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An urban agglomeration is the engine of regional and national economic growth, but also causes many ecological and environmental issues that emerge from massive land changes. In this study, the spatiotemporal evolution of an urban agglomeration was quantified and its impacts on the urban and regional landscape patterns were evaluated. It showed that the urbanized land area of the Pearl River Delta Urban Agglomeration (PRDUA) in China nearly quadrupled, having linearly increased from 1819.8 km2 to 7092.2 km2 between 1985 and 2015. The average annual growth rate presented a bimodal wave-like pattern through time, indicating that the PRDUA has witnessed two rounds of the urbanization process. The growth modes (e.g., leapfrog, edge-expansion, infilling) were detected and they exhibited co-existing but alternating dominating patterns during urbanization, demonstrating that the spatiotemporal evolution of the urban development of the PRDUA follows the “spiral diffusion-coalescence” hypothesis. The morphology of the PRDUA presented an alternating dispersal-compact pattern over time. The city-level and regional-level landscape patterns changed synchronously with the spatiotemporal evolution of the PRDUA over time. The urbanization of the PRDUA increased both the complexity and aggregation of the landscape, but also resulted in an increasing fragmentation and decreasing connectivity of the natural landscape in the Pearl River Delta region. These findings are helpful for better understanding how urban agglomerations evolve and in providing insights for regional urban planning and sustainable land management. Natural Science Foundation of China National Key R&D Program of China China Postdoctoral Science Foundation Joint-PhD project of Shanghai Jiao Tong University and The University of Melbourne

There is great potential for carbon emission reduction in energy-enriched areas. It is important to master the spatiotemporal characteristics and driving factors of carbon emissions to achieve the goal of carbon emission reduction. Previous studies on carbon emissions mainly focused on the numerical changes in regional carbon emissions. There have been few studies on spatiotemporal characteristics, making it difficult to formulate carbon emission reduction strategies according to local conditions. This study is based on the carbon emission calculation method proposed by the Intergovernmental Panel on Climate Change (IPCC), taking the method of exploratory spatial data analysis (ESDA), standard deviation ellipse (SDE) analysis and the geographically weighted regression model (GWR) to analyse the spatiotemporal evolution characteristics and determinants and dividing regional types of carbon emissions. The results show that aggregate carbon emissions and other carbon emission indicators presented an upward trend from 2000 to 2016, and the growth momentum of carbon emissions was difficult to curb in the short term. The carbon emissions of the study area are relatively concentrated in spatial; the direction of carbon emissions presented a trend of “northeast–southwest”, and the main axis and centre of carbon emissions tend to move northward over time. There are six regional types of carbon emissions in the study area. The low total amount–low intensity–low pressure type (L-L-L) became the dominant regional type of carbon emissions. The results of the GWR model showed that the degree of influence of explanatory variables on carbon emissions in descending order is urbanization rate > industrial structure > population > population density > per capita GDP.

The spatial and temporal evolution of the sandbody architecture of shallow-water deltas in open lacustrine basins is controlled by the classification of allocyclicity and autocyclicity. On the southwestern margin of the Ordos Basin, a braided river system deposited a shallow-water delta in the Late Triassic Period. Based on the principle of sequence stratigraphy and the hierarchical analysis of reservoir architecture, the spatial and temporal evolution of individual sandbodies in the Chang 81 member of the Yanchang Formation in the Zhenbei Oilfield is interpreted by utilizing data from cores, wells and outcrops. The research ideas are as follows: large deposition scale architectural elements (first- to third-order cycles, as defined by Miall) of different sequence levels are affected by allocyclicity associated with changes in tectonic activity, provenance, and sea level, and small deposition scale architectural elements (fourth- to fifth-order cycles, as defined by Miall) of different sedimentary facies mainly consist of individual sandbodies that are affected by autocyclicity associated with lake-level changes caused by various river processes. Based on previous studies, the results are as follows. The sedimentary characteristics of shallow-water deltas have been verified by core and outcrop data. In addition, three ultrashort-term cycles are identified on the basis of boundary sequences and lithofacies’ sequences in the outcrop section of the Rui River, and three sedimentary evolution stages of the delta front are defined. Finally, according to well data, five types of architectural elements at the level of single sandbodies are identified. The vertical superimposition and lateral contact relationships of different architectural elements indicate that during the three sedimentary evolution stages, the hydrodynamics weakened, strengthened slightly, and finally weakened substantially. Among the 20 kinds of architectural element spatial combination patterns formed by single sandbodies, primary and secondary sandbodies have great potential for hosting remaining oil. In the process of architectural spatiotemporal evolution, the geometry and connectivity of the underwater distributary channel gradually weakened, and the spatial relationship between the underwater distributary channel and other architectural elements increased. This article proposes a new method for researching shallow-water deltas and has some guiding significance for exploiting the remaining oil in oil fields.

The ecological environment in arid areas of Northwest China has undergone considerable changes under the combined effects of climate change and human factors. Therefore, exploring the spatial and temporal evolution of the ecological environment quality is of great significance for the protection and management of the ecological environment in arid areas of Northwest China. This study adopted Yuyang district as the study area. Landsat Thematic Mapper/Operational Land Imager images from 1993 to 2018 were selected as the data source for the retrieval of important surface indicators and the construction of the remote sensing distance ecological index. The spatial distribution, trend, and grade classification of the ecological environment quality were monitored and analyzed. The results showed that (1) the ecological environment quality of Yuyang district from 1993 to 2018 showed an overall upward trend, mainly manifested as a sharp decline in the area of poor ecological environment from 84.81 to 53.36%. (2) The spatiotemporal changes in the ecological environment quality showed a downward trend in the central urban area and an upward trend in the noncentral urban area. (3) In general, rainfall and temperature had limited impact on the ecological environment quality. Urbanization seriously affected the local ecological environment quality and the implementation of the ecological restoration policies, regulations, and measures were the main drivers of the improvement to the ecological environment quality in other surrounding areas.

A turbidity current is a particle-laden current driven by density differences due to suspended sediment particles. Turbidity currents can transport large amounts of sediment down slopes over great distances, and play a significant role in fluvial, lake and submarine systems. To better understand the sediment transport process, the flow system of an experimentally produced turbidity current in an inclined flume was investigated using video processing. We observed that the current progresses with constant frontal velocity and maintains an unchanged global interface geometry. In addition, the spatio-temporal profiles of the inner mean and turbulence velocity obtained by ultrasound velocity profiler (UVP) showed that similar distributions were maintained, with low dissipation. The results indicate that the turbidity current progressed in a quasi-stationary state, which enabled long-distance sediment transport. To understand the mechanisms behind the quasi-stationary flow, we analyzed the forces acting on the turbidity current. We found that under particular densities of suspended particles, the gravitational force is balanced by the viscous forces along the slope direction. We conclude that this specific force balance induces the quasi-stationary flow structure, enabling the long-distance transport of a substantial amount of sediment downstream with low dissipation. (C) 2020 International Research and Training Centre on Erosion and Sedimentation/the World Association for Sedimentation and Erosion Research. Published by Elsevier B.V. All rights reserved.

