of Carbon Emission Spatial Association Network:A Case Study of Yangtze River Delta City Cluster,China

City cluster is an effective platform for encouraging regionally coordinated development.Coordinated reduction of carbon emissions within city cluster via the spatial association network between cities can help coordinate the regional carbon emission management,realize sustainable development,and assist China in achieving the carbon peaking and carbon neutrality goals.This paper applies the improved gravity model and social network analysis(SNA)to the study of spatial correlation of carbon emissions in city clusters and analyzes the structural characteristics of the spatial correlation network of carbon emissions in the Yangtze River Delta(YRD)city cluster in China and its influencing factors.The results demonstrate that:1)the spatial association of carbon emissions in the YRD city cluster exhibits a typical and complex multi-threaded network structure.The network association number and density show an upward trend,indicating closer spatial association between cities,but their values remain generally low.Meanwhile,the network hierarchy and network efficiency show a downward trend but remain high.2)The spatial association network of carbon emissions in the YRD city cluster shows an obvious‘core-edge’distribution pattern.The network is centered around Shanghai,Suzhou and Wuxi,all of which play the role of‘bridges’,while cities such as Zhoushan,Ma'anshan,Tongling and other cities characterized by the remote location,single transportation mode or lower economic level are positioned at the edge of the network.3)Geographic proximity,varying levels of economic development,different industrial structures,degrees of urbanization,levels of technological innovation,energy intensities and environmental regulation are important influencing factors on the spatial association of within the YRD city cluster.Finally,policy implications are provided from four aspects:government macro-control and market mechanism guidance,structural characteristics of the‘core-edge’network,reconfiguration and optimization of the spatial layout of the YRD city cluster,and the application of advanced technologies.

Spatial pattern analysis and associations of different growth stages of populations of Abies georgei var.smithii in Southeast Tibet,China

Abies georgei var.smithii is an important plant species in Southeast Tibet,China.It has high ecological value in terms of biodiversity protection,as well as soil and water conservation.We analyzed the spatial pattern and associations of A.georgei var.smithii populations at different growth stages by using Ripley's L function for point pattern analysis.The diameter structure was a nearly reverse 'J' shape.The amount of saplings and medium-sized trees accounts for a large part of the entire population,suggesting a high regeneration rate and an expanding population.In the transition from saplings to medium trees or to large trees,saplings show a significant aggregation distribution at small scales,while medium trees and large trees show a random distribution.There are significant inverse associations between saplings and medium trees and large trees at small scales,while there are no obvious associations between medium trees and large trees.The natural regeneration was affected by interspecific competition,and it was also affected by intraspecific competition.The joint effects of biological characteristics and environmental factors contribute to the spatial distribution pattern and associations of this A.georgei var.sm ithii population.

Structural characteristics and influencing factors of spatial correlation network for regional high-quality development in China

On the basis of measuring the regional high-quality development in China from 2011 to 2020,this study uses gravity model to build spatial correlation network,and uses social network analysis method to analyze the structural characteristics and influencing factors of correlation network.The results are shown as follows.First,from 2011 to 2020,the level of regional high-quality development in China is rising gradually,and the discrete characteristics between regions are gradually obvious,showing a step-like distribution structure decreasing from east to west.Second,the network density of regional high-quality development is generally low and tends to decline,but it has strong stability and correlation strength.Third,the spatial correlation network has an obvious core-edge structure.Shanghai is always at the center of the network and plays a significant intermediary role,while Qinghai and Xinjiang are always at the edge of the network.Fourth,the regional high-quality development association network can be divided into four major sectors:main benefit,net benefit,net spillover,and broker,showing the spatial correlation characteristics of inter-plate contact and intra-plate agglomeration.Fifth,the level of economic development,the level of urbanization and geographical proximity have a significant impact on the formation of regional high-quality development correlation network.

