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Introduction: The agricultural sector is the second largest emitter of greenhouse gases, accounting for 23% of global anthropogenic carbon emissions. Analysis of the basic state of carbon emissions from China's agriculture is helpful to achieve carbon reduction targets. Methods: Agricultural carbon emissions were calculated using the emission factor method, based on data from the China Rural Statistical Yearbook and various provincial statistical yearbooks. To analyze spatial patterns, the standard deviation ellipse method and the center of gravity migration model were employed, uncovering the migration path of agricultural carbon emissions. Regional disparities and the driving factors of agricultural carbon emissions were further examined using the Theil index and the Logarithmic Mean Divisia Index (LMDI) model. Results: The analysis indicated that the emissions center has gradually shifted towards the central and western regions, reflecting changes in agricultural production activity areas. Intraregional differences are the primary contributors to the imbalance in agricultural carbon emissions, with pronounced disparities in grain production and consumption balance regions. Key influencing factors include agricultural production efficiency, adjustments in agricultural industrial structure, economic structure and output, and urbanization levels. The economic output effect and urbanization effect are identified as the main drivers of increased carbon emissions, while declining production efficiency has hindered emission reduction efforts. Conclusion: The findings provide valuable insights for regional management and policymaking in China's agricultural sector, highlighting the need to enhance production efficiency and optimize agricultural structure to reduce emissions. [ABSTRACT FROM AUTHOR]

Background: Intestinal infectious diseases (IIDs) can impact the growth and development of children and weaken adults. This study aimed to establish a spatial panel model to analyze the relationship between factors such as population, economy and health resources, and the incidence of common IIDs. The objective was to provide a scientific basis for the formulation diseases prevention measures. Methods: Data on monthly reported cases of IIDs in each district and county of Zhejiang Province were collected from 2011 to 2021. The spatial distribution trend was plotted, and nine factors related to population, economy and health resources were selected for analysis. A spatial panel model was developed to identify statistically significant spatial patterns of influencing factors (P < 0.05). Results: The results revealed that each type of IIDs exhibited a certain level of clustering. Each IIDs had a significant radiation effect, HEV (b = 0.28, P < 0.05), bacillary dysentery (b = 0.38, P < 0.05), typhoid (b = 0.36, P < 0.05), other infectious diarrheas (OIDs) (b = 0.28, P < 0.05) and hand, foot and mouth disease (HFMD) (b = 0.39, P < 0.05), indicating that regions with high morbidity rates spread to neighboring areas. Among the population characteristics, density of population acted as a protective factor for bacillary dysentery (b=-1.81, P < 0.05), sex ratio acted as a protective factor for HFMD (b=-0.07, P < 0.05), and aging rate increased the risk of OIDs (b = 2.39, P < 0.05). Urbanization ratio posed a hazard factor for bacillary dysentery (b = 5.17, P < 0.05) and OIDs (b = 0.64, P < 0.05) while serving as a protective factor for typhoid (b=-1.61, P < 0.05) and HFMD (b=-0.39, P < 0.05). Per capita GDP was a risk factor for typhoid (b = 0.54, P < 0.05), but acted as a protective factor for OIDs (b=-0.45, P < 0.05) and HFMD (b=-0.27, P < 0.05). Additionally, the subsistence allowances ratio was a risk factor for HEV (b = 0.24, P < 0.05). Conclusion: The incidence of IIDs in Zhejiang Province exhibited a certain degree of clustering, with major hotspots identified in Hangzhou, Shaoxing, and Jinhua. It would be essential to consider the spillover effects from neighboring regions and implement targeted measures to enhance disease prevention based on regional development. [ABSTRACT FROM AUTHOR]

Urban agglomerations play a leading role in China's economic development and social governance, and the study of carbon emissions from land-use in urban agglomerations is helpful to the regional coordinate emission reduction. In this study, the carbon emission coefficient method to measure the land-use carbon emissions of the urban agglomeration around Poyang Lake during 2000-2020 was adopted, the standard deviation ellipse was used to further explore the migration trajectory of the land use carbon emissions, and finally the Markov-PLUS model and the gray BP neural network were applied to the multi-scenario prediction of the land- use carbon emissions in 2030. The finding of the study indicated that during the years 2000-2020, the farmland was an important source of rapid expansion of urban agglomerations, land-use carbon emissions showing an upward trend with an average annual increase of 1.880 million tons, while the construction land and forest land were the main contributors of carbon sources and sinks, respectively. As a whole, main part of the carbon emission tended to the change from southwest-ward migration to northeast-ward migration, with a cumulative migrated distance of 37.39 km and 38.50 km, respectively; and the prediction results showed that the urban agglomeration around Poyang Lake will have the highest carbon emission (58.826 3 million tons) in the scenario of adequate farmland protection in 2030, followed by the natural development and ecological priority scenarios, with respective 58.764 8 million tons, 58 669 4 milliontons. The results drawn from this study could provide the reference basis for the urban agglomeration around Poyang Lake to increase carbon sinks, and to reduce carbon sources, thus realizing the sustainable development of the city. [ABSTRACT FROM AUTHOR]

Sloping farmland (SpF) is not only an important space for food production and supply in China's hilly areas, but also a major source of soil erosion. Thus, it is important to achieve a healthy balance between regional food security and environmental protection. Yangtze River Economic Belt (YREB), an important grain production base where SpF concentrated in China, is also faced with serious soil erosion. However, research at the macro scale on the spatiotemporal change of SpF and its driving forces in YREB is still lacking. To bridge the gap, we first analyzed the long-term evolution characteristics of SpF in 1069 counties in the YREB and then explored the driving mechanism of SpF changes during 1980–2020. Results showed that the SpF in the YREB continuously decreased during the study period, with a total area decreasing by 26,300 km2. SpF was primarily concentrated in the upper reaches of the YREB while SpF use dynamic degree varied significantly with the most active change in the lower reaches, reaching to a maximum of 0.324%. The spatial gravity of SpF distribution relocated 20.15 km towards the southwest. As for the driving factors, the socioeconomic factors contributed greater to SpF changes in the whole YREB and its subregions. The intensity of human activities is the most crucial, with factor contribution rate constantly above 0.76. The interactive detection revealed that the prevailing interaction format was primarily bi-enhanced, supplemented with nonlinear-enhanced, which amplified the role of different factors after interacting with them. The pair-wise interaction involving socioeconomic factors had a more potential effect on SpF changes compared to those between physical geography and locational factors. The influence of the intensity of human activities on SpF changes is greatly enhanced after interacting with any factor. It dominated SpF changes in the YREB and its interaction with GDP played an important role at all times. These findings can enlighten differential management strategies of SpF use and ecological conservation in the YREB. [ABSTRACT FROM AUTHOR]

Abstract Background Intestinal infectious diseases (IIDs) can impact the growth and development of children and weaken adults. This study aimed to establish a spatial panel model to analyze the relationship between factors such as population, economy and health resources, and the incidence of common IIDs. The objective was to provide a scientific basis for the formulation diseases prevention measures. Methods Data on monthly reported cases of IIDs in each district and county of Zhejiang Province were collected from 2011 to 2021. The spatial distribution trend was plotted, and nine factors related to population, economy and health resources were selected for analysis. A spatial panel model was developed to identify statistically significant spatial patterns of influencing factors (P