This paper contributes to the study of regional economic resilience by analyzing the dynamic characteristics and influence mechanisms of resilience from the perspective of spatial heterogeneity. This paper focuses on the resistance and recoverability dimensions of resilience and analyzed the dynamic changes in economic resilience in China’s Yellow River Basin in response to the 2008 economic crisis. The multi-scale geographical weighted regression model was utilized to examine the effect of key factors on regional economic resilience. Our findings show the following: (1) The resistance of the Yellow River Basin to the financial crisis was high; however, the recoverability decreased significantly over time. (2) The spatial heterogeneity of driving factors was significant, and they had different effect scales on economic resilience. Related variety, government agency, environment, and opening to the global economy had a significant effect on economic resilience only in a specific small range. Specialization, unrelated variety, and location had opposite effects in different regions of the Yellow River Basin. (3) Specialization limited the area’s resistance to shock but enhanced the recoverability. Related variety improved regional economic resilience. Unrelated variety was not conducive to regional resistance to shock and had opposite effects on the recoverability in different regions. (4) Government agency and financial market promoted regional economic resilience. Environment pollution and resource-based economic structure limited regional economic resilience. Opening to the global economy and urban hierarchy limited regional resistance to shock, but strong economic development had the opposite effect of improved regional resistance. The location in the east of the Yellow River Basin enhanced the recoverability; however, the location in the west limited the recoverability.

Since the emergence of COVID-19, there have been many local outbreaks with foci at shopping malls in China. We compared and analyzed the epidemiological and spatiotemporal characteristics of local COVID-19 outbreaks in two commercial locations, a department store building (DSB) in Baodi District, Tianjin, and the Xinfadi wholesale market (XFD) in Fengtai District, Beijing. The spread of the infection at different times was analyzed by the standard deviation elliptical method. The spatial transfer mode demonstrated that outbreaks started at the center of each commercial location and spread to the periphery. The number of cases and the distance from the central outbreak showed an inverse proportional logarithmic function shape. Most cases were distributed within a 10 km radius; infected individuals who lived far from the outbreak center were mainly infected by close-contact transmission at home or in the workplace. There was no efficient and rapid detection method at the time of the DSB outbreak; the main preventative measure was the timing of COVID-19 precautions. Emergency interventions (closing shopping malls and home isolation) were initiated five days before confirmation of the first case from the shopping center. In contrast, XFD closed after the first confirmed cases appeared, but those infected during this outbreak benefitted from efficient nucleic acid testing. Quick results and isolation of infected individuals were the main methods of epidemic control in this area. The difference in the COVID-19 epidemic patterns between the two shopping malls reflects the progress of Chinese technology in the prevention and control of COVID-19.

The accurate inversion of actual evapotranspiration (ETa) at a regional scale is crucial for understanding water circulation, climate change, and drought monitoring. In this study, we produced a 1 km monthly ETa dataset for Turpan and Hami, two typical arid cities in northwest China, using multi-source remote sensing data, reanalysis information, and the ETMonitor model from 1980 to 2021. We analyzed the spatiotemporal variation of ETa using various statistical approaches and discussed the impact of climate and land use and cover changes (LUCC) on ETa. The results show the following: (1) the estimation results correlate well with ETa products on monthly scales (coefficient of determination (R2) > 0.85, root mean square error (RMSE) < 15 mm/month) with high reliability. (2) The ETa values were spatially distributed similarly to precipitation and LUCC, with the multi-year (1980–2021) average of 66.31 mm and a slightly fluctuating downward trend (−0.19 mm/a). (3) During the 42-year period, 63.16% of the study area exhibited an insignificant decrease in ETa, while 86.85% experienced pronounced fluctuations (coefficient of variation (CV) > 0.20), and 78.83% will show an upward trend in the future. (4) ETa was significantly positively correlated with precipitation (94.17%) and insignificantly positively correlated with temperature (55.81%). The impact of human activities showed an insignificant decreasing trend (85.41%). Additionally, the intensity of ETa varied considerably among land types, with the largest for cropland (424.12 mm/a). The results of the study have implications for promoting the rational allocation of regional water resources and improving water use efficiency in arid zones.

The trade-off and coordinated development of the “production-living-ecological” functions (PLEFs) of an area is an important basis for the optimization of the spatial pattern of the land, and helps to promote the harmonious symbiotic relationship between human beings and nature. This paper combines ecological niche theory, a coupling coordination model, and a trade-off synergy model to construct an evaluation index system for Chinese county PLEFs. Quantitative methods were used to measure spatiotemporal evolution characteristics, trade-off synergy of PLEFs in 38 counties in Chongqing, China, and the coupling coordination degree between PLEFs. The results showed that the ecological niche width of the “production-ecological” function revealed an overall growth trend. However, there was a mismatch in regional development of the “production-ecological” function, showing dislocation characteristics of “high in the west and low in the east” and “high in the east and low in the west.” The niche width of the life function is similar to the comprehensive niche width of PLEFs, showing the characteristics of fluctuation and partition change. PLEFs and both the aforementioned functions showed distribution characteristics of “high in the west and low in the east,” with the whole moving towards the stage of coordinated coupling, of which the “production-living” function has the highest coupling level. The functional coupling coordination degree of “production-living-ecological” is generally manifested as “high in the west and low in the east,” and changing from the primary stage of imbalance to well-coordinated development. The “production-ecological” and “living-ecological” functions are in low-level imbalance in the primary and moderate coordination stages. Additionally, the evolution trend of the “production-ecological” and the “living-ecological” functions are similar, showing alternating and fluctuating development characteristics. Overall, in the past 20 years, Chongqing’s “living-production” function has changed from a trade-off model to a collaborative development relationship, and the “living-ecological” function is generally based on a collaborative development relationship. The “ecological function” is manifested as a trade-off constraint relationship. Moreover, the coordinated development level of “living-production,” “living-ecological,” and “production-ecological” functions in the central urban area has been greatly improved, while counties have gradually shown different degrees of trade-offs.

Exploring the coupling coordination degree between supply and demand and its key influencing factors is important for ecological security and socioeconomic sustainable development in resource-based cities. On the basis of measuring the supply and demand of ecosystem services in 125 resource-based cities in China from 2000 to 2020, we analyzed the matching pattern and coupling coordination degree between supply and demand. The Spearman correlation analysis and quantile regression models were used to explore the impacts of the natural and socioeconomic factors on the coupling coordination degree between supply and demand. The results indicate that the supply and demand of ecosystem services in resource-based cities exhibits obvious spatiotemporal heterogeneity. Cities with a higher ecosystem service demand are mainly located in Eastern China. Cities with a higher ecosystem service supply are mainly concentrated in Western China. The ecosystem service supply decreased, while the demand increased over time. In addition, the coupling coordination degree between supply and demand is low and increased slowly over time. Population density, economic density, construction land, arable land and grassland have significant effects on the supply–demand relationship in resource-based cities. The elasticity coefficients obtained from the quantile regression model imply that the effects are significantly heterogeneous in terms of time and the level of coupling coordination degree.