Industrial Carbon Emission Distribution and Regional Joint Emission Reduction:A Case Study of Cities in the Pearl River Basin,China

China’s low-carbon development path will make significant contributions to achieving global sustainable development goals.Due to the diverse natural and economic conditions across different regions in China,there exists an imbalance in the distribution of car-bon emissions.Therefore,regional cooperation serves as an effective means to attain low-carbon development.This study examined the pattern of carbon emissions and proposed a potential joint emission reduction strategy by utilizing the industrial carbon emission intens-ity(ICEI)as a crucial factor.We utilized social network analysis and Local Indicators of Spatial Association(LISA)space-time trans-ition matrix to investigate the spatiotemporal connections and discrepancies of ICEI in the cities of the Pearl River Basin(PRB),China from 2010 to 2020.The primary drivers of the ICEI were determined through geographical detectors and multi-scale geographically weighted regression.The results were as follows:1)the overall ICEI in the Pearl River Basin is showing a downward trend,and there is a significant spatial imbalance.2)There are numerous network connections between cities regarding the ICEI,but the network structure is relatively fragile and unstable.3)Economically developed cities such as Guangzhou,Foshan,and Dongguan are in the center of the network while playing an intermediary role.4)Energy consumption,industrialization,per capita GDP,urbanization,science and techno-logy,and productivity are found to be the most influential variables in the spatial differentiation of ICEI,and their combination in-creased the explanatory power of the geographic variation of ICEI.Finally,through the analysis of differences and connections in urban carbon emissions under different economic levels and ICEI,the study suggests joint carbon reduction strategies,which are centered on carbon transfer,financial support,and technological assistance among cities.

Spatial distribution patterns of Symplocos congeners in a subtropical evergreen broad-leaf forest of southern China

Studies on spatial distribution of congeneric species can supplement our understanding of species ecological processes. We analyzed population structure, spatial distribution, intra-and interspecific associations among six Symplocos tree species on a large(50 ha) plot in a subtropical, evergreen broad-leaf forest in southern China using spatial point pattern analysis methods. Our results suggested that the six Symplocos tree species were all clustered at small scales. The aggregation intensity of S. wikstroemiifolia with low abundance but relatively numerous large-diameter trees was much higher than that of the other five Symplocos species that occurred at high abundance but included few large-diameter trees. Spatial associations among the six congeners showed that 12 of 30 pairs were associated positively at small scales, and 13 of 30 pairs were unrelated. For species among different size classes, 79 of 120 pairs were not correlated, and 17 of 120 pairs were associated positively. These results showed insufficient evidence for interspecific competition and congeneric Symplocos species commonly coexist within subtropical plant communities. The spatial patterns of Symplocos species and their correlations changed with size(DBH) class and were simultaneously affected by spatial scales; the intensity of their aggregation and association decreased with increasing area of the sample plot.

Geographical Accessibility to Basic Infrastructures and Services in Rural Senegal: The Case of the Niakhar Area

Access to basic infrastructure and services is a factor in economic development and an important aspect in combatting social and spatial disparities. But this access is often subject to several constraints, including geographical accessibility. In this article, we aim to analyze the geographical accessibility to basic infrastructure and services in the Niakhar area, using the improved two step floating catchment area method and local spatial association indicators. The results reveal that the areas with high accessibility to health and education infrastructures and services are mainly located along the south-east and north-west gradient, while those with low accessibility are found in the south-west and north-east center. They also show high accessibility to trade services in the center of the study area.

Application of Integration of Spatial Statistical Analysis with GIS to Regional Economic Analysis

This paper summarizes a few spatial statistical analysis methods for to measuring spatial autocorrelation and spatial association, discusses the criteria for the identification of spatial association by the use of global Moran Coefficient, Local Moran and Local Geary. Furthermore, a user-friendly statistical module, combining spatial statistical analysis methods with GIS visual techniques, is developed in Arcview using Avenue. An example is also given to show the usefulness of this module in identifying and quantifying the underlying spatial association patterns between economic units.

