Standard Deviational Ellipse Research Articles

The Impact of New Urbanization on Water Ecological Civilization: Based on the Empirical Analysis of Prefecture-Level Cities in Jiangxi, China

This study aims to improve the level of water ecological civilization (WEC) in the urbanization process based on the data of prefecture-level cities in Jiangxi, China, from 2011 to 2020. This paper applies spatial analysis methods such as the natural fracture method, barycenter transfer model, and standard deviation ellipse method to explore the spatiotemporal evolution characteristics of WEC and the impact of new urbanization (NU) on WEC. The NU pilot construction is further regarded as an exogenous impact, and the “net effect” of the NU pilot policy on WEC is tested. The results showed that (1) the spatial distribution pattern of the east–west polarization of WEC was broken, and a spatial distribution pattern of strong in the north and weak in the south was gradually formed. (2) NU contributes to improving the WEC level, among which population, digital, and green urbanization can significantly promote the WEC level, while economic urbanization impedes the improvement of the WEC. This conclusion is still valid following a series of robustness tests. (3) heterogeneity analysis showed that the impact of NU in improving the level of WEC is more evident in cities with scarce water resources, non-resource-based cities, and non-old industrial base cities after the implementation of NU planning. (4) NU’s pilot policy can help improve the WEC level in the region and the WEC level in neighboring regions through the spillover effect of policy. Therefore, it is necessary to make use of the superimposed effect of multidimensional urbanization based on urban characteristics, implement differentiated policy, break administrative barriers, make use of the spatial spillover effect of pilot policy, and improve the WEC level.

Temporal and Spatial Evolution of Public–Private Partnership (PPP) Project Risks in China: 2003–2019

The implementation of public–private partnership (PPP) is perturbed by multiple factors, and it is difficult for the Chinese government to fully control the risks of PPP projects. Based on the DPSIR model, this study constructed the PPP projects risk evaluation index system by using the TOPSIS method. Then the spatial variation, standard deviation ellipse, and gray dynamic model were used to analyze the spatial–temporal dynamic evolution characteristics of the risk level of PPP projects from 2003 to 2019 and to make reasonable predictions of the future spatial distribution pattern. This study yielded the following five results: (1) the average risk level of China’s PPP projects is 0.722, with a decreasing trend of fluctuation and relatively stable risk; (2) high-risk provinces for PPP projects decrease, medium-risk provinces increase; (3) the spatial variability of risk is increasing, and the spatial differentiation is significant, showing a spatial evolution pattern of “west > central > east,” but areas with low-risk values are clearly migrating to the east; (4) the spatial distribution pattern of risk has a north-easterly orientation, with a “north-west to north-east” trend in the path of movement; (5) There are differences in the spatial distribution patterns in the east–west and north–south directions, and the spatial spillover effect is not obvious. Based on the above results, the risk center of China’s PPP projects will be shifted to the northeast in 2025–2035. Our study captures the evolution of PPP project risks in China in both temporal and spatial dimensions, which can provide lessons for optimizing global PPP project risk management.

Spatiotemporal evolution and driving factors of tourism ecological adaptation in the Dongting Lake Area, China

Tourism ecological adaptation (TEA) offers a novel research framework and practical tool for analyzing sustainable regional development. This facilitates high-quality tourism development, safeguards the ecosystem, and enhances risk resilience. However, existing TEA research has shortcomings regarding methodology and research scales. This study constructed a TEA index system to address these deficiencies. The index system comprises two subsystems, tourism industry adaptation (TIA) and ecological environment adaptation (EEA), including three dimensions: sensitivity, stability, and response. The entropy-weighted TOPSIS method, adaptation assessment model, standard deviation ellipse, and geographic detector were used to analyze the spatiotemporal evolution and driving factors of TEA in the Dongting Lake area, China, from 2012 to 2021. The TIA index displays a rise-fall-rise pattern, whereas the EEA index demonstrates a fluctuating upward trend. Additionally, the TEA index exhibits a distinctive basin-type spatial distribution pattern, with lower values in the central region and higher values in the surrounding areas. Over the past decade, standard deviation ellipses of adaptability have shown minimal changes in shape, position, and center. Both the clustering and center positions reached a state of basic equilibrium. The predominant TEA type was characterized by low adaptation, including 41.18% of the counties. The spatiotemporal evolution of TEA is driven by tourism resource endowment, government regulatory efforts, level of economic development, and environmental governance capacity

Balancing low-carbon and eco-friendly development: coordinated development strategy for land use carbon emission efficiency and land ecological security.