Natural disasters present a significant challenge to the productivity of Zhejiang Province. This paper is the first to evaluate social vulnerability to natural disasters in Zhejiang Province and provides a scientific foundation for disaster prevention, mitigation, and risk management. In this paper, we construct an indicator system for evaluating social vulnerability of natural disasters in Zhejiang Province through demand analysis, frequency analysis, and applicability analysis. The methodology employed in this paper reduces errors arising from subjective indicator selection and provides a reference for future international research on evaluating social vulnerability to natural disasters. This study analyzes the spatiotemporal evolution of social vulnerability to natural disasters in 11 cities from 2011 to 2020. The results indicate an overall downward trend of social vulnerability to natural disasters in Zhejiang. Social vulnerability to natural disasters exhibits significant spatial variability. The evaluation can help to bridge the knowledge gap regarding the social vulnerability of Zhejiang Province to natural disasters. The analysis of the spatiotemporal evolution of social vulnerability provides insights into the contributing factors to vulnerability and the effectiveness of past disaster management strategies. The findings of this study can serve as a valuable reference for future research in Zhejiang Province and other regions facing similar challenges. The results can contribute to the advancement of comprehensive knowledge of social vulnerability to natural disasters, which can inform the development of policies and strategies aimed at mitigating disaster risk and promoting effective disaster management globally.

Cities in China do not constitute a few global metropolises, but are characterized by heterogeneity. Studying counties can give us a comprehensive picture of urban sprawl in China. This study measured the sprawl index of 1880 counties in China from 2005 to 2020 for the first time and then revealed the evolution of their spatiotemporal characteristics and driving mechanisms. The results revealed the following. (1) China’s counties had a noticeable sprawling trend from 2005 to 2020, and their evolutionary process was characterized by spatiotemporal heterogeneity. (2) From 2005 to 2020, the counties’ sprawl gradually evolved into a spatial distribution pattern of high in the east and low in the west. The spatial distribution of sprawl in county and municipal districts had the characteristics of an interlocking distribution. (3) High–high cluster areas of CSI are mainly distributed in plains, and hilly, basin, and plateau areas tend to be low–low cluster areas. High–low outliers were distributed in a “point–line” pattern along the railroad lines and a cluster pattern near railroad intersections and central cities. Low–high outliers had the trend of encircling the high–high cluster areas. (4) The coefficient of the natural drivers was higher but tended to decrease, while the coefficient of economic and spatial drivers was lower but gradually increased. This study is the first to refine the study of urban sprawl to the county scale, which provides a reference for decision making to optimize the spatial structure of counties and thus promote high-quality development.

Drought poses a serious threat to agricultural production and food security in the context of global climate change. Few studies have explored the response mechanism and lag time of agricultural drought to meteorological drought from the perspective of cultivated land types. This paper analyzes the spatiotemporal evolution patterns and hysteresis relationship of meteorological and agricultural droughts in the middle and lower reaches of the Yangtze River in China. Here, the Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation index products and surface temperature products were selected to calculate the Temperature Vegetation Dryness Index (TVDI) from 2010 to 2015. Furthermore, we obtained the Standardized Precipitation Evapotranspiration Index (SPEI) and the Palmer Drought Severity Index (PDSI) for the same period. Based on these indices, we analyzed the correlation and the hysteresis relationship between agricultural and meteorological drought in rainfed and irrigated arable land. The results showed that, (1) compared with SPEI, the high spatial resolution PDSI data were deemed more suitable for the subsequent accurate and scientific analysis of the relationship between meteorological and agricultural droughts. (2) When meteorological drought occurs, irrigated arable land is the first to experience agricultural drought, and then alleviates when the drought is most severe in rainfed arable land, indicating that irrigated arable land is more sensitive to drought events when exposed to the same degree of drought risk. However, rainfed arable land is actually more susceptible to agricultural drought due to the intervention of irrigation measures. (3) According to the cross-wavelet transform analysis, agricultural droughts significantly lag behind meteorological droughts by about 33 days during the development process of drought events. (4) The spatial distribution of the correlation coefficient between the PDSI and TVDI shows that the area with negative correlations of rainfed croplands and the area with positive correlations of irrigated croplands account for 77.55% and 68.04% of cropland areas, respectively. This study clarifies and distinguishes the details of the meteorological-to-agricultural drought relationship in rainfed and irrigated arable land, noting that an accurate lag time can provide useful guidance for drought monitoring management and irrigation project planning in the middle and lower reaches of the Yangtze River.

Given that glaciers are good indicators of climate change, it is of great scientific significance to study glacier change for regional environmental protection and water resource development and utilization. Using the Google Earth Engine (GEE) platform, we obtained the distribution of glaciers in western China in 2000, 2005, 2010, 2015, and 2020. Then, we analyzed the temporal and spatial evolutions of the glacier areas and their responses to climate change. The results showed that there were 52,384 glaciers in western China in 2020, with an area of 42,903.57 km2, among which those belonging to the headwater of the Tarim River are the largest, accounting for 35.25% of the total area. From 2000 to 2020, the glaciers indicated an overall trend of retreat, with the total area decreasing by 15,575.94 km2 at a change rate of 1.46%/a. From 2000 to 2010, glaciers in the southeast Qinghai-Tibet Plateau (QTP) and Qilian Mountains saw the fastest area loss (>4%/a), followed by the Tianshan Mountains (3.31%/a), while those in the Pamir-Karakoram-West Kunlun regions and the Qiangtang Plateau had the slowest loss. From 2010 to 2020, the glacier retreat rate exhibited an accelerating trend in southeast QTP and the western Himalayas, while it slowed down in the Tianshan Mountains. The change in glaciers was greatly attributed to the combination of snowfall and summer temperature trends. The glaciers in southeast QTP showed an accelerated retreat tendency, probably due to the accelerating snowfall decrease and continuous temperature rise. The decreasing temperature mitigated the loss of glacier area in the Pamir-Karakoram-West Kunlun regions with continuously decreasing snowfall.

The spatial-temporal differentiation characteristics and driving mechanisms of ecosystem services are of great significance for optimizing the pattern of land spatial protection and realizing regional sustainable development. Existing studies seldom consider the segmental influence mechanism of various influencing factors on different levels of ecosystem service value (ESV). Therefore, this paper analyzes the temporal and spatial differentiation evolution characteristics of ESV in semiarid regions through an improved ESV evaluation model. The spatial panel quantile regression (SPQR) model was introduced to explore the relationship between various types of influencing factors and ESV in different intervals. The results showed the following: (1) The changes in ESV in Baotou City from 2000 to 2018 tended to be stable, but the spatial differentiation of ESV intensified. The aggregation feature of the low-ESV region is significant and gradually expanding. (2) Precipitation was the dominant factor increasing the ESV in each interval, and temperature had a significant negative impact on the low-ESV area. (3) Higher land use integrity accelerates the decline of ESV in the surrounding areas of built-up areas. The high-ESV area was more sensitive to the intensity of human activity. The direction of human activities should be effectively controlled, and the structure of comprehensive land use should be optimized to enhance the service function of regional ecosystems. This research provides new thinking for the ecological restoration zoning of regional territorial spatial planning and the sustainable development of resource-based cities.