Distribution Patterns and Associations of Dominant Tree Species in a Mixed Coniferous-Broadleaf Forest in the Changbai Mountains

In 2012 a plot was established with 1-ha area in a mixed coniferous-broadleaf forest in the Changbai Mountains, northeastern China for examining local forest processes, structure and succession. A method of O-ring statistics （pair- correlation function） was applied to analyze the spatial patterns and associations of the dominant species within different vertical layers. After the evaluation by their importance values, six tree species （or group） （i.e. Abies nephrolepis, Picea jezoensis, Pinus koraiensis, Tilia amurensis, and species group of Betula ssp. and species group of Acer ssp.） were determined as dominant trees species. It was found that some of these species exhibited closely clustered distributions at fine distances. As spatial distance increased, a random or even regular distribution gradually appeared with the exception of the upper layers of A. nephrolepis and P. koraiensis, and the lower layers of P. jezoensis, P. koraiensis and Betula ssp., which were substantially randomly distributed. Intra- and inter-species spatial associations varied in accordance with species, tree height and reciprocal distances. Positive associations were observed between the lower and upper height classes of trees of the same species （except for that of P. jezoensis） at fine distances. This may be owing to limited seed dispersal and geological heterogeneity. The aggregation intensity declines with increasing distances and this consistent with the predictions of self-thinning. Some coniferous trees （e.g. Pinus koraiensis） in the lower height class were positively associated with T. amurensis and group of Betula ssp. of the upper height class at some distances, suggesting that saplings of coniferous trees occupy a broader niche and can grow well under the canopy of the adult of broad-leaved trees. Negative associations were observed between upper coniferous trees and lower broad-leaved trees and between upper P. jezoensis and lower P. koraiensis, suggesting that a canopy of these trees might not provide suitable environment for the survival, establishment, and growth of o lower individuals, corresponding well to Janzen-Connell hypothesis.

Mining multilevel spatial association rules with cloud models

The traditional generalization-based knowledge discovery method is introduced. A new kind of multilevel spatial association of the rules mining method based on the cloud model is presented. The cloud model integrates the vague and random use of linguistic terms in a unified way. With these models, spatial and nonspatial attribute values are well generalized at multiple levels, allowing discovery of strong spatial association rules. Combining the cloud model based method with Apriori algorithms for mining association rules from a spatial database shows benefits in being effective and flexible.

Spatial patterns of interprovincial mountain geographical names in China and implications for regional governance

Suffering from fragile environment, poor accessibility and infrastructure, as well as social,political and economic marginality, the interprovincial mountain geographical entities are difficult areas for the regional governance in China.By analyzing the spatial patterns and the influencing factors of the interprovincial mountain geographical names(IMGNs), the goal of this research is to clarify the geographical features of IMGNs and offer alternatives for the management of interprovincial mountain regions in China. The spatial visualization,the analysis of spatial agglomeration and the influencing factors of IMGNs were all implemented under a geographical information system. Results showed that there were 6869 IMGNs in China according to the database of "China's Second National Survey of Geographical Names(2014-2018)",including 4209 mountain geographical names, 1684 mountain peak geographical names and 976 the other mountain geographical names. Hunan Province had the largest number of names while Shanghai had the smallest number of names. In addition, the spatial variance of the mountain peak names and the mountain names were larger than that of the other mountain geographical names, and the IMGNs showed a significant clustering phenomenon in the southern part of China. The relative elevation and the population had an impact on the distribution of the IMGNs. The largest number of the names occurred where the relative elevation was between 1000-2000 m and where the population was between 40-50 million. Density of unnamed interprovincial mountain geographical entities declined from west to east in China. The analysis of generic names of different types of IMGNs implied that the naming of IMGNs is inconsistent. Based on these analyses, it is suggested that the government should take the IMGNs as management units, strengthen the naming of unnamed interprovincial mountain geographical entities, standardize the generic names of IMGNs and identify areas of poverty based on the survey of IMGNs.