Correctly identifying and handling the relationship between land use carbon emission efficiency (LUCEE) and land ecological security (LES) are important to promote carbon neutrality in the overall layout of ecological civilization construction. This study takes 30 provinces in China as the research unit and measures the level of LUCEE and LES in each province in the period from 2011 to 2020 via a super-efficient slack-based measure model considering undesirable output. The coupling coordination degree (CCD) of LUCEE and LES is calculated, and its spatiotemporal evolution pattern is explored by kernel density estimation and standard deviational ellipse (SDE). The Dagum Gini coefficient is used to study spatial regional differences and the sources of differences. Results show that (1) China's LUCEE exhibited a downward and then an upward trend, as well as a spatial pattern of "high in the west and low in the east" with obvious regional differences. The LES experienced a positive transformation of "less secure → basically secure → more secure" nationwide, with no apparent regional differences. (2) The kernel density curves showed a continuous increase in CCD in general, while interprovincial differences increased, then decreased, and shifted from multipolar to bipolar differentiation. (3) The migration of SDE centers in CCD demonstrated a path of "southeast → southwest → northeast," and the ellipticity increased from 0.167 to 0.173, showing a trend of concentrated distribution. (4) The overall Gini coefficient of the national CCD indicated a decreasing trend, but imbalances remained, with the largest annual average value in the western region (0.120) and the smallest in the northeast (0.044). The main source of regional disparity was the intensity of transvariation. Accordingly, this study proposes targeted regional development strategies to promote low-carbon sustainable land use and improve the ability of land ecosystems to prevent security risks.

Dynamic evolution and spatial difference of public health service supply in economically developed provinces of China: typical evidence from Guangdong Province

ObjectiveThe outbreak of the COVID-19 pandemic has drawn attention from all sectors of society to the level of public health services. This study aims to investigate the level of public health service supply in the four major regions of Guangdong Province, providing a basis for optimizing health resource allocation.MethodsThis article uses the entropy method and panel data of 21 prefecture-level cities in Guangdong Province from 2005 to 2021 to construct the evaluation index system of public health service supply and calculate its supply index. On this basis, the standard deviation ellipse method, kernel density estimation, and Markov chain are used to analyze the spatiotemporal evolution trend of the public health service supply level in Guangdong Province. The Dagum Gini coefficient and panel regression model are further used to analyze the relative differences and the key influencing factors of difference formation. Finally, the threshold effect model is used to explore the action mechanism of the key factors.ResultsOverall, the level of public health service supply in Guangdong Province is on an upward trend. Among them, polarization and gradient effects are observed in the Pearl River Delta and Eastern Guangdong regions; the balance of public health service supply in Western Guangdong and Northern Mountainous areas has improved. During the observation period, the level of public health services in Guangdong Province shifted towards a higher level with a smaller probability of leapfrogging transition, and regions with a high level of supply demonstrated a positive spillover effect. The overall difference, intra-regional difference and inter-regional difference in the level of public health service supply in Guangdong Province during the observation period showed different evolutionary trends, and spatial differences still exist. These differences are more significantly positively affected by factors such as the level of regional economic development, the degree of fiscal decentralization, and the urbanization rate. Under different economic development threshold values, the degree of fiscal decentralization and urbanization rate both have a double threshold effect on the role of public health service supply level.ConclusionThe overall level of public health service supply in Guangdong Province has improved, but spatial differences still exist. Key factors influencing these differences include the level of regional economic development, the degree of fiscal decentralization, and the urbanization rate, all of which exhibit threshold effects. It is suggested that, in view of the actual situation of each region, efforts should be made to build and maintain their own advantages, enhance the spatial linkage of public health service supply, and consider the threshold effects of key factors in order to optimize the allocation of health resources.

