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Urban park green areas are part of territorial space planning, shouldering the mission of providing residents with high-quality ecological products and public space. Using a combination of several measurement models such as the BCG (Boston Consulting Group) matrix, ESDA (Exploratory Spatial Data Analysis), MLR (Machine Learning Regression), GWR (Geographically Weighted Regression), and GeoDetector, this paper presents an empirical study on the changes in Urban Park Green Areas (UPGAs) in the Grand Canal of China. By quantitatively measuring the spatio–temporal evolution patterns of UPGAs, this study reveals the driving mechanisms behind them and proposes policy recommendations for planning and management based on performance evaluation. The spatio–temporal evolution of UPGAs and their performance in China's Grand Canal are characterized by significant spatial heterogeneity and correlation, with diversified development patterns such as HH (High-scale–High-growth), HL (High-scale–Low-growth), LH (Low-scale–High-growth), and LL (Low-scale–Low-growth) emerging. The evolution performance is dominated by positive oversupply and positive equilibrium, where undersupply coexists with oversupply. Therefore, this paper recommends the implementation of a zoning strategy in the future spatial planning of ecological green areas, urban parks, and green infrastructure. It is also recommended to design differentiated construction strategies and management policies for each zoning area, while promoting inter-city mutual cooperation in the joint preparation and implementation of integrated symbiosis planning. Furthermore, the spatio–temporal evolution of the UPGAs in the Grand Canal of China is influenced by many factors with very complex dynamic mechanisms, and there are significant differences in the nature, intensity, spatial effects, and interaction effects between different factors. Therefore, in the future management of ecological green areas, urban parks, and green infrastructure, it is necessary to interconnect policies to enhance their synergies in population, aging, industry and economy, and ecological civilization to maximize the policy performance. [ABSTRACT FROM AUTHOR]

New urbanization in counties and the logistics industry are closely related and are essential in promoting regional economic and social development. There are specific challenges and obstacles to revealing the interaction mechanism and system state measurement between the two. This paper explains the two coupling mechanisms and constructs the evaluation index system. It proposes a new analysis method based on the coupling coordination degree model, the spatio-temporal evolution analysis, and the grey prediction model. The goal is to learn more about and fully realize the coordinated development mechanisms of the two. It then uses the Hebei province of China as an example to empirically analyze its systematic cross-sectional data from 2013 to 2022. Research findings: (1) In Hebei province, the new urbanization in counties and the logistics industry have a systematic coupling relationship. However, the logistics industry's comprehensive development level is relatively lagging. The two systems have been at a high-level coupling stage for the last decade and maintain a high coupling status. The coupling coordination has shown significant improvement. (2) Although the geographical distribution of the coupling and coordination degree of the new urbanization in counties and logistics industry system has short-term volatility, it is still stable in the long term and presents economic-related spatial characteristics. (3) Over the next five years, the coupling coordination of 11 cities in Hebei province will steadily grow. There will be greater harmonization between the two systems. (4) From the analysis results, the evaluation index system of the coupled system constructed is scientific and reasonable. The analysis method can not only measure the system's coupling degree, but it can also predict the development trend and analyze the spatial evolution. The technique has novelty and validity, which can be used as a reference for analyzing and making decisions about similar systems. [ABSTRACT FROM AUTHOR]

Ecosystems are undergoing continuous degradation due to the dual perturbation of global climate change and human activities, posing unprecedented threats and challenges to the ecosystem services they provide. To gain a deeper understanding of the spatio-temporal evolution of ecosystem service value (ESV), it is essential to accurately capture the characteristics of its spatial and temporal changes and its influencing factors. However, traditional spatio-temporal statistical methods are limited to analyzing the heterogeneity of ESV in a single temporal or spatial dimension, which fails to meet the comprehensive analysis needs for spatio-temporal heterogeneity over an extended continuum. Therefore, this paper constructs a Bayesian spatio-temporal hierarchical model to analyze the ESV heterogeneity in both temporal and spatial dimensions in Northeast China from 2000 to 2020 to accurately identify the regions with unstable fluctuations in ESV and analyze the influencing factors behind them. It aims to comprehensively and systematically reveal the intrinsic laws of spatio-temporal evolution of ESV, and provide a scientific basis for relevant decision-making. The study found a continuous fluctuating downward trend of ESV in Northeast China from 2000 to 2020, with significant spatial and temporal heterogeneity. Notably, the distribution of hot and cold spots is regularly concentrated, especially in the transition zone from low hills to plains, which forms an "unstable zone" of spatial and temporal fluctuations of ESV. Natural factors such as NDVI and NPP exhibit a significant positive correlation with ESV, while social factors like population density and GDP show a strong negative correlation. Compared to traditional statistical methods, the Bayesian spatio-temporal hierarchical model, with its outstanding flexibility and accuracy, provides a new perspective and way of thinking for analyzing classical spatio-temporal problems. Firstly, the model examines time and space as a whole and fully accounts for the influence of spatio-temporal interactions on ESV. Secondly, the Bayesian spatio-temporal hierarchical model meets the needs of long-term continuous ESV outcome detection, which provides us with solid support for a deeper understanding of the evolution of ESV. [ABSTRACT FROM AUTHOR]