China has entered a new stage of integrated development of urban and rural areas under the constraints of scarce land resources and the need for high-quality economic and social development. While there is concern about the state and speed of urban–rural integrated development (URID), increasing attention is being paid to efficiency improvement. This paper comprehensively measures the efficiency of URID from the input–output perspective, taking into account the impact of carbon emissions; it also studies the efficiency of URID and its developmental spatiotemporal characteristics in 73 cities within three major city clusters in the Yangtze River Economic Belt (YREB) from 2010 to 2019, and analyzes the input–output optimization strategies for URID within each of these major urban systems. The results show that (1) the comprehensive efficiency evaluation system constructed by the study can more objectively reflect the state and trends of URID. From 2010 to 2019, the efficiency of URID in the three major city clusters in the YREB showed a downward trend; in cities with better economic development, the efficiency of URID was lower than in cities with average economic development, where carbon emission indicators showed a significant impact. (2) The spatial distribution of URID efficiency in the three major city clusters in the YREB follows an inverted “U” shape; URID efficiency in the urban agglomeration in the middle reaches of the Yangtze River (MRYRUA) is higher than in the Chengyu urban agglomeration (CYUA), where it is higher than in the Yangtze River Delta urban agglomeration (YRDUA). (3) The input redundancy rates are high in the indicators for culture, sports and media, energy conservation and environmental protection, urban and rural communities, and housing security expenditures. Carbon emission redundancy has a negative impact on efficiency in URID. Based on the high redundancy rates of each input–output indicator, this paper proposes methods to optimize the efficiency of URID in each of the three major city clusters and provides directional guidance for promoting the high-quality development of regional urban–rural integration.

As a result of climate change and human activities, water resources in the Xiangjiang River Basin (XRB) are subject to seasonal and regional shortages. However, previous studies have lacked assessment of the spatiotemporal evolution of water yield in the XRB at seasonal and monthly scales and quantitative analysis of the driving forces of climate change and land use on water-yield change. Quantitative evaluation of water yield in the XRB is of great significance for optimizing water-resource planning and allocation and maintaining ecological balance in the basin. In this paper, the seasonal water-yield InVEST model and modified Morris sensitivity analysis were combined to study the characteristics of monthly water yield in the XRB. Seventeen attributes were identified using the Budyko framework. The results show that: (1) the water yield of the XRB showed an increase trend from northeast to southwest from 2006 to 2020; (2) the transfer-in of unused land, grassland, woodland and farmland as well as the transfer-out of water and construction land have positive effects on the increase in water yield, and the change to construction land has the greatest impact on water yield; (3) water yield is positively correlated with NDVI and precipitation and negatively correlated with potential evapotranspiration; (4) climate change and land-use change contributed to water-yield changes of 67.08% and 32.92%, respectively.

There is an obvious imbalanced regional development among eastern, central, and western China. This is also a fundamental problem that policy makers and planners need to address. Specific to urban development, we wondered whether there were regional differences in urban sprawl and whether this trend was under control. By using the urban sprawl index (USI), this paper investigated the spatiotemporal pattern of urban sprawl from 2006 to 2019, and its regional difference and convergence among eastern, central, and western China. It finds that the cities with high, medium, and low sprawl in the east and west regions are distributed with a clear geographical pattern, while the distribution in the central region has no intuitive geographical features. Also, the proportion of cities with high sprawl in the eastern region is more than that in the other regions, with low sprawl in central China and medium sprawl in the western region. Moreover, urban sprawl in all three regions showed a downward trend, but this process was fluctuating and had obvious phase characteristics. It can be concluded that there is a convergence trend in urban sprawl in China over the research period, and the club convergence effect exists in the eastern, central, and western regions.

A substantially growing health expenditure has become an important global issue. Thus, how and why health expenditure is rising should be urgently investigated in systematic research. The Bayesian space-time model and the Bayesian least absolute shrinkage and selection operator (LASSO) model were employed in this study to investigate the spatiotemporal trends and influence patterns of total health expenditure per capita (THEPC) and total health expenditure (THEE) as a share of the gross domestic product (GDP) on the Chinese mainland from 2009 to 2018. The spatial distribution of THEE as a share of GDP in mainland China has shaped a distinct geographical structure with the characteristic of ‘west high/east low’. Its local increasing trends formed a geographical structure that exhibited a ‘north high/south low’ feature. The heterogeneity of the influence patterns of health expenditure was observed from east to west across China. Natural environmental factors, such as air pollution and green coverage, along with changes in dietary structures, have increasingly influenced the growth of health expenditures.

Investigating urban green innovation efficiency (UGIE) is imperative because it is correlated with the development of an ecological civilization and an innovative country. Spatiotemporal evolution and influencing factors of UGIE are two important scientific problems that are worth exploring. This study presents an indicator system for UGIE that includes input, expected output, and unexpected output, and employs a super-efficiency slacks-based measure (super-SBM) to calculate UGIE in 284 cities at or above the prefecture level in China from 2005 to 2020. Then, we adopted spatial auto-correlation to identify its spatial differences among these cities and Geodetector to evaluate its influencing factors. The results are as follows: (1) The overall UGIE tended to rise, except in northeastern China, megacities, and super large-sized cities. (2) The UGIE of Chinese cities exhibited remarkable spatial differences and auto-correlation, and the “low-low” type enjoyed the most local spatial auto-correlations. (3) Sociocultural factors represented by the number of collections in public libraries became the most important factors affecting the UGIE in China.

To explore the spatiotemporal evolution of carbon sinks in Shaanxi Province, and their impact mechanisms, this study used panel data from 107 counties (districts) in Shaanxi Province from 2000 to 2017. First, we conducted spatial distribution directional analysis and exploratory spatial data analysis (ESDA). Then, we constructed a geographic spatial weight matrix and used the spatial panel Durbin model to analyze the driving factors of carbon sink changes in Shaanxi Province, from the perspective of spatial effects. The results showed that: (1) The temporal evolution of carbon sinks during the study period showed an overall upward trend, but the carbon sinks of counties (districts) differed greatly, and the center of gravity of carbon sinks, as a whole, showed the characteristics of “south to north” migration. (2) The carbon sinks of Shaanxi Province have a significant positive global spatial autocorrelation in geographic space. The local spatial pattern was characterized by low-value agglomeration (low-low cluster) and high-value agglomeration (high-high cluster), supplemented by high-value bulge (high-low outlier) and low-value collapse (low-high outlier). (3) The result of the spatial measurement model proved that the spatial Durbin model, with dual fixed effects of time and space, should be selected. In the model results, factors such as population, per capita gross domestic product (GDP), local government general budget expenditure, and local government general budget revenue all reflect strong spatial spillover effects. Accordingly, in the process of promoting “carbon neutrality”, the government needs to comprehensively consider the existence of spatial spillover effects between neighboring counties (districts), and strengthen the linkage-management and control roles of counties (districts) in increasing carbon sinks.