In order to explore the spatial distribution, spatial pattern evolution and spatial aggregation of the coupling and coordination of water resources utilization, low-carbon emission and green development of the Upper and Middle Yellow River, coupling coordination degree model, standard deviation ellipse and spatial autocorrelation analysis method were used to analyze the spatial heterogeneity of the coupling and coordination of water resources utilization, low-carbon emission and green development in 54 cities of the Upper and Middle Yellow River from 2010 to 2020. The results show that a) the comprehensive evaluation index of the three subsystems has been improved to varying degrees and the degree of coupling and coordination of each city is different. The proportion of primary coordination cities has increased from 55 % in 2010 to 74 % in 2020, and there are fewer intermediate coordination cities. b) The main migration direction of the center of gravity of the coupling coordination degree of the three subsystems is southwest, and the direction of the long axis of the standard deviation ellipse is north- west-southeast. The standard deviation of the long axis and the short axis is reduced by 2.21 km and 0.59 km, respectively, and there is a gathering trend of migration to the southwest. c) The coupling coordination degree of the three subsystems has a significant positive correlation in space. The high-high aggregation is mainly distributed in the south and west of the middle reaches of the Yellow River, the high-low aggregation is mainly distributed in Lanzhou City, and the low-low aggregation is mainly distributed in the west of the upper reaches of the Yellow River. Although the coupling coordination degree of the three subsystems of the Upper and Middle Yellow River has been increased year by year, the spatial heterogeneity is obvious. [ABSTRACT FROM AUTHOR]

Government environmental information disclosure (GEID) plays an important role in promoting the digital transformation of environmental governance, leading the concept of sustainable development, enhancing public oversight capacity, and promoting democratic decision-making governance. Using provincial panel data from China spanning from 2009 to 2021, we conducted spatial data exploratory analysis and used the dynamic spatial panel model to investigate the spatial–temporal development trends and influencing factors of GEID. The results show that (1) GEID in China exhibits significant spatial agglomeration characteristics, with an "H-H" (High-High aggregation type) agglomeration characteristic observed in three national strategic development regions: Yangtze River Delta, southeast coastal areas, and Beijing–Tianjin–Hebei region. (2) The spillover effect from the southeast coastal provinces gradually radiates to the northwest, resulting in an overall westward movement of GEID. (3) GEID exhibits a significant path-dependency feature in the temporal dimension and a "peer effect" in the spatial dimension. (4) Population size has the greatest impact on GEID. Population size, public participation, and the industrial and transportation sectors positively influence GEID improvement at the local level. However, they generate negative spillover effects to neighbouring provinces. Environmental status and the size of the Real Estate sector have no significant effect. Therefore, China should strengthen regional cooperation, narrow regional disparities, cultivate new quality productive forces, establish a government-led proactive disclosure mechanism under public supervision, and improve the level of GEID at the national level. [ABSTRACT FROM AUTHOR]

Using the land use data set from 2000 to 2020 as the data source, GIS technology was used to explore the characteristics of land use change in Zhaotong city from three aspects: land use transfer matrix, standard deviation ellipse and center of gravity transfer model, and landscape pattern index was used to analyze the landscape pattern evolution from the landscape level and landscape type level. The results show that: (1) The main land types in Zhaotong are forest land, cultivated land and grassland, the growth rate of construction land is the largest, the standard deviation ellipse of grassland is the least obvious, and the distribution of center of gravity of cultivated land, forest land and grassland is relatively stable. (2) From the landscape level, the number of patches increased, the degree of connectivity decreased, the largest patch distribution dominance weakened, the degree of fragmentation increased, the connectivity decreased, the cohesion decreased and the complexity increased. (3) From the landscape type level, the landscape type with the largest patch number, patch density and edge density is cultivated land, the landscape type with the largest patch index and aggregation index is woodland, the landscape type with the largest mean patch fractal dimension is construction land, and the landscape type with the largest interspersion & juxtaposition index is water. [ABSTRACT FROM AUTHOR]

Studying spatial and temporal characteristics of land use changes and the driving factors in the Yellow River Basin as well as simulating and predicting future land use is crucial for resource management, ecological protection, and regional sustainable development in the Yellow River Basin. Based on the China Land Cover Dataset (CLCD) of the Yellow River Basin from 1990 to 2021, this study employs various methods such as the Mann–Kendall test and sliding t-test, land use dynamics, the land use transfer matrix, the standard deviation ellipse, the center of gravity migration model, and a geographic detector to explore the spatial and temporal characteristics of land use changes and driving forces in the Yellow River Basin over the past 30 years. Additionally, the study predicts land use types in the study area for the year of 2030 by using the Future Land Use Simulation (FLUS) model. The results show the following: (1) From 1990 to 2021, the area of forest, grassland, water, and impervious surfaces increased significantly, while the area of cropland, shrub, barren land, and wetlands decreased significantly. The most actively changing land use types are cropland, grassland, barren land, and impervious surfaces. (2) The center of gravity for shrub and impervious surfaces shifted westward, while wetlands showed a trend of obvious concentrated distribution, and the remaining land use types exhibited stable directional distributions. (3) Economic factors had a stronger driving effect on land use changes than topographic and climatic factors. The land use changes in the Yellow River Basin are influenced by the coordinated driving forces of multiple factors. (4) In 2030, the main land use types in the Yellow River Basin are still expected to be cropland, grassland, and forest. However, there will be a significant expansion of impervious surfaces and forest land, with substantial encroachment on cropland and grassland. [ABSTRACT FROM AUTHOR]

Guizhou is a typical mountainous province and is also one of the lowland regions in China that has attracted a population influx. Here, using population density data from 2000 to 2020 as the basic dataset and the coefficient of variation method and standard deviation ellipse analysis, we investigated the spatial characteristics across different years. The results show: Firstly, Guizhou's population has a distinct spatial distribution, characterized by a lower population density in the southeast and a higher density in the northwest as well as an increasing polarization of population concentration toward the centers of prefecture-level cities and provincial capitals. Fluctuations in population density resemble a central siphon effect, which is particularly pronounced in the provincial capital and show a significant gravitational pull. Secondly, the coefficient of variation in population density across Guizhou's counties is spatially divided by Guiyang, showing higher values in the east and lower values in the west. Furthermore, the ellipse of the standard deviation of population density is gradually shrinking, indicating an increasingly concentrated population distribution. Thirdly, the explanatory power of the population and socio-economic systems on the population distribution in Guizhou is significantly greater than that of the natural systems. Population distribution and migration patterns have shifted from purely "economic driven" to coexisting with "economic and comfort-oriented" trends, and there is an urgent need to improve the comfort level of public services as a typical supply, in order to boost Guizhou's population attraction. [ABSTRACT FROM AUTHOR]