With the increase in regional economic development disparities, a regional coordinated development strategy is put forward that prioritizes human welfare and holistic social progress over a purely materialistic growth model. To address the challenges of balanced regional development, this paper has developed a multidimensional assessment framework of social development encompassing education, healthcare, culture, and social security. Using the entropy weight TOPSIS method, this study measures the social development level across 296 Chinese prefecture-level cities from 1990 to 2020. It explores the spatio-temporal evolution characteristics of China's social development level through the Dagum Gini coefficient decomposition method and exploratory spatial data analysis. The results indicate that (1) the level of social development in China exhibits a fluctuating upward trend over the time series, showing a phase-wise pattern of decline–rise–rise; (2) there is a clear heterogeneity in the level of social development, with a general hierarchy of Eastern, Northeastern, Western, and Central regions in terms of social development; (3) spatially, China's social development level has evolved from a patchy distribution in 1990 to a clustered distribution around urban agglomerations by 2020, with pronounced characteristics of spatial imbalance; (4) the level of social development in China displays varying degrees of spatial clustering, with this trend intensifying over time; and (5) over the period 1990–2020, the overall disparity in China's social development level presents a fluctuating trend, with a notable reduction after an initial increase, and regional disparities following the order of Central, Western, Eastern, and Northeastern regions. This research offers valuable insights for policymakers and scholars seeking to understand and enhance China's social development landscape. [ABSTRACT FROM AUTHOR]

Background: The precise allocation and efficient use of industrial land are necessary for the development and optimization of urban production space; however, the mismatches between urban industrial land consumption and the growth of manufacturing are becoming more serious and has become the primary obstacle to sustainable urban development. Methods: Based on a combination of the Boston Consulting Group matrix, spatial mismatch model, decoupling index, GIS, and Geodetector tools, this paper conducts an empirical study on the Yangtze River Delta region in an attempt to reveal the spatio-temporal evolution of the mismatch between urban industrial land changes and the growth of manufacturing and provide a basis for spatial planning and land management in the new era. Results: The distribution of urban industrial land is characterized by high heterogeneity and agglomeration, the coexistence of expansion and contraction, and increasingly complex and diversified changes. Gross domestic product, government revenue, the added value of tertiary industry, and government investment in science and technology indicate that the goal orientation and scale effect of economic growth play a decisive role in the allocation of urban industrial land and that the influence of industrial structures and technological innovation is rapidly increasing. The interaction between the different factors is a bifactor enhancement, for example, land used for logistics and storage, utilities, commercial and other services, and the import and export trade, which have a strong synergistic enhancement effect. The mismatches between urban industrial land changes and the growth of manufacturing are still within a reasonable degree but there is an increasing number of cities with negative mismatches, making it necessary to implement a differentiated spatial adjustment and management policy. Conclusions: Compared with the mismatches of mobile resources such as labor, finance, and capital, the mismatches of immovable land resources have an increasing impact with more serious consequences and it is harder to make optimizations and corrections. However, the academic community has limited knowledge about land resource mismatches. By quantitatively assessing the mismatches between industrial land consumption and the growth of manufacturing in YRD cities, this paper argues that the mismatches can be rectified through spatial and land use planning and suggests the establishment of a zoning management and governance system to achieve the optimal allocation of urban industrial land resources through the implementation of a "standard land + commitment system" and industrial land protection lines. [ABSTRACT FROM AUTHOR]

Shrinking cities are a global issue with regional characteristics. This paper focuses on the county-level administrative units in the Three Northeastern Provinces in China to identify and classify shrinking cities using a two-step identification method and explores their spatial-temporal evolution. The paper utilizes the panel threshold regression model for empirical testing. The results indicate the following: (1) The number of shrinking cities in the region is large and deep. Quantitatively, the shrinking cities account for about 50% of the whole; spatially, there are six major shrinking city "groups", showing the distribution trend around the "Ha-Da" urban corridor. (2) The threshold effect test reveals that GDP is a critical threshold variable influencing the formation of shrinking cities. Moreover, cities are classified into three types based on the threshold values: Type I (GDP > 2,270,731 yuan), Type II (434,832 < GDP ≤ 2,270,731), and Type III (GDP < 434,832). (3) The results of the dual-threshold and grouped regression models show significant variations in the dominant factors of shrinking cities of different scales. Variables such as impervious area, fiscal revenue, and grass area demonstrate relatively stable promoting effects. [ABSTRACT FROM AUTHOR]

In the political context of "carbon peaking" and "carbon neutrality" proposed by the Chinese government, this paper investigates the spatio-temporal evolution of land use transition in China after the implementation of the carbon emission trading scheme (CETS). Based on the analysis of the spatio-temporal evolution, we discuss the spatial spillover of the policy effects. With the help of China's CETS policy, this study explores the above issues with the main observation samples of the six provincial pilots included in CETS. Using the entropy weighting method, the indicator construction method, and local Moran's I test, this paper takes 30 provincial areas in China from 2010 to 2017 as the full sample, and draws the following conclusions: (1) both the economic and environmental effects generated by CETS can optimize land use transition in the pilot areas, but the effective time points of the two are different; (2) the time for land use transition to be optimized by the two effects of CETS is different, among which the economic effect takes effect faster than the environmental effect; and (3) there is spatial spillover of the optimization effect of CETS on land use transition, but the specific effect depends on the industrial structure and development plan of the pilot areas. [ABSTRACT FROM AUTHOR]

The Chinese "New Normal" economic model is a national strategy for adapting to sustainable development and offers important implications for the development of new economies. The "New Normal" economic model aims at improving the use efficiency of land resources in the framework of sustainable development. A discussion of the spatio-temporal evolution of land resource use efficiency (LRUE) in urban built-up areas can help in better assessing LRUE. In this paper, the super-efficiency slack-based measure (Super-SBM) method and spatial econometric models are used to study 281 prefecture-level cities in China between 2004 and 2020. Further, this paper explores the relationship between economic agglomeration and LRUE, which is of great value in managing land resources. The results show that there is a spatial spillover in LRUE and a U-shaped relationship between it and economic agglomeration. [ABSTRACT FROM AUTHOR]