The Central Plains has a long history, rich culture, unique geographical advantages, and profound cultural heritage. The occurrence of ancient cities in the Central Plains marks the formation of Chinese state-level societies. The number, size, and distribution of ancient cities have changed greatly from the late Yangshao to the Xia and Shang Dynasties, which reflects the evolution of settlement and social organization. In this study, Geographic Information System (GIS) spatial database technology was used to establish a spatiotemporal database of ancient cities in the late Yangshao, Longshan, as well as Xia and Shang Dynasties in the Central Plains. This paper uses GIS spatial analysis technology to analyze the relationship between the ancient city distribution and the geographical environment, as well as the evolution of ancient city's shapes and sizes. Furthermore, by using the method of the nearest neighbor distance and gravity center analysis, this paper discusses the agglomeration characteristics and gravity center evolution of ancient cities. The results show that: (1) Most of the ancient cities were distributed in areas below 500 m and within 3 km from the river during the time interval from the late Yangshao to Xia and Shang Dynasties; (2) The shape of the ancient cities gradually changed from circles to squares in the Central Plains, which became a unified model for the later ancient city design; (3) The sizes of the 18 ancient cities in the Yangshao period shared high similarity, with an average area of 20 hectares. The sizes of 24 ancient cities in the Longshan period increased significantly, with an average of 39 hectares. During the Xia and Shang Dynasties, there were 22 ancient cities with an average size of 340 hectares, and the grade of sizes became obvious, marking the entrance into Chinese state-level societies; (4) Cities were scattered in the decentralized pattern during the late Yangshao and Longshan periods, whereas they became agglomerative in Xia and Shang Dynasties. This reflects the evolution of the spatial scopes and social organizational forms; and (5) From the late Yangshao to Xia and Shang Dynasties, the gravity center of ancient cities moved around the Songshan Mountain from the northwest to the southeast and again to the northeast.

To examine the evolutionary pattern of livestock production activities in China, this paper analyzes the livestock production pattern from 1995 to 2020 using the models of center of gravity shift, spatial agglomeration and binary structure equilibrium index. The results show that: (1) overall, the degree of geographic agglomeration of China’s livestock industry shows a weak trend of enhancement, the center of gravity of production moves to the northwest, the main production areas gradually move to the three northern regions, and Inner Mongolia and Liaoning become emerging large livestock production provinces; (2) in terms of classification, there are obvious geographical characteristics in the movement of the center of gravity of production of various livestock products; some livestock product production is highly concentrated in a few provinces and produces (3) “Zhongtiao Mountains-Taihang Mountains” has become an important geographical division of spatial division of labor for livestock products in China, and the North China Plain and Loess Plateau on the left and right sides have become the landing areas of the center of gravity for the production of grain-consuming and herbivorous livestock products, respectively; 2006 was the peak of spatial concentration of livestock industry in China. 2006 is not only the peak inflection year of spatial concentration of livestock industry in China, but also the turning point of balanced development of grain-consuming livestock industry and herbivorous livestock industry. Therefore, following the intrinsic requirements of the new development concept on productivity layout, it is proposed to comprehensively implement the green spatial layout strategy, deeply promote the innovation of grass-livestock balance system, construct the green production mode of animal husbandry, coordinate and promote the “one place, one product” characteristic animal husbandry industrialization project and promote the transformation from a large country of animal husbandry production to a strong country of animal husbandry industry.

Mangrove ecosystems play a dominant role in global, tropical, and subtropical coastal wetlands. Remote sensing plays a central role in mangrove conservation, as it is the preferred tool for monitoring changes in spatiotemporal distribution. To improve correlated estimation accuracies and explore the influencing mechanisms based on the mangrove ground survey, this study used a support vector machine (SVM) machine learning and Res-UNet deep learning algorithms to identify the land area of mangrove forests and the crown surface cover area of mangrove forests in the Hainan Island from 1991 to 2021. Both classification techniques were verified by a confusion matrix, which from 1991 to 2021, revealed overall accuracies of 93.11 ± 1.54% and 96.43 ± 1.15% for SVM and Res-UNet, respectively. Res-UNet was more accurate in identifying the crown surface cover area, whereas SVM was more suitable for obtaining the land area. Furthermore, based on the crown surface cover area of the mangrove forests on the Hainan Island, influencing mechanisms were analyzed through dynamic changes and landscape patterns. Since 1991, the Hainan Island mangrove forest area has increased, with the center of mass moving from coastal areas to the ocean and increasing the overall landscape fragmentation. Moreover, the change in the mangrove forests area was correlated with economic development and the increasingly urban population of the entire island. Altogether, the reliable assessment of the tropical mangrove forest land area and crown surface cover provides an important research foundation for the protection and restoration plans of tropical mangrove forests.

Quantitative evaluation of the coupling coordination degree (CCD) between regional haze the disaster risk index (HRI) and urbanization development index level (UDI) is of great significance for the realization of regional sustainable development goals. Given the lack of the combination of remote sensing and statistical data to evaluate the CCD between two systems, the Chinese mainland’s 31 provinces and autonomous regions were taken to evaluate their HRI and UDI by building index systems. Then, an entropy method and one improved coupling coordination model were used to calculate and analyze the spatiotemporal characteristics of CCD between HRI and UDI during 2000–2020. The results showed that: (1) From 2000 to 2020, the value of HRI in China showed a “W” type change trend with its value increased from 0.7041 in 2000 to 0.8859 in 2020, indicating that haze pollution level showed a fluctuating downward trend; (2) From 2000 to 2020, China’s UDI values showed a gradual upward trend with its value increased from 0.1647 in 2000 to 0.4640 in 2020, with an average annual growth rate of 8.63%; (3) From 2000 to 2020, CCD values between HRI and UDI showed a fluctuating upward trend with its value increased from 0.5374 in 2000 to 0.7781 in 2020, with an average annual growth rate of 2.13%; the overall level of China’s CCD had raised from low coordination to moderate coordination, and eastern coastal provinces had higher CCD values, while those of central and western provinces had lower CCD values; (4) HRI, UDI and CCD could be well fitted with the R2 of 0.9869. Specifically, UDI had a higher contribution to improving the CCD than the HRI.

To further understand the evolution of regional tourism efficiency, a more systematic and theoretical analysis is required. Taking the urban agglomeration in the middle reaches of the Yangtze River as a case, this study applied evolutionary economic geography to analyze the evolutionary process of regional tourism efficiency. Data envelopment analysis (DEA) and the Malmquist index were used to measure the regional tourism efficiency and total factors productivity changes. Moreover, this paper employed the semi-variogram, Kriging interpolation, and Markov chain to explore the spatiotemporal evolution and transition characteristics of regional tourism efficiency. Finally, based on the test results of Geo-detector, the driving mechanism of the spatiotemporal evolution of regional tourism efficiency was constructed. The results show that the overall tourism development was inefficient, and the leading sources of inefficiency were primarily embedded in pure technology inefficiency, while the main contributor to the growth of total factor productivity was the positive technical change. Over time, the spatial spillover effect of regional tourism continued to increase, and the spatial pattern changed from divergence to convergence, resulting in co-evolution. The inertial trajectory of the evolution of regional tourism efficiency reveals a significant path dependence. Factors such as traffic accessibility, tourism resource endowments, tourism specialization, industrial structure, informatization, and openness can reasonably explain the evolution of regional tourism efficiency.