Effects of microtopography on spatial point pattern of forest stands on the semi-arid Loess Plateau,China

Microtopography may affect the distribution of forests through its effect on rain redistribution and soil water distribution on the semi-arid Loess Plateau,China.In this study,we investigated the characteristics of microtopography on two shady slopes（slope A,5 hm2,uniform slope;slope B,5 hm2,microtopography slope） and surveyed the height,the diameter at breast height and the location（x,y coordinates） of all selected individual trees（Robinia pseudoacacia Linn.,Pyrus betulifolia Bunge,Populus hopeiensis Hu ＆ Chow,Armeniaca sibirica Lam.,Populus simonii Carr.and Ulmus pumila Linn.） on slope A and slope B in the watersheds of Wuqi county,Shaanxi province.Subsequently,the effects of microtopography on the spatial pattern of forest stands were analyzed using Ripley＇s K（r） function.The results showed that：（1） The maximal aggregation radiuses of the tree species on the uniform slope（slope A） were larger than 40 m,whereas those of the tree species on the microtopography slope（slope B） were smaller than 30 m.（2） On slope B,the spatial association of R.pseudoacacia with P.betulifolia,A.sibirica,P.simonii and U.pumila varied from being strongly negative to positive at microtopography scales.The spatial association of Populus hopeiensis Hu ＆ Chow with U.pumila also varied from being strongly negative to positive at microtopography scales.However,there was no spatial association between P.betulifolia and P.hopeiensis,P.betulifolia and A.sibirica,P.betulifolia and P.simonii,P.betulifolia and U.pumila,P.hopeiensis and A.sibirica,P.hopeiensis and P.simonii,A.sibirica and P.simonii,A.sibirica and U.pumila,and P.simonii and U.pumila.On slope A,the spatial association between tree species were strongly negative.The results suggest that microtopography may shape tree distribution patterns on the semi-arid Loess Plateau.

A New Method Based on Association Rules Mining and Geo-filter for Mining Spatial Association Knowledge

Association rule mining methods, as a set of important data mining tools, could be used for mining spatial association rules of spatial data. However, applications of these methods are limited for mining results containing large number of redundant rules. In this paper, a new method named Geo-Filtered Association Rules Mining(GFARM) is proposed to effectively eliminate the redundant rules. An application of GFARM is performed as a case study in which association rules are discovered between building land distribution and potential driving factors in Wuhan, China from 1995 to 2015. Ten sets of regular sampling grids with different sizes are used for detecting the influence of multi-scales on GFARM. Results show that the proposed method can filter 50%–70% of redundant rules. GFARM is also successful in discovering spatial association pattern between building land distribution and driving factors.

Spatial patterns and storage composition of woody debris in a natural secondary forest dominated by Pinus tabulaeformis on Loess Plateau, China

Woody debris(WD) is an important par of natural Pinus tabulaeformis mixed stands, and i affects the forest ecosystem stability and developmen The WD spatial patterns are especially importan structural characteristics that can provide insights into forest dynamics. In this paper, the WD storage WD spatial patterns and WD associations among the main species were examined in the natural secondary forest on Loess Plateau in northwest China. Data were collected in a 1 ha(100 m × 100 m) permanent plot and all the trees with a diameter at breast height o more than 3 cm were measured and stem-mapped Ripley's K functions from the spatial-point-pattern analysis method were used to analyze the spatia distribution and associations. The results showed tha(1) The total storage of WD was 10.73 t/ha, fallen wood was the main source of WD, and the majority diameters were greater than 20 cm, and in intermediate levels of decay;(2) The overall spatia pattern was closely related to the spatial scale, which exhibited an aggregated pattern on a small scale, and a random pattern on a large scale. The spatia patterns of coarse woody debris also gradually transitioned from an aggregated pattern in fine scales to a random pattern in broader spatial scales, which matched the overall spatial pattern. The spatial intensity was gradually decreased with the increasing diameters, and increased with the decomposition classes;(3) The WD of Pinus tabulaeformis species was negatively associated with Betula platyphylla and Populus davidiana on a small scale but positively associated with these species on a large scale. The spatial pattern and interspecies relations were the results of long-term interactions between the natural secondary forest community and the surrounding natural environment. These findings would provide a scientific basis for the sustainable management and protection of natural secondary forest ecosystems on Loess Plateau.