Copyright of Resources Development & Market is the property of Sichuan Resource Development & Market Magazine Co., Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Against the backdrop of rapid urbanization and coordinated development in the Beijing–Tianjin–Hebei region of China, urban residential land prices in Hebei Province have experienced significant increases, exacerbating housing pressures on residents. This study aims to elucidate the spatio-temporal evolution characteristics of urban residential land prices, identify the key influencing factors in Hebei Province of China, and offer insights on macro-control of the land market, optimization of the land supply structure, and guidance on the sustainable development of land and real estate markets in the region. Utilizing land price monitoring data from 11 prefecture-level cities in Hebei Province spanning the past five years, this research employs quantitative methods, such as the Theil index, the standard deviation ellipse, and the geographic detector model, to analyze the spatio-temporal dynamics and factors shaping urban residential land prices. The results show that: (1) Urban residential land prices in Hebei Province exhibited an overall upward trend from 2018 to 2022, characterized by pronounced spatial variations, with higher prices predominantly concentrated in the cities along the Shijiazhuang–Baoding–Langfang–Tangshan corridor; (2) The distribution pattern of urban residential land prices generally mirrors that of GDP, indicating a consistent movement of price centers with urban land price escalation; (3) Urban land prices are influenced by multiple factors in combination, where the interactions among these factors outweigh the impact of any single factor. Specifically, the proportion of GDP attributed to the tertiary industry and location conditions emerge as pivotal factors affecting urban residential land prices in Hebei Province. Given these significant spatial disparities, addressing the industrial structure and optimizing urban land resource allocation are critically imperative. [ABSTRACT FROM AUTHOR]

Declining levels of social welfare caused by climate warming and air pollution place increasing constraints on high-quality, sustainable global development. To achieve global climate-governance goals, it is essential to accelerate the process of peaking carbon emissions and meeting air-quality standards. Despite growing awareness of the impact of low-carbon city policies on the environment, few studies have focused on their impact on urban air quality. Based on panel data drawn from 275 cities between 2011 and 2017, the present study evaluates the effects of a low-carbon city policy on urban sulfur-dioxide emissions, using the low-carbon city policy as a quasi-natural experiment. The findings reveal that urban sulfur-dioxide emissions have obvious spatial-autocorrelation characteristics, showing obvious spatial clustering. The low-carbon city policy not only significantly reduced urban sulfur-dioxide emissions in pilot cities, but also suppressed sulfur-dioxide emissions in surrounding cities through an indirect rebound effect. This paper provides a theoretical reference for collaborative governance, which can help to achieve peak carbon emissions and air-quality standards. To reach those goals, nations must abandon territorial prevention-and-control methods based on administrative divisions and to fully activate cross-city regional joint prevention-and-control measures. This study proposes key policies, including promoting inter-city regional coordination mechanisms, strengthening the collaborative governance in relation to carbon-dioxide and sulfur-dioxide emissions, and promoting the construction of inner-city green facilities. [ABSTRACT FROM AUTHOR]

Quantifying green transformation level of 26 mountainous counties is crucial for the construction of a demonstration zone for common prosperity in Zhejiang. Based on the perspective of "green ecology-green production-green life" three-dimensional space, a green transformation indicator system was constructed; the temporal and spatial differentiation characteristics and driving factors of green transformation in 26 mountainous counties of Zhejiang from 2010 to 2021 were studied using vertical and horizontal pull-off grade method, gravity center-standard deviation ellipse, and geographically and temporally weighted regression (GTWR) model. The results show that from 2010 to 2021, the overall green transformation of 26 mountainous counties showes an increasing trend, with an average annual increase of 2. 428%, indicating that there is still considerable room for improvement; the variation coefficient of green transformation decreases year by year, and the characteristic of the regional differences gradually changes from "large gap and low level" to "small gap and high level". From 2010 to 2021, green transformation of 26 mountainous counties gradually showes a spatial distribution pattern with "Yongjia-Jinyun-Qingtian" as the core; the gravity center of green transformation gradually expands to the north, and the northern region of 26 mountainous counties have a significant improvement in green transformation during the study period; the spatial distribution of green transformation in 26 mountainous counties generally follows a northwest-southeast trend, and the distribution pattern is relatively stable; the distribution range of the standard deviation ellipse gradually narrows, and the spatial agglomeration continues to increase, indicating that the problem of regional development imbalance has improved. Each influencing factor shows strong temporal and spatial heterogeneity. Economic development, urbanization, government regulation and human capital quality have always been the main driving factors for green transformation of 26 mountainous counties; the driving forces of financial development, scientific, technological level and openness to the outside world have gradually increased; the driving effect of industrial structure is still unstable, and the driving ability for green transformation of 26 mountainous counties is limited. [ABSTRACT FROM AUTHOR]

Copyright of Resources Development & Market is the property of Sichuan Resource Development & Market Magazine Co., Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Simple Summary: In recent years, the damage inflicted upon vegetation by the fall webworm (FWW), Hyphantria cunea (Drury) (Lepidoptera: Erebidae: Arctiidae), has escalated globally. The black-headed fall webworm has extensively invaded regions in Europe and Asia. In China, scholars have conducted extensive research on the fall webworm. However, there has been limited research on the dynamics of invasion by the black-headed form of the fall webworm and the comprehensive interplay of various factors affecting its spread. Therefore, this study focuses on the dynamics of invasion by the black-headed form of the fall webworm and the combined influence of various factors affecting its spread. The plan is to map the invasion road map of Autumn Dictyophora melanocephala since its introduction into China and summarize the effects of terrain, vegetation, and human factors on the temporal and spatial changes of the species. The fall webworm (FWW), H. cunea (Drury) (Lepidoptera: Erebidae: Arctiidae), is an extremely high-risk globally invasive pest. Understanding the invasion dynamics of invasive pests and identifying the critical factors that promote their spread is essential for devising practical and efficient strategies for their control and management. The invasion dynamics of the FWW and its influencing factors were analyzed using standard deviation ellipse and spatial autocorrelation methods. The analysis was based on statistical data on the occurrence of the FWW in China. The dissemination pattern of the FWW between 1979 and 2022 followed a sequence of "invasion-occurrence-transmission-outbreak", spreading progressively from coastal to inland regions. Furthermore, areas with high nighttime light values, abundant ports, and non-forested areas with low vegetation cover at altitudes below 500 m were more likely to be inhabited by the black-headed FWW. The dynamic invasion pattern and the driving factors associated with the fall webworm (FWW) provide critical insights for future FWW management strategies. These strategies serve not only to regulate the dissemination of insects and diminish migratory tendencies but also to guarantee the implementation of efficient early detection systems and prompt response measures. [ABSTRACT FROM AUTHOR]

IntroductionThe agricultural sector is the second largest emitter of greenhouse gases, accounting for 23% of global anthropogenic carbon emissions. Analysis of the basic state of carbon emissions from China's agriculture is helpful to achieve carbon reduction targets.MethodsAgricultural carbon emissions were calculated using the emission factor method, based on data from the China Rural Statistical Yearbook and various provincial statistical yearbooks. To analyze spatial patterns, the standard deviation ellipse method and the center of gravity migration model were employed, uncovering the migration path of agricultural carbon emissions. Regional disparities and the driving factors of agricultural carbon emissions were further examined using the Theil index and the Logarithmic Mean Divisia Index (LMDI) model.ResultsThe analysis indicated that the emissions center has gradually shifted towards the central and western regions, reflecting changes in agricultural production activity areas. Intraregional differences are the primary contributors to the imbalance in agricultural carbon emissions, with pronounced disparities in grain production and consumption balance regions. Key influencing factors include agricultural production efficiency, adjustments in agricultural industrial structure, economic structure and output, and urbanization levels. The economic output effect and urbanization effect are identified as the main drivers of increased carbon emissions, while declining production efficiency has hindered emission reduction efforts.ConclusionThe findings provide valuable insights for regional management and policymaking in China's agricultural sector, highlighting the need to enhance production efficiency and optimize agricultural structure to reduce emissions.