Population shrinkage has had a certain negative impact on urban and rural development in many aspects. The impact of population shrinkage on urban–rural integration has become one of the core scientific issues that needs to be addressed in the current research on promoting the goal of common prosperity in China. Northeast China is a typical region in China that is experiencing a decrease in population and economic activity. Investigating the integrated development of urban and rural areas in this region is highly important for revitalizing Northeast China. This research paper focuses on 32 prefecture-level cities in Northeast China and utilizes spatial correlation analysis and the Geographical Weighted Regression model to uncover the evolving spatial patterns and influential factors affecting integrated urban–rural development in the context of population decline. The findings revealed the following: (1) The level of integrated urban–rural development in Northeast China continues to rise despite the shrinking population. During the comprehensive population decline stage, the growth rate of the urban–rural coupling coordination degree surpasses that of the initial stage. The areas with high values of urban–rural coupling coordination degree shift from northeastern Heilongjiang to four sub-provincial cities. The spatial correlation between urban–rural coupling and coordinated development weakens, with the main type being low–low agglomeration. (2) Factors such as economic development level, labor force size, urbanization level, level of openness, urban–rural accessibility, and proportion of built-up areas significantly correlate with urban–rural coupling and coordination. The influence of each factor varies in magnitude and direction across different locations. Labor force size and urban–rural accessibility have the most-significant impact on integrated urban–rural development, with labor force size having a positive effect and urban–rural accessibility having a negative effect. The impact of the economic development level follows a pattern of initial increase and subsequent decrease as the population shrinks. (3) Although population decline does not hinder integrated urban–rural development in Northeast China, it is closely connected to changes in the factors influencing such development. To capitalize on the development opportunities presented by national policies, Northeast China should adopt a model of urban–rural development that promotes rural growth through cities. This entails attracting talented individuals to return, enhancing the flow of urban–rural development elements in both directions, and creating a spatial development pattern characterized by "big city, big agriculture, and big ecosystem". By doing so, the revitalization of Northeast China can be achieved. [ABSTRACT FROM AUTHOR]

Background: Desertification is one of the main obstacles to global sustainable development. Monitoring, evaluating and mastering its driving factors are very important for the prevention and control of desertification. As one of the largest deserts in China, the development of desertification in Otindag Sandy Land (OSL) resulted in the reduction in land productivity and serious ecological/environmental consequences. Although many ecological restoration projects have been carried out, the vegetation restoration of OSL and the impact mechanism of climate and human activities on desertification remain unclear. Methods: Taking OSL as the research area, this paper constructs the desertification index by using the remote sensing images and meteorological and socio-economic data, between 1986 and 2016, and analyzes the spatio-temporal evolution process and driving factors of desertification by using trend analysis and spearman rank correlation. Results: The results showed that: (1) Desertification in the OSL has fluctuated greatly during the past 30 years. Desertification recovered between 1986 and 1990, expanded and increased between 1990 and 2000, reduced between 2000 and 2004, developed rapidly between 2004 and 2007, and recovered again between 2007 and 2016; (2) The desertification of OSL is dominated by a non-significant change trend, accounting for 73.27%. In the significant change trend, the area of desertification rising trend is 20.32%, which is mainly located in the north and east, and the area of declining trend is 6.41%, which is mainly located in the southwest; (3) Desertification is the result of the superposition of climate and human activities. Climate change is the main influencing factor, followed by human activities, and the superposition effects of the two are spatio-temporal differences. Conclusions: These results shed light on the development of desertification in OSL and the relative importance and complex interrelationship between human activities and climate in regulating the process of desertification. Based on this, we suggest continuing to implement the ecological restoration policy and avoid the destruction of vegetation by large-scale animal husbandry in order to improve the situation of desertification. [ABSTRACT FROM AUTHOR]

Land use change is closely related to the terrestrial ecosystem. Studying the relationship between land use and ecosystem service carbon storage under future climate change can optimize the regional ecosystem service function and formulate sustainable social and economic development policies, which is of great significance for regional carbon emission management and climate change response. In this paper, the coupled model of SSP-RCP-PLUS-InVEST was constructed to simulate land use change under different scenarios, analyze the influence degree of driving factors on different regions, and explore the spatio-temporal evolution and spatial correlation of carbon storage, taking Central Yunnan City agglomeration as an example. The results showed that: (1) from the perspective of land use change, the overall changes in SSP126 and SSP245 scenarios were similar, and the change rates of different types were slightly different. Under the SSP585 scenario, the forest area decreased, and the urban land and cropland land expanded. (2) Under the three scenarios in the future, the decrease in total carbon storage is the most serious under the SSP245 scenario, and the decrease is the most serious under the SSP585 scenario. (3) Comparative spatial correlation: the carbon storage in the Central Yunnan urban agglomeration is generally correlated among counties, and there is no significant difference under the future scenarios, showing a high accumulation pattern in the east and low accumulation pattern in the middle. In general, reasonable planning of land spatial patterns and increasing the proportion of forest is conducive to the proportion of regional carbon sequestration capacity. The research methods can provide references for addressing climate change and territorial spatial planning. [ABSTRACT FROM AUTHOR]

Carbon density change and land use change are important factors in the spatiotemporal evolution of ecosystem carbon stock. Accurately assessing regional carbon stock and analyzing its relationship with land use patterns and carbon density change are of great value to regional ecosystem protection and sustainable social and economic development. In order to effectively evaluate the carbon stock in North China, this study divided the target area into 5 sub-regions, and a variety of methods were used to calculate the carbon density in each sub-region over different time periods. The classic InVEST model was selected to evaluate carbon stock evolution under changes in land use and carbon density from 2000 to 2015. The results show that the carbon stock in North China in 2000, 2005, 2010 and 2015 were 1.301 × 1010 t, 1.325 × 1010 t, 1.332 × 1010 t and 1.366 × 1010 t, respectively, with a cumulative increase of 6.506 × 108 t. As two main factors, the land use type change and carbon density change showed different influences on the carbon stock of different regions and different ecosystems, but the former had a greater impact in North China during 2000–2015. Converting farmland to forest and grassland and converting bare land to grassland increased carbon stock, while converting farmland to building land reduced carbon stock. In addition, the carbon density of most land use types in each sub-region increased from 2000 to 2015, which further caused the increase in carbon stock. The carbon stock in North China had a significant spatial pattern of high in the east and low in the west, and this distribution pattern is closely related to land use. This research can provide scientific reference for land use management decision-making and sustainable carbon stock function in North China. [ABSTRACT FROM AUTHOR]