Spatiotemporal Distribution and Fragmentation Driving Mechanism in Paddy Fields and Dryland of Urban Agglomeration in the Middle Reaches of the Yangtze River

The spatial-temporal distribution pattern of China’s cultivated land has changed dramatically from 1990 to 2020, and the problem of cultivated land fragmentation has become more prominent. However, the existing research lacks a focus on the two specific land use types, paddy fields and dryland. In this study, the spatiotemporal distribution pattern and the fragmentation driving mechanism of paddy field and dryland during the years 1990 to 2020 were identified by using the center of gravity center migration model, standard deviation ellipse, and land-use dynamic model for the urban agglomeration in the middle reaches of the Yangtze River as an example. The results show that there are significant differences in the spatiotemporal distribution characteristics of paddy field and dryland in the MRYRUA. Among the provinces and cities, Hubei province and its Xiangyang city showed the most obvious trend of change. The loss and gain of paddy fields and dryland is related to economic and policy contexts in each period. The main driving factor of paddy field and dryland fragmentation is natural condition, whereas a relatively important factor is the per capita disposable income of rural residents. The effects of each factor on paddy field and dryland fragmentation were not independent; any two factor interactions had a stronger effect on paddy field and dryland fragmentation than a single factor. In general, this study provides guidance and references for the main grain-producing areas undergoing rapid urbanization relating to cultivated land conservation, food security, and sustainable agricultural utilization.

Research on the fine-scale spatial-temporal evolution characteristics of carbon emissions based on nighttime light data: A case study of Xi'an city

Carbon emissions have resulted in severe ecological damage, jeopardizing the very existence of humanity. In China, carbon emissions from urban areas contribute to 80% of the total carbon emissions, this significant contribution underscores the importance of addressing urban emissions. To gain insights into the spatial patterns of carbon emissions in urban areas at the fine-scale regional level, this study utilizes Xi'an as a case study, constructs a fine-scale regional carbon emission estimation model based on energy consumption and NPP-VIIRS-like NTL data, and quantifies multiscale carbon emissions from 2000 to 2021. Furthermore, global spatial autocorrelation, cold and hot spot analysis, and standard deviation ellipse analysis were used to investigate the spatial characteristics of carbon emissions at the street (township) level in Xi'an. This study revealed a sixfold increase in carbon emissions in Xi'an, rising from 51.35 million tons in 2000 to 281.95 million tons in 2021.The area affected by carbon emissions has expanded, with the centre of gravity of emission consistently shifting towards the south. The average street-level carbon emission density fluctuated and doubled compared to that in 2000. The total number of streets with low-carbon-emission-density decreased by 23%, indicating a shift away from low-carbon-emission-density streets. Furthermore, the global Moran's I index consistently remained within the range of 0.85–0.95, indicating significant spatial clustering, with cold spots expanding into surrounding districts and counties. Additionally, this study accurately identified carbon emissions within the city, offering the potential for the development of more precise carbon reduction strategies. Moreover, this approach can provide valuable support for the dynamic monitoring of carbon emissions in developing cities worldwide.

Geospatial Analysis of Artisanal Refineries Distribution Pattern in the Central Niger Delta, Nigeria

The study examined the geospatial analysis of geospatial analysis of artisanal refineries distribution pattern in the Central Niger Delta, Nigeria. The study made use of locational data obtained as secondary data from National Oil Spill Monitor and National Oil Spill Detection and Response Agency. Geographic analyses such as nearest neighbour analysis, directional distribution (Standard deviation ellipse), and Mean Center were carried out. Descriptive statistics involving spatial extent, frequency and percentage were employed for the data analysis. The results showed that that a total of 1476 artisanal sites were discovered in the Central Niger Delta. Of this total 55.35% (817) were found in Bayelsa State, 5.49% (81) were found in Delta State and 39.16% (578) were found in Rivers State. The nearest neighbour analysis showed that the distribution pattern of artisanal refineries was significantly clustered in Bayelsa State (Z= 47.5252, p=0.000); Delta State (Z= -10.129, p=0.0000); Rivers State (Z= -35.13333, p=0.0000) and the entire Central Niger Delta (Z= -59.8222, p=0.0000). The mean center of the distribution of artisanal refineries in Bayelsa State was found in Southern Ijaw LGA, Delta State in Uvwie LGA, Rivers State is found in Ikwerre LGA, and the entire Central Niger Delta was found in Ogbia LGA. The directional distribution standard deviation ellipse covered 58.49% in Bayelsa State, 35.06% in Rivers State and 6.35% of dispersion in Delta State. The study can be concluded that the spatial distribution pattern of artisanal refineries in the entire Central Niger Delta was clustered in nature and Bayelsa and Rivers States were more affected. It is recommended to among others that more studies should be done on the proliferation of artisanal refineries in the study area and entire Niger Delta so that the environmental effects resulting from artisanal refinery activities are reduced to the barest minimum.