Wood processing products can be used as a substitute for some high carbon emission materials, thus contributing significantly to climate change mitigation. China has significant importance in guaranteeing a stable global supply of wood products. However, China has experienced a decline in wood product exports recently, which could affect the world's progress toward sustainable development. This study focuses on the spatial agglomeration of China's wood-processing industry and explores the potential of integrating spatial agglomeration to address the diminishing export growth. We found that the spatial agglomeration of China's wood-processing industry generally increased rapidly between 1999 and 2004, but decreased after 2004. The centroid of China's wood-processing is shifting from the northeastern region toward the eastern coastal areas. The industry is more concentrated in the north–south direction and slightly dispersed in the east–west direction. Most sub-sectors of China's wood-processing industry operate at the primary agglomeration level, indicating significant potential for improvement and further development. The empirical results unveil the substantial positive influence of spatial agglomeration on exports within China's wood-processing industry, indicating the prospects for enhancing exports through the deliberate exploitation of agglomeration effects. The results advocate the view that spatial agglomeration acts as an essential accelerator for export growth and firms' international competitiveness. Therefore, spatial agglomeration can alleviate the export constraints of China's wood-processing industry. The results also show that exports are hampered by increased enterprise productivity. The 'productivity paradox' phenomenon has also surfaced in low-tech industries, like the wood-processing industry, as a result of issues with transaction costs, the development path, and policy orientation. Therefore, we should strategically leverage the spatial agglomeration effect, especially in the western region, and guide the moderate competition of enterprises to enhance the competitiveness of low-tech enterprises. China's wood-processing industry can provide advanced experience and lessons for other countries regarding industrial cluster allocation and sustainable development models. [ABSTRACT FROM AUTHOR]

Exploring the spatial distribution characteristics of tourist attractions and the influencing factors is of significant importance for destination development, yet little relevant research has been conducted. This study explores the spatial patterns and determinants of tourist attractions using Hubei Province of China as a case based on the POI (Points of Interest) data, combined with standard deviation ellipse, GeoDetector method and so on. The results show that: (1) The distribution of tourist attractions in Hubei Province is concentrated in Wuhan and Huanggang. (2) The overall spatial patterns of tourist attractions in Hubei Province show a trend of “overall dispersion, partial concentration”, with the direction of northwest-southeast. (3) The permanent population, passenger traffic volume, per capita GDP, and the added value of the tertiary industry are the primary factors influencing the spatial distribution of tourist attractions in Hubei Province. Additionally, topography and river systems factors also impact their distribution. This study provides critical information for theory and practice in terms of tourism resources optimization.

Guizhou is a typical mountainous province and is also one of the lowland regions in China that has attracted a population influx. Here, using population density data from 2000 to 2020 as the basic dataset and the coefficient of variation method and standard deviation ellipse analysis, we investigated the spatial characteristics across different years. The results show: Firstly, Guizhou’s population has a distinct spatial distribution, characterized by a lower population density in the southeast and a higher density in the northwest as well as an increasing polarization of population concentration toward the centers of prefecture-level cities and provincial capitals. Fluctuations in population density resemble a central siphon effect, which is particularly pronounced in the provincial capital and show a significant gravitational pull. Secondly, the coefficient of variation in population density across Guizhou’s counties is spatially divided by Guiyang, showing higher values in the east and lower values in the west. Furthermore, the ellipse of the standard deviation of population density is gradually shrinking, indicating an increasingly concentrated population distribution. Thirdly, the explanatory power of the population and socio-economic systems on the population distribution in Guizhou is significantly greater than that of the natural systems. Population distribution and migration patterns have shifted from purely “economic driven” to coexisting with “economic and comfort-oriented” trends, and there is an urgent need to improve the comfort level of public services as a typical supply, in order to boost Guizhou’s population attraction.

Studying spatial and temporal characteristics of land use changes and the driving factors in the Yellow River Basin as well as simulating and predicting future land use is crucial for resource management, ecological protection, and regional sustainable development in the Yellow River Basin. Based on the China Land Cover Dataset (CLCD) of the Yellow River Basin from 1990 to 2021, this study employs various methods such as the Mann–Kendall test and sliding t-test, land use dynamics, the land use transfer matrix, the standard deviation ellipse, the center of gravity migration model, and a geographic detector to explore the spatial and temporal characteristics of land use changes and driving forces in the Yellow River Basin over the past 30 years. Additionally, the study predicts land use types in the study area for the year of 2030 by using the Future Land Use Simulation (FLUS) model. The results show the following: (1) From 1990 to 2021, the area of forest, grassland, water, and impervious surfaces increased significantly, while the area of cropland, shrub, barren land, and wetlands decreased significantly. The most actively changing land use types are cropland, grassland, barren land, and impervious surfaces. (2) The center of gravity for shrub and impervious surfaces shifted westward, while wetlands showed a trend of obvious concentrated distribution, and the remaining land use types exhibited stable directional distributions. (3) Economic factors had a stronger driving effect on land use changes than topographic and climatic factors. The land use changes in the Yellow River Basin are influenced by the coordinated driving forces of multiple factors. (4) In 2030, the main land use types in the Yellow River Basin are still expected to be cropland, grassland, and forest. However, there will be a significant expansion of impervious surfaces and forest land, with substantial encroachment on cropland and grassland.

Against the backdrop of rapid urbanization and coordinated development in the Beijing–Tianjin–Hebei region of China, urban residential land prices in Hebei Province have experienced significant increases, exacerbating housing pressures on residents. This study aims to elucidate the spatio-temporal evolution characteristics of urban residential land prices, identify the key influencing factors in Hebei Province of China, and offer insights on macro-control of the land market, optimization of the land supply structure, and guidance on the sustainable development of land and real estate markets in the region. Utilizing land price monitoring data from 11 prefecture-level cities in Hebei Province spanning the past five years, this research employs quantitative methods, such as the Theil index, the standard deviation ellipse, and the geographic detector model, to analyze the spatio-temporal dynamics and factors shaping urban residential land prices. The results show that: (1) Urban residential land prices in Hebei Province exhibited an overall upward trend from 2018 to 2022, characterized by pronounced spatial variations, with higher prices predominantly concentrated in the cities along the Shijiazhuang–Baoding–Langfang–Tangshan corridor; (2) The distribution pattern of urban residential land prices generally mirrors that of GDP, indicating a consistent movement of price centers with urban land price escalation; (3) Urban land prices are influenced by multiple factors in combination, where the interactions among these factors outweigh the impact of any single factor. Specifically, the proportion of GDP attributed to the tertiary industry and location conditions emerge as pivotal factors affecting urban residential land prices in Hebei Province. Given these significant spatial disparities, addressing the industrial structure and optimizing urban land resource allocation are critically imperative.