Epidemiological features of seasonal influenza transmission among 11 climate zones in Chinese mainland

Background Previous studies provided some evidence of meteorological factors influence seasonal influenza transmission patterns varying across regions and latitudes. However, research on seasonal influenza activities based on climate zones are still in lack. This study aims to utilize the ecological-based Koppen Geiger climate zones classification system to compare the spatial and temporal epidemiological characteristics of seasonal influenza in Chinese mainland and assess the feasibility of developing an early warning system.Methods Weekly influenza cases number from 2014 to 2019 at the county and city level were sourced from China National Notifiable Infectious Disease Report Information System. Epidemic temporal indices, time series seasonality decomposition, spatial modelling theories including Moran’s/ and local indicators of spatial association were applied to identify the spatial and temporal patterns of influenza transmission.Results All climate zones had peaks in Winter-Spring season. Arid, desert, cold (BWk) showed up the first peak. Only Tropical, savannah (Aw) and Temperate, dry winter with hot summer (Cwa) zones had unique summer peak. Temperate, no dry season and hot summer (Cfa) zone had highest average incidence rate (IR) at 1.047/100,000. The Global Moran’s/ showed that average IR had significant clustered trend (z = 53.69,P < 0.001), with local Moran’s/ identified high-high cluster in Cfa and Cwa. IR differed among three age groups between climate zones (0-14 years old:F = 26.80,P < 0.001;15-64 years old:F = 25.04,P < 0.001;Above 65 years old:F = 5.27,P < 0.001). Age group 0-14 years had highest average IR in Cwa and Cfa (IR= 6.23 and 6.21) with unique dual peaks in winter and spring season showed by seasonality decomposition.Conclusions Seasonal influenza exhibited distinct spatial and temporal patterns in different climate zones. Seasonal influenza primarily emerged in BWk, subsequently in Cfa and Cwa. Cfa, Cwa and BSk pose high risk for seasonal influenza epidemics. The research finds will provide scientific evidence for developing seasonal influenza early warning system based on climate zones.

Spatial distribution and influencing factors of interprovincial terrestrial physical geographical names in China

The interprovincial terrestrial physical geographical entities are the key areas of regional integrated management. In this paper, we analyzed the spatial patterns of the interprovincial terrestrial physical geographical names(ITPGN) from three aspects: numerical features, spatial variance and spatial agglomeration. The influencing factors of the distribution of ITPGN and the implications for the regional management were further discussed. GIS technology was used to visualize the distribution of ITPGN, analyze the spatial agglomeration and the influencing factors of ITPGN. A total of 11,325 ITPGN, including 4243 water ITPGN and 7082 terrain ITPGN, were extracted from the database of "China's Second National Survey of Geographical Names(2014–2018)", and the mountain geographical names were the largest type in ITPGN. Hunan Province had the largest number of the names in China, and Shanghai had the smallest number of the names. The spatial variance of the terrain ITPGN was larger than that of the water ITPGN, and the ITPGN showed a significant agglomeration phenomenon in the southern part of China. In addition, the relative elevation and the population had an impact on the distribution of the ITPGN. The largest number of the geographical names occurred in the regions where the relative elevation was between 1000–2000 meters, and where the population was between 40–50 million. Based on the analysis, it was suggested that the government should take the ITPGN as management units, optimize management strategies based on the characteristics of different types of ITPGN, strengthen the naming of unnamed interprovincial terrestrial physical geographical entities and balance the interests in the controversial ITPGN. This study demonstrated that GIS and spatial analysis techniques were useful for the research of ITPGN and the results could provide targeted management suggestions to realize coordinated development in the interprovincial regions.