Manufacturing sector spatial pattern evolution and its relationship with regional economic differences: Evidence from Jiangsu, China.

This study presents the case of China's Jiangsu Province. The spatial-temporal pattern evolution of different manufacturing sectors is discussed using spatial analysis technology (spatial autocorrelation and standard deviation ellipses). The Granger test is used to analyze the relationship between the change in the manufacturing industry spatial agglomeration and regional economic differences. The following conclusions are drawn: 1) The spatial agglomeration trend of most manufacturing sectors is weakening. Much of the manufacturing sector, like the rubber and plastic product industries, has been transferred from southern to northern Jiangsu. 2) From the scale, only a minority of these enterprises possess substantial registered capital. The capital injection scale of more manufacturing enterprises is insignificant. At the same time, manufacturing companies with substantial financial resources are increasingly inclined to choose less-concentrated areas when choosing new investment areas. 3) The reduction of regional economic differences is considered to be the Granger-cause for the decline of the spatial agglomeration degree of the manufacturing industry in Jiangsu Province. Analyzing the spatiotemporal pattern of the manufacturing industry in Jiangsu Province will provide specific policy reference values for the manufacturing industry and economic development of Jiangsu province. In addition, for companies of different sizes, the findings of this paper also provide valuable references on how they can choose suitable investment locations according to their size in the future.

Dynamic Evolution Analysis of Spatial Differences of Carbon Emissions in Beijing-Tianjin-Hebei Region from 1997 to 2017

Carbon emission is the main cause of climate change, and Beijing-Tianjin-Hebei (BTH), is one of the main region of carbon emission in China. In order to study the carbon emission characteristics in the BTH region, this paper uses the Geostatistical method to analyze the dynamic evolution of the spatial variations of carbon emissions from 1997 to 2017. (1) The global Moran’s I analysis indicates that carbon emissions take on a spatial agglomeration effect in BTH region. The global Moran’s I show a decreasing trend from 1997 to 2012, indicating that there is gradually weakening pressure between cities. However, from 2012 to 2017, the global Moran’s I show an increasing trend, indicating that there is gradually strengthening pressure between cities. (2) The hotspot areas have remained largely unchanged except Beijing. Beijing has transitioned from a hotspot area to a non-hotspot area. (3) Standard deviational ellipse analysis showed that that the carbon emission distribution in the BTH region basically exhibits a northeastsouthwest distribution pattern and has a very small variation.

Spatiotemporal Evaluation of Water Resource Vulnerability in Four River Basins of Henan Province, China

Climate change, population growth, and socio-economic transformations present multifaceted challenges to the water resource systems in the four major river basins of Henan Province. Consequently, to gain a comprehensive understanding of water security within the study area, a quantitative assessment of water resource vulnerability (WRV) is imperative. In this investigation, the vulnerability scoping diagram (VSD) model serves as the analytical framework, subdividing vulnerability into three critical subsystems: exposure, sensitivity, and adaptive capacity. Utilizing a comprehensive evaluation index system, this study assesses WRV in Henan Province’s four primary watersheds. Temporal variations and spatial patterns of WRV from 2000 to 2020 are systematically examined through the standard deviational ellipse (SDE) and GeoDetector methods. The findings indicate that vulnerability within these river basins is shaped by the interactions among exposure, sensitivity, and adaptive capacity. Moreover, exposure and sensitivity are found to be more influential than adaptive capacity. Although there are indications of future improvements in the system’s resilience against water resource vulnerability, the overarching scenario remains precarious, particularly within the Hai and Yellow River basins. Considering the diverse characteristics of the watershed, it is recommended that adaptive management strategies be implemented. This study enhances the understanding of WRV dynamics in Henan Province, thereby aiding more effective decision making in sustainable water resource management.

Spatial-temporal pattern of change in production-living-ecological space of Nanchong City from 2000 to 2020 and underlying factors.