Evapotranspiration (ET) is a crucial parameter in the process of the hydrological cycle. It is vital for water resource management in the Xiangjiang River Basin (XRB) within Hunan Province of China to explore the spatial and temporal dynamic characteristics of ET. Based on MOD16, this study revealed the characteristics of spatiotemporal patterns of ET in the XRB from 2000 to 2020. We first applied land use data and change rate for overall trend analysis on ET. Then, we obtained migration routes of ET through standard deviation ellipse (SDE). Furthermore, we demonstrated the effects of monsoon and urban expansion on ET change. The results showed: (1) while the ET of artificial surfaces decreased the change rate in most regions of the XRB was 8.83%, indicating that the overall trend of ET in the XRB was increasing. (2) At 10-year intervals, the SDE center of ET all migrated in a clockwise direction. (3) The correlation between precipitation and ET is more obvious than that between temperature and ET. (4) With the influence of monsoon on precipitation in East Asia, the changes in precipitation are consistent with the ET change. HIGHLIGHTS Revealing the spatiotemporal characteristics of evapotranspiration (ET) in a river basin with the typical East Asian monsoon climate.; Using the standard deviation ellipse method to access the spatiotemporal migration routes of ET, which provides a new insight for ET mapping.; Demonstrating the implications of the monsoon and urban expansion on ET changes.;

[Objective] The utilization efficiency of land and water resources in the Huaihe River basin was evaluated to clarify the degree of coupling and coordination between the two and their spatial differentiation characteristics, in order to provide a theoretical reference for improving the utilization efficiency of land and water resources and promoting the benign and coordinated development of land and water resources in the basin. [Methods] The Super-SBM model was used to measure the land and water resource utilization efficiencies of 30 cities in the Huaihe River basin. The coupling coordination degree model was constructed to discuss the coordinated development of the two. The standard deviation ellipse and the Dagum Gini coefficient method were used to analyze the spatial deviation degree and spatial differentiation source of the coupled coordination degree. [Results] ① During the study period, the utilization efficiency of land and water resources in the Huaihe River basin showed a fluctuating upward trend, and the spatial heterogeneity was significant. ② From 2011 to 2014, the degree of coupling and coordination between the two factors was in the barely coordinated stage. From 2015 to 2020, the degree of coupling and coordination was basically in the primary coordination and intermediate coordination stage, both of which were dominated by the lag of water resource utilization efficiency. A spatial pattern of “higher in the east and west, and lower in the middle” was gradually presented. ③ The coupling and coordination degree of land and water resource utilization efficiency in the northwest and southeast cities of the Huaihe River basin increased rapidly, and there was a phenomenon of strong and weak alternation. ④ The overall difference of the coupling coordination degree between the two showed a downward trend, and the spatial differentiation mainly came from the hypervariable density, followed by regional differentiation. [Conclusion] The utilization efficiencies of urban land resources and water resources in the Huaihe River basin were not high, and the coupling coordination degree was also low. Cities should strengthen the efficient and intensive use of water and land resources, improve the coupling coordination degree between the two, and provide a decision-making basis for the implementation of differentiated resource development strategies in various regions.

This paper proposes a theoretical framework for assessing ecological protection and restoration from the perspective of ecological efficiency. We applied the super-efficiency Slack-based measure model to examine the social and economic impacts of ecological resource consumption transformation in Heilongjiang Province, China. Additionally, a convergence analysis was used to evaluate and test the impact of the standard deviation ellipse method on regional sustainability. The results indicated that the land use structure was unstable; the conversion rate of resource consumption was low; and the average Ecological efficiency was only 0.343 in terms of the land use structure. Funds for forest ecological restoration have a significant impact on the effectiveness of ecological resource transformation. Implementing the Chinese ecological restoration project improves the ecological efficiency level of the communities. The center of gravity of ecological efficiency moved greatly in the years when forestry investment increased. Technological transfer and diffusion, experience imitation in environmental regulation, and eventually convergent steady-state levels of the ecological efficiency of different regions are necessary to improve the economic and social development level of regions with low environmental quality efforts should be made to reduce resource consumption intensity, increase fund utilization efficiency, and form a comprehensive and systematic system of ecological environment governance through reasonable enhancement of regional environmental regulations, increased investment in technological advancement, and funds for ecological protection and restoration.

Toponym, as the spiritual memory shared by the residents, carries rich cultural connotation and is of great significance to the continuation and development of the excellent traditional Chinese context. This paper analyzes the spatial distribution characteristics of the toponyms in Hehuang Valley by means of the research methods of classification statistics, kernel density estimation and standard deviation ellipse. The results show：（1） geographical names of Hehuang Valley can be divided into three categories（natural landscape, human landscape and others）.（2）The names of Hehuang Valley show a directional trend of the divergence of Huangshui River, Yellow River, Datong River and other water systems with Xining as the center.（3）The toponyms of natural landscape fully embodies the ancestors'wisdom in living near the rivers and trying to avoid the disadvantages of the landscapes for their residence in Hehuang Valley, and reflects the rough natural environment.（4）The toponyms of human landscape show the historical facts of the integration and development of multi-ethnic groups, and the characteristics of the military and communication areas in the Hehuang Valley. This paper can provide some useful information of the toponyms for the study of multi-ethnic integration, population migration, and cultural inheritance in Hehuang Valley. [ABSTRACT FROM AUTHOR]

Due to the policy of balancing the occupation and compensation of cultivated land and uneven regional economic development in China, the cultivated land tends to move from developed area to undeveloped area. China's undeveloped regions are mainly located in the west, where the climate is more arid and the soil is more barren, and more agrochemical inputs such as fertilizers and mulch films are needed to ensure grain production. Therefore, the westward shift of cultivated land may bring about even faster westward shift of agricultural chemicals, which poses great danger to the already fragile ecological environment in the western region. However, the current research mainly focuses on the spatio-temporal changes of cultivated land, and the research on the environmental effect brought by the spatial movement of cultivated land is still lacking. Based on the cultivated land data and corresponding agrochemical inputs at the provincial level from 2000 to 2020, spatio-temporal statistical models were used to analyze the evolution of cultivated land distribution patterns and the super-environmental effect. The following results were found: (1) the gravity centers of China's cultivated land area moved to the northwest, with corresponding average annual moving speeds of 1.67 km year−1 during the study period; (2) the gravity centers of agrochemical inputs were also moved westward or north-westward and showed even higher speeds than that of cultivated land area, i.e., mulch film (14.93 km year−1) > fertilizer (6.69 km year−1) > pesticide (5.59 km year−1) > agricultural diesel (3.78 km year−1) > cultivated land area (1.67 km year−1); (3) it was revealed from the spatio-temporal double-difference modeling that the westward shift of cultivated land distribution patterns had increased the relative agrochemical inputs per area in the west, which explained why the westward shift of agrochemical inputs was faster than that of cultivated land. This study has enriched the existing ecological policy evaluation methods theoretically, revealed the super-environmental effect brought by the westward shift of cultivated land patterns under the current policy background, and confirmed that the westward shift of cultivated land will bring the pressure of agricultural non-point source pollution to the western region, which may lead to the destruction of the ecological environment in the western region. In practice, it can provide a decision-making reference for rational agrochemical inputs in the process of grain cultivation and protection of agricultural ecological environment in western China. [ABSTRACT FROM AUTHOR]