Significance Understanding what determines the distribution of biodiversity remains one of the great challenges in evolutionary biology and ecology. The Northern Hemisphere conifers do not follow a latitudinal diversity gradient and show a unique distribution pattern, that is most species are distributed at middle latitudes. To reveal the mechanisms underlying this pattern, we investigate the spatiotemporal evolution of the largest conifer genus Pinus. We find that the midlatitude region has been an evolutionary museum for Pinus, and particularly, topography has played the most important role in pine diversification. Moreover, our results indicate that pine’s preference of warm and somewhat drier habitats could be helpful for their adaptation to the Anthropocene climate warming, which is important for biodiversity conservation and forest management., How coniferous forests evolved in the Northern Hemisphere remains largely unknown. Unlike most groups of organisms that generally follow a latitudinal diversity gradient, most conifer species in the Northern Hemisphere are distributed in mountainous areas at middle latitudes. It is of great interest to know whether the midlatitude region has been an evolutionary cradle or museum for conifers and how evolutionary and ecological factors have driven their spatiotemporal evolution. Here, we investigated the macroevolution of Pinus, the largest conifer genus and characteristic of northern temperate coniferous forests, based on nearly complete species sampling. Using 1,662 genes from transcriptome sequences, we reconstructed a robust species phylogeny and reestimated divergence times of global pines. We found that ∼90% of extant pine species originated in the Miocene in sharp contrast to the ancient origin of Pinus, indicating a Neogene rediversification. Surprisingly, species at middle latitudes are much older than those at other latitudes. This finding, coupled with net diversification rate analysis, indicates that the midlatitude region has provided an evolutionary museum for global pines. Analyses of 31 environmental variables, together with a comparison of evolutionary rates of niche and phenotypic traits with a net diversification rate, found that topography played a primary role in pine diversification, and the aridity index was decisive for the niche rate shift. Moreover, fire has forced diversification and adaptive evolution of Pinus. Our study highlights the importance of integrating phylogenomic and ecological approaches to address evolution of biological groups at the global scale.

In the context of sustainable development, economic resilience provides a new research perspective for resource-based cities to resist external shocks and risks. The purpose of this study is to explore the characteristics and determinants of resource-based cities’ economic resilience in China, and to provide effective policy recommendations. This paper constructs an index system to measure the economic resilience of 114 resource-based cities in China from 2005 to 2019. This paper uses spatial analysis methods and the Theil index to reveal spatiotemporal evolution and regional disparities. Then, it uses the spatial Durbin model to reveal influencing factors from the perspective of spatial spillover effects. The conclusions are as follows: Firstly, the economic resilience of resource-based cities in China shows a growth trend. The spatial polarization of economic resilience in resource-based cities has intensified, showing a distribution pattern of high in the east and low in the west and northeast, with the cold spot of economic resilience moving from the southwest to the northeast. Secondly, the distribution of economic resilience in the eight economic regions is spatially heterogeneous. Inter-regional disparity is the main source of different economic resilience in the eight major economic regions. Thirdly, market potential and talent development potential are the direct drivers of economic resilience in resource-based cities. Nationalization, industrial specialization, and fiscal risk inhibit the development of economic resilience. Resource dependence not only hinders local innovation and transformation ability, but also negatively impacts the economic resilience of surrounding cities. Therefore, resource-based cities need to promote the diversification of industrial structures, and ensure resource allocation through the combination of the market and the government. At the same time, the government should build a new mechanism for coordinated regional development and open up the enclave economic model.

Forest carbon sinks (FCS) play an important role in mitigating global climate change, but there is a lack of more accurate, comprehensive, and efficient forest carbon stock estimates and projections for larger regions. By combining 1980–2020 land use data from the Northeast China Forestry (NCF) and climate change data under the Shared Socioeconomic Pathway (SSP), the land use and cover change (LUCC) of NCF in 2030 and 2050 and the FCS of NCF were estimated based on the measured data of forest carbon density. In general, the forest area of NCF has not yet recovered to the level of 1980. The temporal change in the FCS experienced a U-shaped trend of sharp decline to slow increase, with the inflection point occurring in 2010. If strict ecological conservation measures are implemented, the FCS of the NCF is expected to recover to the 1980 levels by 2050. We believe that the ecological priority (EP) scenario is the most likely and suitable direction for future development of the NCF. We also advocate for more scientific and stringent management measures for NCF natural forests to unlock the huge potential for forest carbon sequestration, which is important for China to meet its carbon neutrality commitments.

Promoting agricultural green growth has become an indispensable key content to speed up the process of agricultural modernization, has become a necessary prerequisite to achieve common prosperity of the rural people, and has become the basic practice of implementing people-centered development thought in the stage of high-quality development. Many researchers have studied the problems, level measurement and route choice of the growth of agriculture. However, there have been few studies on how to promote the agricultural green growth from the perspective of agricultural modernization, and how to combine the green agricultural GDP with the agricultural green total factor productivity (GTFP). To address this research inadequacy, in this paper, we focus on the time and space comparison of green agricultural GDP, agricultural GTFP, and their source decomposition, and summarize and discuss the key factors affecting agricultural GTFP. The results show that the share of output value of green agriculture in Tongren City is relatively high within the region of the province, and there is a large temporal and spatial difference between the change of agricultural GTFP and agricultural technology utilization efficiency and agricultural technology progress. At the same time, the improvement of economic development level can significantly promote the rise of agricultural GTFP, agricultural technology utilization efficiency, and agricultural technology progress. On balance, our results compare green agricultural GDP, agricultural GTFP, and their source decomposition in time and space, and reveals their evolution law and development trend from the perspective of high-quality development of agricultural modernization. In this way, we can provide an empirical basis and decision-making reference for accelerating the high-quality development of agricultural modernization.

To curb soil erosion, the Grain-for-Green Project has been implemented in the Loess Plateau region, and there have been few quantitative evaluations of the impact of ecological engineering on the spatial distribution of soil erosion on the Loess Plateau. In this paper, we used ArcGIS software, the Revised Universal Soil Loss Equation (RUSLE) model and the Geographic Detector (GeoDetector) model to investigate the changes in the spatial distribution of soil erosion and driving forces before and after the implementation of the Grain-for-Green Project in Yanhe River Basin, a typical area on the Loess Plateau. After the implementation of the Grain-for-Green Project, the soil erosion showed a decreasing trend over time and from local improvement to global optimization in space. The implementation of the Grain-for-Green Project led to changes in the dominant driving force of the spatial distribution of soil erosion, with the dominant driving force changing from the slope factor to the vegetation coverage factor. The main driving force of the two-factor interaction on soil erosion spatial differentiation changed from the slope factor and other factors to the vegetation coverage and other factors. The Grain-for-Green Project mainly influenced soil erosion by increasing the vegetation cover. The effect of the Grain-for-Green Project on the spatial distribution of soil erosion had hysteresis and spatial differences, and the direct and indirect driving forces generated by ecological engineering reached more than 50% on average.