Coal is one of the fundamental fossil energy supporting the world's economy. The synergistic development between efficient coal mining and ecological environment protection is the inevitable requirement for the preservation of global harmony. As the world's largest coal producer, China has conducted a strategic shift from east to west in terms of the exploitation of its energy resources, posing a serious threat to the fragile ecological environment of the western region. In particular, the surface subsidence caused by coal mining is the root of the ecological deteriotation and the destruction of ground structures. However, it is difficult to reveal the law of large-scale surface subsidence in western mining areas merely by conventional measurement methods such as leveling, on account of the high intensity of coal seam mining, the weakness of the lithology of overlying rock and the large thickness of wind-blown sand strata. In view of this, small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) technology was used in this study to obtain the time series of surface vertical displacement during the whole mining process of the 2401 working face in the Yingpanhao coal mine, Inner Mongolia. Based on the deformation data, the dynamic evolution characteristics of surface subsidence under high intensity mining in the western mining area were analyzed exhaustively. It was found that the surface subsidence is characterized by an extensive coverage range (48.52 km2) with minimal ground settlement (250 mm) in the study area. Meanwhile, the boundary shape of the subsidence basin followed a "circular-parallelogram-trapezoid" changeable process and the coverage area of the basin experienced three stages: a linear increasing period, a temporary stagnation period, and a re-expansion period. Furthermore, there existed an abnormal uplift phenomenon on the east side of the open-off cut in the 2401 working face. Combined with the structure of overlying strata, this paper carried out a preliminary analysis on the reasons of the abovementioned phenomenon. The research results are of vital realistic significance for ground buildings and ecological environmental protection in the aeolian sand mining area in Western China. [ABSTRACT FROM AUTHOR]

China's rapid urbanization drive, marked by extensive urban renewal projects, necessitates a meticulous examination of their transformational impact on the human settlement environment (HSE) across urban landscapes. This study investigates the impact of China's urban renewal progress on the spatial–temporal changes in the HSE from 2009 to 2019, using data from 40 prefecture-level cities in the Yangtze River Delta. Our findings reveal an overall positive relationship between the spatio–temporal evolution of urban renewal and the HSE, suggesting that urban renewal projects have had a beneficial impact, particularly following the announcement of China's New Urbanization policy in 2014. However, the extent of this positive impact varied among different areas, with more significant improvements observed in core cities and economically developed areas. Additionally, our study uncovered significant variations in how urban renewal influenced the HSE over time. We found that the primary influencing factor shifted from material renewal to industrial renewal. These findings offer valuable insights for improving the HSE during urban renewal processes, both in China and other regions undergoing rapid urbanization. [ABSTRACT FROM AUTHOR]

Faced with the dual challenges of ecological degradation and economic deceleration, promoting urban green high-quality development (UGHQD) is pivotal for achieving economic transformation, ecological restoration, and regional sustainable development. While the existing literature has delved into the theoretical dimensions of UGHQD, there remains a notable dearth of empirical studies that quantitatively assess its developmental levels, spatio-temporal evolution, and driving factors. This study examines 107 cities of China's five major urban agglomerations from 2003 to 2020, constructing a comprehensive evaluation indicator system for UGHQD. By employing methodologies, including the Dagum Gini coefficient, Kernel density estimation, Markov chain, and geographical detector, this study extensively assesses the spatial difference, dynamic evolution, and underlying driving forces of UGHQD in these urban agglomerations. The findings indicate: (1) The UGHQD level of the five major urban agglomerations has witnessed a consistent year-over-year growth trend, with coastal agglomerations like the Pearl River Delta (PRD) and Yangtze River Delta (YRD) outperforming others. (2) Pronounced regional differences exist in UGHQD levels across the urban agglomerations, with inter-regional differences primarily contributing to these differences. (3) The dynamic evolution of UGHQD distribution generally transitions from a centralized to a decentralized pattern, with a marked "club convergence" characteristic hindering cross-type leaps. (4) While a range of factors drive UGHQD in these agglomerations, technological innovation stands out as the principal factor inducing spatial differentiation. The comprehensive analysis and findings presented in this research not only contribute to academic knowledge but also hold practical implications for policymakers and practitioners striving for environmentally conscious land use planning and urban management. [ABSTRACT FROM AUTHOR]

From the middle of the Northern Song Dynasty (960–1127), the Linji School became the main branch of the Southern Chan Buddhism. Understanding the historical significance of the Linji School is crucial for comprehending the origins and development of Chan Buddhism in China and East Asia. This article adheres to the academic approach of studying Chan in its historical context, using GIS (Geographic Information System) tools to include in the research all seven generations of Linji monks, from the fourth to the tenth Linji generation, and reconstructing the spatial and temporal process of Linji's transmission in the 10th and 11th centuries. The study found that the Linji monastic group maintained a tenuous relationship with secular power in their ideology during the Northern Song Dynasty, with their preaching distribution center far from the power center (the capital), located to the south of the Yangtze River. This situation allowed the Linji monastic group to avoid extinction during the transition between the Song and Jin Dynasties, and the monastic group later became a unique and thriving force. [ABSTRACT FROM AUTHOR]