This article calculates the indices for high-quality economic development and water resource systems across 25 cities in the Yangtze River Delta from 2011 to 2021. Utilizing a multifaceted analytical framework comprising the CRITIC method, standard deviation ellipse, harmonious development coefficient, and coupling coordination coefficient, we investigate spatiotemporal evolutionary trends and overarching harmonious development states between the two systems. Results indicate: (1) Throughout the research period, mean values of high-quality economic development indices fluctuated within the range of 0.05 to 0.68, while water resource carrying capacity indices oscillated between 0.18 and 0.81. (2) The epicenter of high-quality economic development indices is situated in the periphery of Lake Tai, whereas the fulcrum of the water resource system indices is located in Huzhou City, both displaying a northwest-southeast orientation. (3) Coupling coordination development exhibits a propitious advancement trajectory, with certain locales attaining exemplary coordinated growth. [ABSTRACT FROM AUTHOR]

As an important mode of transportation for the global trade, waterborne transportation has become a priority option for import and export trade due to its large load capacity and relatively low cost. Meanwhile, shipping safety has been highly valued. By collecting technological water traffic accident data from the EM-DAT database, the spatiotemporal distribution and evolution characteristics were investigated in Asia since 2000. The methods of gravity center and standard deviation ellipse analysis were utilized to determine the spatial and data-related characteristics of water traffic accidents. Temporally, the results indicated that accidents occurred most frequently during the seasons of autumn and winter, leading to a significant number of casualties. Spatially, both South-eastern Asia and Southern Asia emerged as regions with a high frequency of water traffic accidents, particularly along the borders of Singapore, Malaysia, Indonesia, and the Bay of Bengal region. In addition, the Daniel trend test and R/S analysis were conducted to demonstrate the evolution trend of accidents across various regions and seasons. The present study provides guidance for improving marine shipping safety, emergency resource management, and relevant policy formulation. [ABSTRACT FROM AUTHOR]

The fall webworm (FWW), H. cunea (Drury) (Lepidoptera: Erebidae: Arctiidae), is an extremely high-risk globally invasive pest. Understanding the invasion dynamics of invasive pests and identifying the critical factors that promote their spread is essential for devising practical and efficient strategies for their control and management. The invasion dynamics of the FWW and its influencing factors were analyzed using standard deviation ellipse and spatial autocorrelation methods. The analysis was based on statistical data on the occurrence of the FWW in China. The dissemination pattern of the FWW between 1979 and 2022 followed a sequence of “invasion-occurrence-transmission-outbreak”, spreading progressively from coastal to inland regions. Furthermore, areas with high nighttime light values, abundant ports, and non-forested areas with low vegetation cover at altitudes below 500 m were more likely to be inhabited by the black-headed FWW. The dynamic invasion pattern and the driving factors associated with the fall webworm (FWW) provide critical insights for future FWW management strategies. These strategies serve not only to regulate the dissemination of insects and diminish migratory tendencies but also to guarantee the implementation of efficient early detection systems and prompt response measures.

This paper first determines the research method of rural tourism and the selection of research objects and carries out the corresponding pre-processing operation for the data. Secondly, the spatial distribution characteristics of key villages of rural tourism are analyzed by using the nearest neighbor index, standard deviation ellipse, geographic concentration index and geographic detector so as to understand the development of rural tourism in the five regions of east, west, south, north and central. The spatial clustering structure of key villages in rural tourism is calculated again using the fractal model to explore grid aggregation and correlation of high-quality development in rural tourism. From the spatial distribution characteristics, the nearest neighbor index of the southern region is 0.838, showing an aggregation-random distribution pattern, and the standard deviation ellipse of the southern region is 51.67°. From the spatial clustering structure, the aggregation dimension of the southern region is 0.485, and the correlation dimension of the four regions of east, west, south, north and south is relatively close to that of highway accessibility, for example. Thus, rural tourism in the context of the Internet needs to further strengthen infrastructure construction, enhance the means of training high-quality personnel, build diversified marketing channels, and realize the rural revitalization strategy to boost rural tourism.

Based on remote sensing images from National Polar-orbiting Partnership—Visible Infrared Imaging Radiometer Suite–like data and related statistical yearbook data acquired at 5-year intervals from 2000 to 2020, the urbanized areas of cities in Anhui Province, China, were extracted. The characteristics of their spatial and temporal expansion were analyzed in combination with the migration path of the urban center of gravity along with measures of the speed and intensity of urban expansion. In addition, the urban development trends in Anhui were evaluated by combining a nighttime light index with spatial autocorrelation and local autocorrelation methods to reveal the characteristics of the level of urban development and internal structural changes in each city in Anhui. The results show that the cities in Anhui are concentrated in two belt areas in the Yangtze and Huai river basins, and that they expanded outward, with several original urbanized areas as the center. The rate of urban expansion reached its lowest point during 2005–2010 and peaked during 2015–2020. The urbanized areas in Anhui were distributed in a northwest–southeast direction, while the center of urban gravity remained in Hefei City during the study period. The total amount of nighttime light in Anhui’s urbanized areas increased by nearly 10 times over 20 years, with the period of 2010–2020 experiencing particularly high increases in nighttime light. The grayness values of urban lights in each period show clear spatial correlation.

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Water and soil resources are the key elements required to maintain the stability and sustainable development of oases in inland drylands. This study takes oases in Xinjiang as an example, and reveals the spatial and temporal distribution characteristics of oases across Xinjiang, as well as the dynamic migration and transformation process of oases and the mutual influence of human activities on oasis resources, through a combination of land movement and attitude indicators, use of a gravity model, and Geodetector. The results show that: (1) the area containing the oases in the study has expanded, increasing by 24.0% between 1990 and 2020; (2) both artificial oases (AO) and natural oases (NO) were tilted in a northeast–southwest direction, with the center point of AOs moving slightly to the northeast, and the centripetal force and dispersion degree did not change significantly; the center point of NO moved significantly to the northeast, and the dispersion degree weakened, showing spatial convergence; (3) cultivated land and grassland were the main land types of oasis evolution, and their contribution to evolution was over 70%; and (4) the Geodetector results show that the three main factors driving the evolution of oases were vegetation cover, population density, and GDP. The research results have practical implications for land-use management planning and ecological environmental protection in arid zones. [ABSTRACT FROM AUTHOR]