This study analyzed the spatial-temporal change pattern and underlying factors in production-living-ecological space (PLES) of Nanchong City, China, over the past 20 years using historical land use data (2000, 2010, 2020). A land use transfer matrix was calculated from the historical land use maps, and spatial analysis was conducted to analyze changes in the land use dynamics degree, standard deviation ellipse, and center of gravity. The results showed that there was a rapid spatial evolution of the PLES in Nanchong from 2000 to 2010, followed by a stabilization in the second decade. The transfer of ecological-production space occurred mainly in the Jialing and Yilong River basins, while the reduction of production space and the increase of living space were most prominent in the intersection of three districts (Shunqing, Jialing, and Gaoping districts). The return of production-ecological space was observed in the south and northeast of Yingshan, and there was little notable transfer of other types. The distribution of production space in Nanchong evolved in a north-south to east-west trend, with the center of gravity moving from Yilong to Peng'an County. The living space and production space expanded in a north-south direction, and the center of gravity position was in Nanbu, indicating a more balanced growth or decrease in the last 20 years. The changes in the spatial-temporal pattern of PLES in Nanchong were attributed to the intertwined factors of national policies, economic development, population growth, and the natural environment. This study introduced a novel approach towards rational planning of land resources in Nanchong, which may facilitate more sustainable urban planning and development.

Research on the Evolution and Driving Factors of the Economic Spatial Pattern of the Guangdong–Hong Kong–Macao Greater Bay Area in the Context of the COVID-19 Epidemic

Understanding the economic impact of COVID-19 is the foundation for formulating targeted policies promoting economic recovery. This study uses panel data of the county economy in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) from 2017 to 2022. Firstly, the evolution characteristics of the economic structure in the GBA were analyzed using the standard deviation ellipse, geographical concentration, and spatial autocorrelation methods. Then, we revealed the changes in various economic indicators. Finally, a spatial Durbin model was constructed to study the factors affecting economic growth and spatial spillover effects in different periods. The results reveal that the economic distribution in the GBA presents a “core–edge” structure. The FDI, consumption, and exports of the Greater Bay Area fluctuate greatly, while investment growth is relatively stable. There is a significant spatial spillover effect in the county economy of the GBA. Investment, consumption, exports, labor, and innovation all have significant positive effects on economic growth, with investment having the greatest impact, while FDI has a significant negative impact. The impact of COVID-19 on the economy of the GBA is mainly reflected in the weakening of spatial spillovers, the strengthening of economic agglomeration, the decline in factor growth, and the change in the driving effect of factors on the economy. These findings can provide a reference for formulating targeted economic development policies.

Spatial Characteristics of the Non-Grain Production Rate of Cropland and Its Driving Factors in Major Grain-Producing Area: Evidence from Shandong Province, China

The non-grain production rate (NGPR) of cropland is a grave threat to global grain and food supply, and has been a hot issue across the world. However, few scholars explored the impacts of the NGPRs of different cropland types, such as those of paddy land and irrigated land in the same region. Thus, according to the third land survey data, this research first estimated the NGPRs of cropland, paddy land, irrigated land, and dry land at different scales in Shandong Province, China in 2019. Then, their spatial characteristics at a county scale were identified by combining the standard deviation ellipse model and spatial autocorrelation analysis. Finally, the potential driving factors of the NGPR of cropland were explored with the geographical weight regression model. Results are as follows: (1) The NGPR of cropland is at relatively lower level in Shandong Province and is dominated by that of irrigated land, and the NGPR of dry land is higher than those of other cropland types; (2) Significant regional differences exist in the NGPR of cropland, with profound severity in the southeast and much lower in the northwest; (3) At the provincial scale, the total power of agricultural machinery per capita and utilization degree of cropland factors can relieve the NGPR of cropland in nearly the entire research area. The proportion of GDP of the primary industry in GDP, urban population rate, and DEM are the main obstacles for NGPR decrease. At the county scale, the influences of driving factors varied across regions. This research can provide targeted and regional differentiated references for policy improvement and NGPR management.