Indoor fire is a sudden and frequent disaster that severely threatens the safety of indoor people worldwide. Indoor fire emergency evacuation is crucial to reducing losses involving various objects and complex relations. However, traditional studies only rely on numerical simulation, which cannot provide adequate support for decision-making in indoor fire scenarios. The knowledge graph is a knowledge base that can fully utilize massive heterogeneous data to form a sound knowledge system; however, it has not been effectively applied in the fire emergency domain. This study is a preliminary attempt to construct a knowledge graph for indoor fire emergency evacuation. We constructed the indoor fire domain ontology and proposed a four-tuple knowledge representation model. A knowledge graph was constructed with 1852 nodes and 2364 relations from 25 indoor fire events. The proposed method was tested for the case study of Henan Pingdingshan '5.25' Fire Accident in China. Results show that the proposed knowledge representation model and the corresponding knowledge graph can represent complicated indoor fire events and support indoor fire emergency evacuation. [ABSTRACT FROM AUTHOR]

Urban vitality is an important reflection of a city's development potential and urban quality. This study used exploratory spatio-temporal big data such as social media check-ins to portray the spatio-temporal evolution of urban vitality at the subdistrict scale in Changsha, a city in central China, from 2013 to 2021, finding that urban vitality in Changsha exhibited central agglomeration and outward circling expansion over time, and then we used Geodetector and spatial regression analyses to explain the interactive effects and spatio-temporal heterogeneity of the spatial elements of subdistrict form, subdistrict function, and subdistrict economy on urban vitality. The results show the following: (1) The subdistrict form and subdistrict function dimensions had a significant effect on urban vitality, and the effect of the economic dimension of the subdistrict was not significant. (2) The interaction effect of the density of entertainment and leisure facilities and the density of business office facilities in subdistrict function was the dominant factor in the change of urban vitality. (3) Under the spatio-temporal effect, land use diversity and park facility density had the strongest positive effect on urban vitality; road density and shopping facility density had the weakest effect. The study aimed to provide a reference for the optimization and allocation of spatial elements of subdistricts in sustainable urban development and urban renewal, in order to achieve the purpose of urban vitality creation and enhancement. [ABSTRACT FROM AUTHOR]

Resource-exhausted cities usually face problems of environmental degradation, landscape fragmentation, and impeded ecological mobility. By clarifying the spatial heterogeneity of ecological restoration needs, efficient and coordinated ecological protection and restoration can be carried out. This study selected Jiawang District, a typical resource-exhausted city, and constructed an ecological security evaluation framework to determine the ecological source area from the three aspects of ecosystem service importance, ecological sensitivity, and landscape stability. The resistance surface was corrected with ecological sensitivity evaluation data, and ecological corridors and ecological nodes were identified using circuit theory. Finally, it explored the spatial and temporal evolution of the key areas of territorial ecological restoration in Jiawang District. This study indicates that: (1) In 2000, 2010, and 2020, the ecological source areas were 123.59 km2, 116.18 km2, and 125.25 km2, and the corresponding numbers of ecological corridors were 53, 51, and 49. The total lengths of the ecological corridors were 129.25 km, 118.57 km, and 112.25 km, mainly distributed in the northern and central areas of the study area. (2) The study area contained 17, 13, and 19 ecological pinch points in 2000, 2010, and 2020, respectively, 16, 20, and 15 ecological obstacle points, and 8, 24, and 33 ecological fracture points, respectively. Targeted rehabilitation of these key areas can significantly improve ecological connectivity. (3) The key area of territorial ecological restoration in 2020 was composed of 125.25 km2 ecological source area, 8.77 km2 of ecological pinch point, 12.70 km2 of ecological obstacle point, and 33 ecological fracture points. According to the present situation of land use, protection strategies are put forward. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to reveal the spatiotemporal evolution of entrepreneurial activities in the local municipalities of the Yangtze River Delta at long timescales from a geographic perspective and to reveal the underlying factors driving such evolution. The ontology of entrepreneurial activities—startups—was chosen as the object of this study, and the developmental characteristics of entrepreneurial activities in the region since 2001 were explored in two dimensions: time series changes and spatial evolution. The driving mechanism was further explored using the geographical detector. The results showed that: (1) Intensive entrepreneurial activities have been underway in the Yangtze River Delta since the beginning of the 21st century. The entrepreneurial process has undergone a stable period of slow growth (2001–2013), as well as one of rapid growth (2014–2018). The number of startups increased during this period, from 241,700 in 2001 to 1,959,600 in 2018. (2) The density of entrepreneurial activities in the Yangtze River Delta has increased since 2001. The agglomerative patterns showed developmental trends of both concentration and diffusion, forming a dotted pattern of agglomeration centered on the provincial capitals of Nanjing, Hangzhou, and Hefei and a belt of agglomeration centered on Shanghai-Suzhou-Wuxi-Changzhou. (3) High-value agglomeration of entrepreneurial activities was found to be relatively stable, and low-value agglomeration steadily weakened. Shanghai, Suzhou, and Nantong have long been part of H-H clusters, while Chizhou, Wuhu, Bozhou, Huaibei, and Huainan in Anhui have become areas of depressed entrepreneurial activities. (4) Financial strength, degree of informationization, economic foundation, innovative vitality, openness, and market demand are the main factors affecting entrepreneurial activities in the Yangtze River Delta. Entrepreneurial activities have significant spatial correlation, and areas with high entrepreneurial vitality radiate their effect to the entrepreneurial activities in the surrounding areas. The factors affecting entrepreneurial activities have multiple characteristics, and policy makers should promote entrepreneurial activities with a comprehensive vision and multi-channel efforts. The findings of this study add to the understanding of the spatial proximity characteristics of long time series of entrepreneurial activities at the municipal scale in developing countries and reveal the characteristics of the multi-factor combinations affecting them. [ABSTRACT FROM AUTHOR]