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Rapid economic and social development has triggered competition for limited land space from different industries, accelerating the evolution of Beijing's urban landscape types. The increase in impermeable surfaces and the decrease in ecological land have led to an increase in the impact on the urban thermal environment. Since previous studies have mainly focused on the impact of a single urban landscape on the urban thermal environment and lacked an exploration of the combined impact of multiple landscapes, this study applied standard deviation ellipses, Pearson correlation analysis, land surface temperature (LST) profile analysis, and hot spot analysis to comprehensively explore the influence of the evolving production–living–ecological space (PLES) pattern on LST. The results show that the average LST of various spaces continued to increase before 2009 and decreased slowly after 2009, with the highest average temperature being living space, followed by production space, and the lowest average temperature being ecological space for each year. The spatiotemporal shift path of the thermal environment is consistent with the shift trajectory of the living space center of gravity in Beijing; LST is positively correlated with living space (LS) and negatively correlated with production space (PS) and ecological space (ES). LST is positively correlated with LS and negatively correlated with PS and ES. Influenced by the change in bedding surface type, the longitudinal thermal profile curve of LST shows a general trend of "low at both ends and high in the middle". With the change in land space type, LST fluctuates significantly, and the horizontal thermal profile curve shows a general trend of "first decreasing, followed by increasing and finally decreasing". In addition, the hot spot analysis shows that the coverage area of very hot spots, hot spots, and warm spots increased by 0.72%, 1.13%, and 2.03%, respectively, in the past 30 years, and the main expansion direction is southeast, and very cold spots and cold spots are distributed in the northwest ecological space, and the area change first decreases and then increases. [ABSTRACT FROM AUTHOR]

In order to accurately grasp the temporal and spatial characteristics of the development of water conservancy scenic spots of nine provinces (regions) in the Yellow River Basin, taking 356 water conservancy scenic spots of nine provinces (regions) in the Yellow River Basin as the research object, comprehensively using spatial autocorrelation analysis, kernel density analysis, standard deviation ellipse and geographic detector to analyze the spatial and temporal differentiation characteristics and influencing factors of water conservancy scenic spots of nine provinces (regions) in the Yellow River Basin. The results show that from 2001 to 2021, the number of water conservancy scenic spots of nine provinces (regions) in the Yellow River Basin shows a rapid growth trend, and the spatial distribution has experienced a process of evolution from low-value areas to middle-value areas and high-value areas. The water conservancy scenic spots of nine provinces (regions) in the Yellow River Basin have a positive correlation in space, showing a significant spatial distribution pattern of agglomeration, and the degree of agglomeration continues to increase. The nuclear density is characterized by a “Xing”-shaped distribution, showing a spatial evolution pattern with the middle and lower reaches of the Yellow River as the core agglomeration area, and the agglomeration difference gradually expands from the middle reaches to the lower reaches. The distribution pattern of the cold and hot spots is “cold in the west and hot in the east”, which shows a trend of continuous expansion of the cold spot area and stable change of the hot spot area. The distribution direction is in the spatial trend of “east (slightly north) -west (slightly south) ”.The spatial differentiation of water conservancy scenic spots of nine provinces (regions) in the Yellow River Basin is the result of the combined action of multiple factors. The economic level is the dominant factor, the traffic condition is the key factor, and the natural condition is the relevant factor. [ABSTRACT FROM AUTHOR]

Agriculture comprises a complex greenhouse gas source and sink system. Different regions and planting and breeding conditions lead to two types of carbon sources or sinks in the agricultural systems. Identifying the characteristics of carbon emissions in agricultural systems and influencing factors is of great significance to achieve green agricultural development, which will also provide a data basis to promote the realization of “carbon peak” and “carbon neutrality” goals. Taking the Hexi Corridor as an example, we calculated and analyzed the spatial and temporal characteristics of agricultural carbon emissions and influencing factors in 20 counties in the Hexi region from 2000 to 2020. The following results were obtained：from 2000 to 2020, agricultural carbon emissions in Hexi showed a slow increase. The regions with the largest agricultural carbon emissions were Liangzhou District and Ganzhou District, accounting for 31.74% of the total agricultural carbon emissions in Hexi. From the perspective of planting and stockbreeding, the planting industry in the Hexi region was determined to be a carbon sink, with carbon absorption of 1.41×108 t, and stockbreeding was considered a carbon source, with carbon emissions reaching 4.17×107 t. From 2000 to 2020, the net carbon emissions of agriculture in Hexi showed fluctuations, but the overall trend was decreasing, and the agricultural system changed to carbon sinks. In the planting industry, the factor with the greatest impact on agricultural carbon emission was determined to be planting scale, and in regions with stable scale development, the factor with the greatest impact was found to be the mechanization degree. The main influencing factors for smaller regions were the rural electricity consumption. In the agricultural area with a large scale and high proportion of stockbreeding industry, the most influential factor was the stockbreeding scale, and the correlation degree was greater than 0.9. From 2000 to 2020, the agricultural carbon emission intensity in the Hexi region showed a process of random distribution to significant aggregation, and the center of agricultural carbon emission shifted slowly to the southeast, but only in Zhangye City. [ABSTRACT FROM AUTHOR]

The spatiotemporal patterns of residential and supporting service facilities are critical to effective urban planning. However, with growing urban sprawl and congestion, the spatial distribution patterns and evolutionary characteristics of these areas show significant uncertainty. This research was conducted for six phases from 2012 to 2022, incorporating datasets of point of interest (POI) data for residential areas and transportation facilities (RATFs) and OpenStreetMap (OSM) data. Using exploratory spatial data analysis (ESDA) and standard deviation ellipse, we investigated the spatiotemporal patterns and directional characteristics of RATFs in Xi'an, as well as their evolution and underlying causes. The analysis demonstrated that: (1) The spatial distribution of RATFs in Xi'an exhibits non-uniform and gradually evolving patterns, with significant spatial agglomeration characteristics over the past decade. Residential areas (RAs) exhibit a spatial autocorrelation that is high in the middle and low in the surrounding areas, while transportation facilities (TFs) exhibit spatial patterns that are high in the southern and low in the northern areas. (2) Overall, the number of RATFs has continued to increase, and they exhibit significant spatial autocorrelation. Specifically, the trend of RAs concentrating in the central city has become increasingly prominent, while TFs have expanded from the center to the north. (3) Furthermore, from the perspective of supply–demand matching, this study proposes targeted adjustment strategies for the distribution of RATFs. It provides significant references for the optimization of service facilities and provides new ideas and practical experience for urban spatial analysis methods based on multi-source data. [ABSTRACT FROM AUTHOR]

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In the strategic context of promoting the comprehensive revitalization of Northeast China, green innovation, as the integration of the two development concepts of innovation-driven and green development, has become an essential means to promote sustainable and high-quality development in Northeast China. By constructing the Super-SBM model with undesired output and the Global Malmquist-Luenberger index model, the green innovation efficiency and green innovation total factor productivity of 34 prefecture-level cities in Northeast China from 2011 to 2020 are measured. Then the natural break point classification method, standard deviation ellipse and Dagum Gini coefficient decomposition method are used to explore their spatial and temporal evolution characteristics. Based on the measured results of green innovation efficiency and green innovation total factor productivity in Northeast China, all the cities are classified into four types: high-high, high-low, low-high and low-low. The study results show that the green innovation efficiency (GIE) of cities in the northeast region shows an excellent upward trend, and the distribution pattern of “strong in the North and weak in the South” is more prominent. The green innovation total factor productivity shows a fluctuating decline, and technical efficiency and technological progress inhibit the improvement of green innovation efficiency. The centre of gravity of efficiency has generally migrated towards the southwest, green innovation efficiency among cities has gradually tended to develop in a balanced manner, and inter-provincial differences are the primary source of spatial differences in green innovation efficiency. The study concludes that the northeast region should continuously improve its green innovation resource allocation capacity, accelerate the green transformation and upgrading of industrial structure, clarify green innovation subjects, optimize the green innovation environment and formulate differentiated development strategies to promote the synergistic development of green innovation among cities.