GAIT AUTOMATICITY AND COMMUNITY MOBILITY OF OLDER ADULTS

Abstract Gait automaticity may decline with age-related impairments in the brain. As subcortical structures supporting gait automaticity decline, the prefrontal cortex (PFC) may provide compensatory function, allowing for maintenance of mobility but with loss of efficiency. Loss of efficiency may reduce ability to navigate complex community environments and restrict community mobility. We assessed the relation between PFC activation during walking in the laboratory with self-reported and objectively measured community mobility in participants aged 65+ (n=42, mean age=76, 60% female) from a randomized trial of a physical activity intervention to improve walking speed. PFC activation was measured by functional near-infrared spectroscopy as change from quiet standing to usual pace walking. Community mobility was measured objectively by 7-day global positioning system recordings of spatial (standard deviation ellipse area (SDEa), maximum distance from home) and temporal (percent time out of home (pTOH)) characteristics. Additionally, step count was recorded from 7-day actigraphy and the Life-Space Assessment (LSA) assessed self-reported mobility. Among participants with complete data at baseline (n=27), higher PFC activation during walking was associated with smaller SDEa (beta=-0.93 (-1.72, -0.15)), less pTOH (beta=-0.45 (-0.78, -0.12)), and lower step count (beta=-346 (-575, -118)) which persisted after adjusting for age, gender, education, or gait speed. PFC activation was not associated with maximum distance or LSA. There were no significant associations at the post-intervention visits (n=39). Greater PFC activation, likely indicating reduced gait automaticity, is related to lower spatial extent, duration, and intensity of community mobility. This association may be mitigated by participation in physical activity interventions.

ASSOCIATIONS BETWEEN NEIGHBORHOOD SOCIAL DESTINATIONS AND GPS-DERIVED COMMUNITY MOBILITY OF OLDER ADULTS

Abstract Neighborhood social destinations may encourage greater out-of-home travel (i.e., community mobility) and support independent functioning in later life. We examined associations between quantity of destinations that promote social interactions (e.g., arts/recreation, restaurants, stores, civic/religious institutions) and objective, GPS-derived community mobility. Participants were 146 adults ≥65 years old (Mean=77.0±6.5 years, 68% women) at baseline of a randomized trial to improve walking coordination. Participants carried a GPS device that passively collected real-time location data for 5-7 days. Spatial extent of community mobility was quantified using median standard deviational ellipse area (SDEa, km2) and maximum distance from home (mDOH, km). Duration of community mobility was characterized using percentage of time spent out-of-home (pTOH). Community mobility measures were stratified into tertiles due to positive skew. We used National Establishment Time Series (NETS) classifications to derive a total social destination count at the Census tract-level (Mean=48.9±35.7 social destinations per tract). Ordinal logistic regressions were adjusted for demographics (age, gender, race, education), device, season, and number of comorbidities and were clustered on Census tract. Each 1-SD greater destination count was associated with 46% greater odds of being in a higher tertile of pTOH (OR=1.46, 95% CI: 1.08-1.97, p=.014). Number of social destinations was not associated with SDEa or mDOH (all p’s>.05). Nearby social destinations may encourage greater duration, but not necessarily spatial extent, of community travel. Future work utilizing GPS can objectively measure activity in community social spaces to assess its benefits for cognitive and mental health in later life.

Spatial suitability between water supply pressure and waterworks water supply capacity in the Guangdong-Hong Kong-Macau Greater Bay Area: Spatial-temporal evolution pattern, driving mechanism and Implications

The Guangdong-Hong Kong-Macao Greater Bay Area (GHMGBA) is one of the four major bay areas in the world. However, the mismatch between water resource distribution and spatial layout of population and productivity poses great challenge to water supply security of the GHMGBA. Evaluating the spatial suitability of water supply pressure (WSP) and waterworks water supply capacity (WSC) is essential to the spatial equilibrium allocation of water resources and water supply security in the GHMGBA. Therefore, the current study first investigated the spatial-temporal evolution pattern of WSP and waterworks WSC using the standard deviational ellipse and Exploratory Spatial Data Analysis (ESDA) methods, the spatial suitability of WSP and waterworks WSC was further evaluated using the coupling coordination degree model, and the driving mechanism of such spatial suitability was finally revealed using the dynamic spatial Durbin model. The results show that the WSP respectively forms high and low value aggregations in the eastern and western parts of the Pearl River estuary; the area with high waterworks WSC is mainly located in the northern part, the high-high cluster areas are in the eastern part of Zhaoqing and the western part of Huizhou, and the low-low cluster areas are mainly in Guangzhou-Foshan, Shenzhen-Hong Kong and Zhuhai-Macao. The coupling coordination of WSP and waterworks WSC was in an overall imbalance state. The eastern and western parts of the Pearl River estuary are slightly unbalanced or with better level. Demand-driven and economic efficiency have significant effects under spatial and economic proximity weights, government guidance has a significant positive effect, while market orientation has an insignificant positive effect; environmental pollution and resource allocation have a significant negative effect under geographical proximity weight, and environmental pollution has a stronger negative effect on spatial suitability. Finally, policy recommendations were proposed to improve the spatial suitability of WSP and waterworks WSC of the GHMGBA.