Suaeda salsa (L.) Pall. (S. salsa) acts as a pioneer species in coastal wetlands due to its high salt tolerance. It has significant biodiversity maintenance, socioeconomic values (e.g., tourism) due to its vibrant color, and carbon sequestration (blue carbon). Bohai Bay region, the mainly distributed area of S. salsa, is an economic intensive region with the largest economic aggregate and population in northern China. The coastal wetland is one of the most vulnerable ecosystems with the urbanization and economic developments. S. salsa in Bohai Bay has been changed significantly due to several threats to its habitat in past decades. In this paper, we analyzed all available archived Landsat TM/ETM+/OLI images of the Bohai Bay region by using a decision tree algorithm method based on the Google Earth Engine (GEE) platform to generate annual maps of S. salsa from 1990 to 2020 at a 30-m spatial resolution. The temporal-spatial dynamic changes in S. salsa were studied by landscape metric analysis. The influencing factors of S. salsa changes were analyzed based on principal component analysis (PCA) and a logistic regression model (LRM). The results showed that S. salsa was mainly distributed in three regions: the Liao River Delta (Liaoning Province), Yellow River Delta (Shandong Province), and Hai River Estuary (Hebei Province, Tianjin). During the past 31 years, the total area of S. salsa has dramatically decreased from 692.93 km2 to 51.04 km2, which means that 92.63% of the area of S. salsa in the Bohai Bay region was lost. In the 641.89 km2 area of S. salsa that was lost, 348.80 km2 of this area was converted to other anthropic land use categories, while 293.09 km2 was degraded to bare land. The landscape fragmentation of S. salsa has gradually intensified since 1990. National Nature Reserves have played an important role in the restoration of suitable S. salsa habitats. The analysis results for the natural influencing factors indicated that precipitation, temperature, elevation, and distance to the coastline were considered to be the major influencing factors for S. salsa changes. The results are valuable for monitoring the dynamic changes of S. salsa and can be used as effective factors for the restoration of S. salsa in coastal wetlands. [ABSTRACT FROM AUTHOR]

The vegetation drought phenomenon will reduce the amount of water available to the vegetation system, change the ecological and hydrological cycles of plants, and affect the aquatic and terrestrial ecosystem in various forms. Therefore, research on the dynamic variation and driving mechanism of vegetation drought will help us recognize and predict the response of vegetation under drought stress conditions, implement appropriate policy measures to deal with the drought crisis, and provide technical support for implementing vegetation protection and alleviating the increasing risk of vegetation drought. However, the dynamic variation of vegetation drought and its dynamic propagation mechanism are still undefined across China. In this study, the spatio-temporal evolutions and pixel-scaled trends of vegetation drought were analyzed during the period between 1999 and 2020. Additionally, the propagation features were investigated between vegetation drought and meteorological drought. Finally, the relationships between vegetation drought and atmospheric teleconnection were explicitly clarified using multivariate cross wavelet transform technology. The results highlighted five key findings: (1) the vegetation drought presented an overall decreasing trend across China in 1999–2020; (2) the most serious vegetation drought occurred in the year 2000, with the average vegetation condition index (VCI) values ranging from 0.36 to 0.46; (3) vegetation droughts were alleviating at the pixel scale for each season; (4) the propagation time from meteorological drought to vegetation drought was shorter in summer (1.26 months) and longer in winter (2.26 months); and (5) the three-factors combination of Pacific North American (PNA), El Niño-Southern Oscillation (ENSO), and Trans Polar Index (TPI) can satisfactorily explain the variations of vegetation drought. This study sheds new viewpoints into the identification of vegetation drought variation across China, which can also be applied in other areas. [ABSTRACT FROM AUTHOR]

The development of the tertiary industry is of great significance for promoting industrial structure, optimizing and upgrading it, and achieving regional energy conservation and emission reduction goals. This study adopts a quantitative method to analyze the spatio-temporal pattern of carbon emissions from China's tertiary industry from 2004 to 2019. In order to analyze emissions from aspects such as energy structure, energy intensity, energy carrying capacity, industrial structure, level of industrial development, income level, consumption capacity, energy consumption intensity, and population size, this study establishes a hybrid factor decomposition model called the "energy-industry-consumption" research framework. The study shows that carbon emissions from China's tertiary industry have been increasing year by year from 2004 to 2019, with a growth rate of 353.10%. Transportation is the largest contributor to the increase in carbon emissions from China's tertiary industry. The carbon emissions from the tertiary industry in each province show four types: high-speed growth, low-speed growth, fluctuating growth, and stable growth. During the study period, carbon emissions produce a spatial heterogeneity with the highest emissions in the south and lowest in the northwestern part of China. The spatial pattern of per capita carbon emissions is not significant. Guangdong has the highest carbon emissions, and Shanghai and Beijing have higher per capita carbon emissions. Industrial factors and consumption factors have a positive effect on carbon emissions in China's tertiary industry, while energy factors have a negative effect. The leading factor of carbon emissions in China's tertiary industry has gradually shifted from energy to industry. [ABSTRACT FROM AUTHOR]