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Based on Panel data collected from 2011 to 2020 targeted to 50 prefecture-level cities in the Yellow River Basin, this paper adopted standard deviation ellipse and spatial Dubin model to explore the nonlinear effects and spatial spillover effects of urbanization on air pollution and ecological resilience in the Yellow River Basin. The results show that the degree of air pollution in the southeast of the Yellow River Basin is higher than that in the northwest of the Yellow River Basin, the distribution range of air pollution is shrinking, the concentration of ecological resilience is enhanced, and the ecological environment is developing for the better. There is a significant U-shaped relationship between urbanization and air pollution in the Yellow River Basin, and an inverted U-shaped relationship between urbanization and ecological resilience. For every 1% increase in urbanization, air pollution decreases by 0.0873%, ecological resilience increases by 0.4046%. For every 1% increase in the square term of urbanization, air pollution increases by 0.2271%, ecological resilience decreases by 0.1789%. The urbanization of the Yellow River Basin has a spatial spillover effect on air pollution and ecological resilience, and urbanization has a significant negative impact on the ecological environment of neighboring cities. The robustness of the above conclusions is verified by introduce an inverse distance weight matrix replacing the spatial weight matrix. [ABSTRACT FROM AUTHOR]

Scientific evaluation of urbanization quality is of great significance to measure the level of urban development and promote sustainable urban development. Based on the two dimensions of urban development and urban environmental quality, an evaluation index system of urbanization quality in Liaoning province was constructed, and methods including entropy weight, standard deviation ellipse and geographic detector were comprehensively used to explore the urbanization quality and its spatial distribution, spatial evolution trend and influencing factors in Liaoning province. The results show that, from 2005 to 2019,the overall urbanization quality index increased from 2.74 to 4.74,of which the quality of economic urbanization subsystem had the largest increase, the quality of social urbanization and environmental governance subsystem had an obvious upward trend, and the quality of environmental state and environmental pressure subsystem was relatively stable. For the spatial distribution of urbanization quality, the index ranged from 0.087 to 0.740 for Liaoning’s cities, with Shenyang as the “big core” and Dalian as the “small core” of regional agglomeration. The center of gravity ellipse of urbanization quality standard deviation fell on Liaoyang, and the deflection trajectory was along southeast-northwest-southwest from 2005 to 2019,with annual increasing distance and speed of the center of gravity ellipse of standard deviation. Among all the subsystems, economic urbanization, social urbanization and environmental management posed more influence on urbanization quality in Liaoning province; specifically, main influencing indexes included urbanization area, fixed assets investment, number of people participating in primary pension insurance, number of college students per ten thousand people, and capacity of domestic garbage removal and urban sewage treatment, which played growing influence on urbanization quality. [ABSTRACT FROM AUTHOR]

The urban heat island (UHI) environment is closely related to the daily life of residents, and the impact of UHI is further expanding in the era of rapid urbanization, which is particularly obvious in the Beijing-Tianjin-Hebei urban agglomeration and Guangdong-Hong Kong-Macao Greater Bay Area (GBA). To explore the connection between UHI and urban expansion, this study takes GBA as the study area, based on Google Earth Engine platform and Landsat satellite data. The urban-rural temperature difference method was used to analyze the heat island zoning in the GBA from 2000 to 2020, and the direction and type of urban expansion in the GBA were investigated by standard deviation ellipse and LEI, to explore the link between the type of urban expansion and the heat island region through geospatial analysis methods. The results of the study show that: (1) The proportion of the area of strong and extreme heat islands in the GBA was 37.64% in 2000; 38.61% in 2005; 47.07% in 2010; 55.76% in 2015; and finally 59.69% in 2020. The proportion of the area of heat island regions in the period from 2000 to 2020 showed an overall increasing trend, with the largest increase in heat island regions in the period from 2015 to 2020. (2) The intensity of urban expansion in the GBA is 32% in both 2000–2005 and 2005–2010, which is significantly higher than the 9% in 2010–2015, and then increases to 24 per cent in 2015–2020. The speed of movement of urban centroids decreases in 2000–2015 and increases in 2015–2020. The direction of urban expansion in the first 5 years is dominated by the northeast, and the direction of urban expansion in the latter 15 years is generally dominated by the southwest, and the type of urban expansion is dominated by the fringe type, with the enclave type of expansion accounting for a smaller proportion. (3) Pearson correlation analysis further confirms that there is a significant positive correlation between urban sprawl and the urban heat island effect, with a correlation coefficient of 0.78 and a p-value of 0.041. There is a high degree of spatial consistency between the distribution of built-up urban areas and the distribution of heat island areas in GBA, and the direction of the evolution of the urban heat island areas is the same as the direction of the evolution of the built-up urban areas in general, and the thermal response of the marginal expansion to the ground surface temperature is stronger than that of enclave expansion. The thermal response to the surface temperature is stronger than that of the enclave type of expansion.

As an important mode of transportation for the global trade, waterborne transportation has become a priority option for import and export trade due to its large load capacity and relatively low cost. Meanwhile, shipping safety has been highly valued. By collecting technological water traffic accident data from the EM-DAT database, the spatiotemporal distribution and evolution characteristics were investigated in Asia since 2000. The methods of gravity center and standard deviation ellipse analysis were utilized to determine the spatial and data-related characteristics of water traffic accidents. Temporally, the results indicated that accidents occurred most frequently during the seasons of autumn and winter, leading to a significant number of casualties. Spatially, both South-eastern Asia and Southern Asia emerged as regions with a high frequency of water traffic accidents, particularly along the borders of Singapore, Malaysia, Indonesia, and the Bay of Bengal region. In addition, the Daniel trend test and R/S analysis were conducted to demonstrate the evolution trend of accidents across various regions and seasons. The present study provides guidance for improving marine shipping safety, emergency resource management, and relevant policy formulation.

Global warming caused by carbon emissions has become a significant concern for countries worldwide. This study thoroughly examines the spatiotemporal patterns and spatial spillover effects of carbon emissions in China. This research employs kernel density estimation, Moran's index, and the standard deviation ellipse model to analyse the spatiotemporal evolution of carbon emissions in China while utilizing the spatial Durbin model to explore the spatial spillover effects of the digital economy on carbon emissions. The subsequent findings are derived from the following: (1) China's carbon emissions are characterized by substantial spatial and temporal agglomeration. Low carbon emissions are in the eastern littoral regions, while high carbon emissions are concentrated in the inland areas, such as the northwest. The local Moran index suggests that high-high and low-low clustering patterns characterize China's carbon emissions. (2) The spatial trends and evolutionary characteristics of carbon emissions in China are readily apparent. During the sample period, the carbon emission level in the east and west was significantly higher than in the central region, and the gap between the areas was progressively narrowing. The results of the standard deviation ellipse indicate that China's carbon emissions are undergoing a substantial discrete phenomenon in their spatial distribution. (3) Digital economies reduce carbon emissions, have regional spillover effects, and reveal geographical variance across eastern, central, and western regions. This study offers quantitative evidence for integrated nationwide and regional emission reduction and carbon mitigation strategies, as well as for region-specific emission reduction programs., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)