Elucidating the correlation among tourism, CO2 emissions, and economic growth from a spatiotemporal standpoint is of utmost significance for the tourism industry responding to China’s “double-carbon” goal. This study expansively uses the bottom-up approach, Theil index, Exploratory Spatial Data Analysis (ESDA), and Logarithmic Mean Divisia Index (LMDI) method to calculate tourism CO2 emissions (TE) at different spatial scales in China during 2000–2019, and based on the TE, we further analyze the spatial heterogeneity of the TE intensity (TEI) and examine the spatiotemporal effects of driving factors on TE increases. The results revealed that (i) China’s TE increased from 3714.06 × 104 t to 19,396.00 × 104 t, and the TEI declined from 47 to 9 g/yuan during 2000–2019. (ii) The high-TEI provinces varied from agglomerative distribution in the north by western region to scattered distribution in the eastern region. (iii) China’s TEI exhibited increasing spatial differences, primarily within regions during 2000–2009, which also distributed with both the global and local agglomeration in space before 2014, and since then, only the local agglomeration enhanced and characterized by diffusing low–low (L–L) agglomeration from the east to the central and west regions. (iv) The tourism industrial scale and the industrial economy exerted cumulative effects on TE increases, and the energy intensity and energy structure exerted reduction effects. The spatial structure played different roles on TE among the regions. Policy implications are also discussed depending on the study results.

Food security is the foundation of development. We comprehensively characterized the spatiotemporal patterns of non-grain production (NGP) areas in China and elucidated the underlying factors driving NGP. Our objectives were to map NGP on cultivated land (NGPCL) in China, and to quantify its spatiotemporal patterns, to investigate the factors underlying NGP spatial differentiation, and to provide a scientific basis for developing NGP management policies and reference points for protecting cultivated land in other countries. We mapped NGPCL in China from 2000 to 2018 using remote sensing and geographic information system data. The spatiotemporal evolution of the NGP rate (NGPR) was also investigated. The dominant factors driving NGP progression and associated interactions were identified using geographic detectors. From 2000 to 2018, the NGPR gradually decreased from 63.02% to 52.82%. NGPR was high in the west and low in the east, and its spatial differentiation and clustering patterns were statistically significant. Precipitation, temperature, altitude, and soil carbon content were the dominant factors affecting the spatial differentiation in NGPR. The interaction between these factors enhanced the spatial differentiation.

The Belt and Road Initiative (BRI) has revealed that it is necessary to strengthen research on land use and land cover change (LUCC) and ecological risk in key regions of countries around the world. In this study, the spatiotemporal characteristics of LUCC in the five capitals of Central Asian countries within the BRI were analyzed. Based on the grid scale, a landscape pattern index was introduced to quantitatively evaluate the landscape ecological risk levels of the five capitals. The results showed the following: first, the components of land use types in the five capitals have different structural characteristics, which are mainly grassland, unused land, and cultivated land. The landscape types that changed significantly were water and unused land, while the construction land area showed a trend of continuous increase. Second, different capitals have different land-use transfer patterns. Akmola State is mainly converted from cultivated land to grassland; Chuy State is mainly converted from forest land to grassland; Dushanbe and Tashkent City are mainly converted from grassland to forestland; and Ahal State is mainly converted from grassland to unused land. Third, the overall landscape ecological risks of the five capitals were low. Akmola State had the largest proportion of lowest ecological risk areas, whereas Chuy State and Dushanbe City had an increasing trend of highest ecological risk areas. The level of ecological risk in Tashkent remained stable during the study period, and the highest ecological risk areas in Ahal State decreased to 49,227.86 km2. This study has enriched the research results of land use change and landscape ecological risk assessment of countries within the BRI and can provide a research reference for these countries and regions to achieve ecological sustainable development and strengthen ecosystem management.

To discuss the coupling coordination relationship among tourism carbon emissions, economic development and regional innovation it is not only necessary to realize the green development of tourism economy, but also great significance for the tourism industry to take a low-carbon path. Taking the 30 provinces of China for example, this paper calculated the tourism carbon emission efficiency based on the super-efficiency Slacks based measure and Data envelope analyse (SBM-DEA) model from 2007 to 2017, and on this basis, defined a compound system that consists of tourism carbon emissions, tourism economic development and tourism regional innovation. Further, the coupling coordination degree model and dynamic degree model were used to explore its spatiotemporal evolution characteristics of balanced development, and this paper distinguished the core influencing factors by Geodetector model. The results showed that (1) during the study period, the tourism carbon emission efficiency showed a reciprocating trend of first rising and then falling, mainly due to the change of pure technical efficiency. (2) The coupling coordination degree developed towards a good trend, while there were significant differences among provinces, showing a gradient distribution pattern of decreasing from east to west. Additionally, (3) the core driving factors varied over time, however, in general, the influence from high to low were as follows: technological innovation, economic development, urbanization, environmental pollution control, and industrial structure. Finally, some policy recommendations were put forward to further promote the coupling coordination degree.

Based on the 30 inland provincial samples of China from 2003 to 2019, this article analyzes the evolutionary characteristics of the coupling coordination between green finance and the ecological environment (CCFE) using ArcGIS 10.5 software and employs the spatial Durbin model to analyze the driving factors of the CCFE. The results can be concluded as follows: (1) the CCFE of China is at a moderately low level, with a fluctuating upward trend. Spatially, it presents a spatial distribution pattern—higher in the east and lower in other regions. In terms of types, the regions of the CCFE are more in primary coordination and basic un-coordination and less in moderate un-coordination and moderate coordination. There are more regions of the green finance lagged type, and relatively few regions have achieved the financial ecological synchronization type. (2) The CCFE hotspots are concentrated in the Pearl River Delta, with a spatial “increase–decrease” development trend. Additionally, the CCFE cold spots are concentrated in the upper Yellow River Basin, with a relatively stable spatial scope. (3) The CCFE shows a positive spillover effect and accumulative delivery effect in the economic geospatial space. The population urbanization rate and the number of granted patent applications have a significant positive impact on the CCFE, and the percentage of secondary industries to GDP has a negative impact accordingly. Spatially, the percentage of secondary industries to GDP and the number of granted patent applications of nearby provinces in the economic geospatial space have a negative impact on the local CCFE. (4) The impact and spatial effect of different factors on the CCFE are obviously different. Finally, policy implications on the coordinated development of green finance and the ecological environment are also made.