Analysis of the Ongoing Effects of Disasters in Urbanization Process and Climate Change: China’s Floods and Droughts

Urban development and climate change have strengthened the possibility of floods and droughts in cities. In this study, we evaluated the influences of these disasters and related social damage in nine major basins during the past 50 years. Unusually, the following conclusions were drawn from the analysis of relevant indicators before and after urbanization: (1) agricultural loss area (flood), grain loss, and direct economic loss showed an upward trend, while other indicators showed the opposite. (2) Floods most often occur in the Yangtze River Basin (58, 26.2%), followed by the Liaohe River Basin (49, 22.2%), which is closely related to the topography and economic progress of the area. (3) The modified Mann–Kendall (MK) analysis results are consistent with the indicators trend. Finally, the regularity of the climate change and urbanization process is revealed by the migration of the standard deviation ellipse and the mean center of the four indicators. China needs to integrate urban water/drought policy development with sustainable urbanization policy development to cope with the changing natural and social environment and to minimize urban ecological risks.

Spatio‐temporal pattern evolution and driving factors of A‐level logistics enterprises in Yangtze River Delta

SummaryIn this paper, standard deviation ellipse, spatial autocorrelation, cold hot spot analysis, kernel density estimation, and other spatial analysis models are first used to analyze the evolution process and spatial and temporal distribution characteristics of A‐level logistics enterprises in the Yangtze River Delta. Secondly, a regression model is used to analyze the main factors driving the evolution of the spatial and temporal patterns of A‐level logistics enterprises in the Yangtze River Delta. The research finds that the development of A‐level logistics enterprises in the Yangtze River Delta urban agglomeration generally presents a trend that increasing number and unbalanced development of enterprises of different levels. Regional economic strength, regional policy, transportation accessibility, cargo transportation capacity, and port development level are the main factors driving the evolution of the spatial and temporal pattern of A‐level logistics enterprises in the Yangtze River Delta.

Spatial distribution and driving factors of Chinese dragon and lion dance athletes based on GIS

As the common wealth of all mankind, intangible cultural heritage carries the memory of history. The implementation of dragon and lion dance technical grade evaluation can be called pioneering work for the legacy inheritance. The purpose of this study is to analyze the distribution characteristics, trends, types, and driving factors of dragon and lion dance athletes. Athletes who were awarded a grade certificate by Chinese Dragon and Lion Dance Sports Association from 2018 to 2021 were taken as the analysis objects. In ArcGIS10.8, trend surface analysis and standard deviational ellipse are used to study the spatial distribution characteristics. Using the global and local Moran's I in GeoDa, this paper explores the concentration degree and types of dragon and lion dance athletes. The factors driving the distribution difference are analyzed with the help of geographical detectors. Continuous data such as total GDP, sports field areas, permanent populations, and altitude are taken as the software input after preprocessing. The results show that there are significant differences in the distribution of provinces and four geographical regions. For dragon dance athletes, there is a linear growth trend in the west-east direction and an inverted U-shape trend in the south-north direction. For lion dance athletes, there is a trend of log function in the west-east direction and an inverted U shape in the south-north direction. The global Moran's I is 0.2386, and there are obvious characteristics of H–H, L-L, and L-H aggregation types. Nomination of sports intangible cultural heritage, total GDP, permanent resident population, urbanization development level, the number of colleges and universities, and the proportion of tertiary industry are the leading factors, and the explanatory power of interactive factors is significantly enhanced. Therefore, it is suggested to strengthen the cultural heritage protection of dragon and lion dance, increase capital investment, enhance public participation, and raise government attention.