Conventional and scientific cropping patterns are important in realizing the sustainable utilization of Black soil and promoting the high-quality development of agriculture. It also has far-reaching significance for protecting Black soil and constructing the crop rotation system to identify the cropping patterns in Northeast China and analyze their spatio-temporal dynamic change. Using the geo-information Tupu methods and transfer land matrix, this study identified the cropping patterns and their spatio-temporal change based on remote sensing data for three periods, namely 2002–2005, 2010–2013, and 2018–2021. The main results revealed that the maize continuous, mixed cropping, maize-soybean rotation, and soybean continuous cropping patterns were the main cropping patterns in Wangkui County, with the total area of the four patterns accounting for 95.28%, 94.66%, and 81.69%, respectively, in the three periods. Against the backdrop of global climate warming, the cropping patterns of continuous maize and soybean and the mixed cropping pattern in Wangkui County exhibited a trend towards evolving into a maize-soybean rotation in the northern region. Moreover, the maize-soybean rotation further evolved into a mixed cropping system of maize and soybean in the north. Furthermore, the spatio-temporal evolution of cropping patterns was significantly driven by natural and social factors. Specifically, natural factors influenced the spatio-temporal patterns of variation in cropping patterns, while social factors contributed to the transformation of farmers' cropping decision-making behavior. Accordingly, new insights, institutional policies, and solid solutions, such as exploring and understanding farmers' behavior regarding crop rotation practices and mitigating the natural and climatic factors for improving food security, are urgent in the black soil region of China. [ABSTRACT FROM AUTHOR]

With the rapid urbanization and industrialization of the past few decades, environmental issues have become increasingly prominent, and air pollution in the form of PM2.5 has become a major concern in China. The Chinese government has recognized the severity of these environmental challenges and has placed great emphasis on protecting the environment while promoting economic growth. This study utilizes remote sensing technology to analyze the spatio-temporal evolution characteristics of the decoupling between land-use intensity and PM2.5 in the Yangtze River Economic Belt (YREB) using 2000–2021 series of PM2.5 and land-use-change data, with the Mean Center Change analysis and the Tapio Decoupling Model. This study attempts to analyze the causes of change from the perspectives of economic development stage and policy execution. The study found that the average PM2.5 level decreased by 11.77 μg/m3 during this period, with high levels concentrated in urban areas and low levels found in less developed regions. The central trajectory of the land-use intensity shifted southeast, indicating a consistent trend in urbanization and industrialization in that direction. Meanwhile, the average land-use intensity value increased by 0.19, with the highest values concentrated in urban areas. A total of 71.12% of the regions in the YREB exhibited strong negative decoupling or negative decoupling between land-use intensity and PM2.5 levels, suggesting rapid urbanization and industrialization with a decrease in PM2.5 levels. These findings provide insight into the dynamic relationship between economic development, urbanization, and PM2.5 in China's Yangtze River Economic Belt. [ABSTRACT FROM AUTHOR]

Innovation networks promote regional innovation and economic growth. Using the patent data of cooperative inventions and the panel data of socio-economic statistics for 2010–2019, this study quantitatively analyzes the spatial structure evolution of intra-city and inter-city innovation networks for 41 cities in the Yangtze River Delta and their influence on economic growth. This study shows that these networks are increasingly connected and have a highly similar Z-shaped spatial structure. City economic growth is generally high, relatively stable, and mainly positively influenced by inter-city innovation networks. Intra-city innovation networks have no significant effect on economic growth; however, they are complementary to the inter-city ones. [ABSTRACT FROM AUTHOR]

Based on the meteorological and hydrological data of the Yalong River Basin from 1960 to 2019, meteorological and hydrological droughts were analyzed using the standardized precipitation evapotranspiration index (SPEI) and standardized runoff index (SRI); then, the spatio-temporal evolution and propagation characteristics of the droughts were studied on multiple time scales. The results showed that, firstly, on the annual scale, the frequencies of meteorological and hydrological droughts in the basin were 28.3% and 34.0%, respectively, in the past 60 years. From upstream to downstream, the longer the alternating period of dry and wet periods, the more significant the frequency of droughts. Secondly, on a seasonal scale, the frequency of meteorological droughts is high in autumn, and the frequency of hydrological drought is high in autumn and winter. The frequency of drought in different seasons decreases from the upper reaches to the lower reaches of the basin. Thirdly, on a monthly scale, the severe and exceptional meteorological drought frequencies are high from March to May, and the severe and exceptional hydrological drought frequencies are high in January, March, October, and December. The frequency of hydrological droughts is much higher than that of meteorological droughts, especially with respect to severe and exceptional drought. Meteorological and hydrological droughts spread in the same period without lag, but they tend to expand. The propagation time of drought is short in summer and autumn, but long in spring and winter. The conclusions can serve as a decision-making basis for the water diversion planning of the west route of China's South-to-North Water Diversion Project and the cascade hydropower operation of the basin. [ABSTRACT FROM AUTHOR]

As the most intuitive manifestation of land use/land cover change, the spatio-temporal evolution of landscape patterns has significant implications for optimizing regional landscape pattern and land use management. Based on multi-period remote sensing data, we selected an optimal scale (570 m) and used the geographic detector model to analyze the spatio-temporal changes in the landscape pattern of a typical hilly area (Yujiang District, Yingtan City, Jiangxi Province) in southern China. The results showed that from 2009 to 2018, the area of urban land, other construction land, rural residential land, and cultivated land expanded by 33.27%, 21.23%, 19.42%, and 1.07%, respectively. In contrast, the area of grassland, forest land, and water area shrank by 18.18%, 5.41%, and 2.19%, respectively, over the past 10 years. At the landscape level, the patch shape became more complex over time, with increased landscape fragmentation and diversity. At the class level, cultivated land, forest land, and grassland tended to be fragmented, whereas rural residential land exhibited an aggregation tendency. Slope gradient, gross regional product, and distance from major highways had a strong ability to explain the spatial differences in landscape pattern change. The results of this study enable a dynamic understanding of landscape pattern evolution in typical hilly areas in southern China and provide a reference for landscape pattern optimization in similar geomorphic settings. [ABSTRACT FROM AUTHOR]