Spatial patterns of a savanna palm tree Borassus aethiopum and its temporal variability

The spatial distributions and associations of plant species in a stand can provide essential information about their dynamics.However,since tree spatial distribution and association depend on factors that operate at different scales,disentangling the effects of environmental heterogeneity and plant-plant interactions requires the choice of a suitable null model for spatial analysis.We analyzed the spatial distributions of the same savanna palm tree populations that were studied,the underlying hypothesis being that these distributions have changed in 20 years.To remove the effect of large-scale environmental heterogeneity,the inhomogeneous L-function under the heterogeneous Poisson null model was used.We showed:(i)unlike 20 years ago,adults had a regular distribution instead of an aggregated distribution in the grass savanna;(i)although the spatial distribution of seedlings and juveniles was always aggregated,we observed a decrease in the size of the aggregates(intensities);ili)except for juveniles,no other stages were associated with nutrient-rich patches,which was also different 20 years ago;(iv)we did not observe any particular difference in structure between two study sites,only that female palm trees were spatially associated with entire-leafed seedlings in the reserve while they were spatially independent in the rural area.Our study supports the hypothesis that the spatial distributions have partially changed,and that the management of spatial heterogeneity has improved and given more precision in the results.

Interspecific association of sika deer in terrestrial animal communities of Liancheng National Nature Reserve, China

The prevention and control of invasive of alien species is an important work for nature reserves.This study analyzes the development trend of the alien species sika deer in Liancheng National Nature Reserve.From October 2019 to June 2020,3523 valid photos and videos of terrestrial animals were acquired from 130 camera traps,and sika deer were recorded in 21 photos from 13 traps.The survival of the sika deer population was investigated by means of morphological identification,population structure analysis,species relative abundance indices,and species spatial association analysis.A total of 13 sika deer individuals were identified by camera trapping,including two kids and three subadults representing the reproductive capacity of the population.Spatially,sika deer is not associated with any local species and was outside the spatial association network of terrestrial animals in Liancheng National Nature Reserve,indicating that the sika deer population has not been integrated into the local community and has failed to perform its ecological function.It is worth noting that the reserve provides habitat suitable for sika deer and that the population has adequate reproductive capacity.Due to the lack of large apex predators in the reserve,the population size of ungulates such as sika deer,red deer,and Siberian roe deer may expand and lead to population outbreaks and the associated problems for the ecosystem.To restore large-and medium-sized carnivores and avoid the population outbreak of the species,the present challenges require immediate attention in Liancheng National Nature Reserve.

Distribution patterns of tree species in an evergreen broadleaved forest in eastern China

Ecological assembly rules in evergreen broad-leaved forest are far from clear understanding.Spatial dispersion of individuals in a species is central in ecological theory.We analyzed the spatial patterns as well as associations between adult and juvenile of each tree species in a 5-ha subtropical evergreen broad-leaved forest plot in eastern China.Out of the 74 species occurring with more than 10 individuals,88.4%of these species are aggregated.Most of them are aggregated from small to large scales.Spatial distributions of some species corre-spond with topography.Many bad dispersed species in the Baishanzu exhibit a highly aggregated distribution at small scales.These suggest that environmental heterogeneity and/or dispersal limitation may be the most important mechanisms that control the distribution patterns of these species.Our observations of the aggregations of abundant species basically support the hypothesis that dispersal limitation decreases as the number of reproductive trees increases.The rest species are randomly distributed,with less than 10 individuals.For most common species,spatial aggregation is weaker in larger diameter classes,and the distance between adults is larger than that between juveniles and adults,suggesting that density-dependence works on loosing aggregation and excluding conspecific juveniles away from adult trees.However,the density-dependent effect is not strong enough to eliminate all seedlings near adult trees and to result in a regular distribution of trees;thus the density dependence is usually masked by the refuge effect.