The coordinated development of farmland transfer (FT) and labor migration (LM) is of great efficiency significance to facilitate the development of rural economy and implement the rural revitalization strategy. The study used socioeconomic data from 30 provinces/autonomous regions/municipalities (hereafter referred to as provinces) in China to measure the coupling coordination degree (CCD) of FT and LM. It adopted the coupling coordination degree model (CCDM), exploratory spatial data analysis method (ESDA), and gray relational analysis model (GARM) to investigate the spatial differences in the CCD and its influencing factors. The results indicate the following: (1) Regional differences are evident despite the fact that the comprehensive evaluation level of FT and LM in the various provinces is relatively low and displaying a rising trend. (2) The CCD of FT and LM exhibits a fluctuating upward trend and is at the primary coupling coordination stage, with a significant difference in coupling coordination levels between regions, and a spatial distribution pattern of central region > eastern region > northeast region > western region. (3) The CCD shows a strong global spatial positive correlation with clear fluctuations, demonstrating the agglomeration dispersion development tendency over time; the local spatial agglomeration state emerges and stabilizes. According to the distribution pattern, the Western region exhibits weak agglomeration type, whereas the eastern and central regions exhibit strong agglomeration type. (4) There are significant variations between provinces in terms of the intensity of the CCD of FT and LM, as well as the level of concurrent employment business, the level of non-agricultural industry development, the level of urbanization, the level of agricultural equipment, and the land approval. [ABSTRACT FROM AUTHOR]

Since economic globalization is unstable, it is difficult for the traditional open economic development model to meet the requirements of China's development, and there is an urgent need for new ideas and models to be reoriented. Based on the analysis of the development mechanism of China's open economy at this stage, we used the entropy method, Theil coefficient, Gini coefficient, and spatial Durbin model (SDM) to analyze the spatio-temporal pattern and influencing factors of the high-quality development level of the open economy in the Yangtze River Delta Area (YRDA). The results indicated that during the study period, the development level and development difference of open economy were on the rise, and the spatial difference in different regions was significant. The development of open economy was affected by many factors, and there was a spatial spillover effect. Based on the existing problems, at the stage of high-quality economic development, the YDRA should seize the opportunities brought by the new development pattern, improve government services, optimize innovation drive, and promote the development of open economy to a higher level. We believe that the results of this study can also provide relevant experience for the development of open economy in other regions of China. [ABSTRACT FROM AUTHOR]

Research on the development performance of small towns is critical for promoting their revitalization, advancing urbanization, and high-quality development and transformation for realizing urban–rural integration. We used the DPSIR-DEA model to study the spatiotemporal evolution process and characteristics of the development performance of 14 small towns within the administrative division of Jiangyin city from 2001 to 2019. We subsequently applied a geographical detector model to analyze the spatiotemporal heterogeneity of the factors influencing the development performance of small towns. The results showed that 2012 was a turning point in the overall development performance index of small towns in Jiangyin, revealing initially decreasing and then increasing trends. The development performance index values of different types of small towns evidenced three trends: a steady increase, a continuous decrease, and an initial decrease followed by an increase. During 2001–2019, the development performance of Jiangyin's small towns reflected a spatial evolution pattern of complete dispersion → small agglomeration → large agglomeration. An optimal spatial pattern comprised an increase in the number of towns demonstrating a high development performance and a decrease in the number of towns with a low development performance. GDP per capita, industrial investments, and construction land density were key influencing factors of development performance, which was mainly driven by economic and social factors, with ecological factors having a relatively weak influence. [ABSTRACT FROM AUTHOR]

The quantitative and qualitative assessment of post-disaster vegetation damage and recovery in the core area of the Wenchuan earthquake is of great significance for the restoration and reconstruction of natural ecosystems and the construction of human settlements in China. This study used time series analysis to determine the time of MODIS data and used the data to study the vegetation damage and restoration in the core area of the Wenchuan earthquake. The determined MODIS images were used to quantitatively analyze a series of vegetation damage changes and the vegetation recovery rate in the core area of the Wenchuan earthquake before and after the earthquake. By applying the topographic factors, we analyzed the spatial and temporal characteristics of the dynamic changes of vegetation damage and the recovery rate in the disaster area. The results show that the study area's vegetation damage was correlated to topographic factors and distance from towns. Besides, the overall vegetation restoration after the disaster was relatively optimistic. In some areas, the vegetation restoration level even exceeded the vegetation coverage level before the disaster. The recovery study of MODIS-NDVI showed a specific lag delay effect on the image of vegetation cover. The vegetation damage and the recovery rate of vegetation cover were significantly correlated with the distance from towns and the topographic factor. Overall, the results contribute to the theoretical support for the damage and recovery of vegetation in the core area affected by the earthquake. [ABSTRACT FROM AUTHOR]

Reasonable rent is the key to promoting land transfer and realizing agricultural operations on a moderate scale in rural China. The purpose of this study was to reveal the spatiotemporal variations in farmland rents and their drivers by employing a multilevel model based on 3547 plot-level transactions in Sichuan Province of China. The results show that the rents of paddy field, irrigated land, dry land and other types of farmland have all maintained an upward trend since 2014, rising by 61%, 53%, 44% and 224%, respectively. The average rent per ha for these properties reached CNY 13,920, 12,285, 10,230 and 7980 in 2020 (1 USD = CNY 6.90 in 2020), respectively. Farmland rents have shown a significant spatial agglomeration phenomenon, and the regions with higher rent were mainly distributed in Chengdu and its surrounding areas, while the regions with lower rent were distributed in the east and northeast of Sichuan Province. The differences in farmland rent were influenced by multilevel factors such as plot level and regional level, and the former explained 73.4% of the farmland rent variation. The plots with a larger area, longer transfer period, clear ownership, better location and good-quality land had higher rents; otherwise, the rents were lower. [ABSTRACT FROM AUTHOR]