Grain production space, ecological service space and urban–rural development space are the classifications of land systems from the perspective of the dominant function of the land system. Grain production space reconstruction concentrates on the principal contradictions of land system changes, and is the key to exploring the transformation of land system. Therefore, the pathways, process and influencing factors of grain production space reconstruction in the Loess Plateau of Chian from 1980 to 2018 was explored from three dimensions of quantity–quality–spatial pattern in this study. Results showed that the quantity of grain production space showed a slight downward trend with a net decrease of 9156 km2 between 1980 and 2018, but its total quality showed a fluctuating growth trend under rain-fed conditions. Due to the intensification of human activities, grain production space was gradually fragmented, and the distribution tended to be decentralized, and the shape gradually became regular. Meanwhile, both the quantity and quality gravity center of grain production space moved to the northwest by 8.32 km and 86.03 km, respectively. The reconstruction of grain production space in the Loess Plateau was mainly realized through four pathways: Grain for Green, Urban Expansion, Deforestation and Reclamation, and Land Consolidation. The grain production space was mainly reconstructed through the pathway of Grain for Green after 2000. The four reconstruction pathways were the result of a combination of natural environment and socio-economic factors, but influencing factors had different strengths and directions for each reconstruction pathway. From the perspective of social economy–land use–ecological environment coupling, in order to maintain the sustainable development of the land systems, it is necessary to reduce the trade-offs of the functions of land systems as much as possible and strive to coordinate the relationship among grain production, ecological protection and high-quality development.

There are significant differences in the dominant driving factors of rocky desertification evolution in different historical periods in southwest karst mountainous areas. However, previous studies were mostly conducted in specific periods. In this study, taking Bijie City as an example, the spatial and temporal evolution pattern of rocky desertification in Bijie City in the recent 35 years was analyzed by introducing the feature space model and the gravity center model, and then the dominant driving factors of rocky desertification in the study area in different historical periods were clarified based on GeoDetector. The results were as follows: (1) The point-to-point B (bare land index)-DI (dryness index) feature space model has high applicability for rocky desertification monitoring, and its inversion accuracy was 91.3%. (2) During the past 35 years, the rocky desertification in Bijie belonged to the moderate rocky desertification on the whole, and zones of intensive and severe rocky desertification were mainly distributed in the Weining Yi, Hui, and Miao Autonomous Region. (3) During 1985–2020, the rocky desertification in Bijie City showed an overall weakening trend (‘weakening–aggravating–weakening’). (4) From 1985 to 2020, the gravity center of rocky desertification in Bijie City moved westward, indicating that the aggravating degree of rocky desertification in the western region of the study area was higher than that in the eastern region. (5) The dominant factors affecting the evolution of rocky desertification in the past 35 years shifted from natural factor (vegetation coverage) to human activity factor (population density). The research results could provide decision supports for the prevention and control of rocky desertification in Bijie City and even the southwest karst mountainous area.

Based on China’s provincial panel data from 2007 to 2017, this paper constructs a comprehensive indicator system for high-quality development of manufacturing from eight dimensions. Using the composite entropy weights method, kernel density estimation (KDE) and exploratory spatial data analysis (ESDA) to investigate its spatiotemporal evolution and spatial correlation characteristics. The results show that: (1) The high-quality development of the manufacturing industry shows a steady upward trend, but each dimension (subsystem) is quite different and can be divided into three types: growth type, flat type, and attenuation type. (2) The spatial distribution of the high-quality development of the manufacturing industry is highly consistent with the “Hu Huanyong Line”, and the overall layout is “high in the east and low in the west, high in the south and low in the north”. Seventy percent of the provinces are below the average level, with large interprovincial differences and significant spatial imbalance. (3) The high-quality development of the interprovincial manufacturing industry shows obvious spatial positive correlation. The hot spots are more active, and the spatial spillover effect is stronger—the Yangtze River Delta is the core, spreading outward in circles, and the main direction of diffusion is “from north to south”. In contrast, the cold spot area develops slowly and moves from south to north. Therefore, China should pay more attention to the “Botai Line”, which is perpendicular to the Hu Huanyong Line, and formulate differentiated development strategies to promote the coordinated development of the manufacturing industry.

The post-fire debris flow (PFDF) is a commonly destructive hazard that may persist for several years following the wildfires. Susceptibility mapping is an effective method for mitigating hazard risk. Yet, the majority of susceptibility prediction models only focus on spatial probability in the specific period while ignoring the change associated with time. This study improves the predictive model by introducing the temporal factor. The area burned by the 30 March 2020 fire in Xichang City, China is selected as an illustrative example, and the susceptibility of the PFDF was predicted for different periods of seven months after the wildfires. 2214 hydrological response events, including 181 debris flow events and 2033 flood events from the 82 watersheds are adopted to construct the sample dataset. Seven conditioning factors consist of temporal factors and spatial factors are extracted by the remote sensing interpretation, field investigations, and in situ tests, after correlation and importance analysis. The logistic regression (LR) is adopted to establish prediction models through 10 cross-validations. The results show that the susceptibility to PFDF has significantly reduced over time. After two months of wildfire, the proportions of very low, low, moderate, high, and very high susceptibility are 1.2%, 3.7%, 24.4%, 23.2%, and 47.6%, respectively. After seven months of wildfire, the proportions of high and very high susceptibility decreased to 0, while the proportions of very low to medium susceptibility increased to 35.4%, 35.6%, and 28.1%, respectively. The reason is that the drone seeding of grass seeds and artificial planting of trees accelerated the natural recovery of vegetation and soil after the fire. This study can give insight into the evolution mechanism of PFDF over time and reflect the important influence of human activity after the wildfire.

Analyzing the distribution characteristics and influencing factors of cultivated land in complex geomorphic areas is significant in evaluating the agricultural farming environment and formulating cultivated land protection measures. This study extracted cultivated land information based on multi-source remote sensing data, and analyzed the geomorphic differentiation of cultivated land distribution and climate response from 2000 to 2020 using the Gini coefficient, spatial autocorrelation analysis and geographic detector. The results show that cultivated land is mainly distributed in low-altitude hills and low-altitude small undulating mountains, and secondarily in low-altitude alluvial and proluvial plains and platforms. Moreover, from 2000 to 2020, the cultivated land in the high-altitude and high-altitude undulating mountains and medium and high-altitude undulating mountains in the Northwest Plateau of Sichuan showed an upward trend, while the cultivated land in the Sichuan Basin mainly increased from the north and south to the middle of the basin. In addition, the highest temperature has the strongest ability to explain the spatial heterogeneity of cultivated land. From the calculation results of the influence coefficient of a single climatic factor and the combined effect of multiple climatic factors, the main factors that affect the distribution of cultivated land are different in different geomorphological regions. Finally, it is proposed to formulate a long-term strategy for agricultural production to adapt to climate change in complex geomorphic areas in order to reduce the negative impact of environmental change on agricultural production.

Terrorist attacks have become a serious source of risk affecting the security of the international community. Using the Global Terrorism Database (GTD), in order to quantitatively study past terrorist attacks and their temporal and spatial evolution the analytic hierarchy process (AHP) was used to classify the degree of damage from terrorist attacks. The various factors influencing terrorist attacks were extracted and represented in three dimensions. Subsequently, using MATLAB for analysis and processing, the grading standards for terrorist attacks were classified into five levels according to the degree of hazard. Based on this grading standard, the top ten terrorist attacks with the highest degree of hazard in the past two decades were listed. Because the characteristics and habits of a terrorist or group exhibit a certain consistency, the K-means cluster analysis method was used to classify terrorists according to region, type of attack, type of target and type of weapon used by the terrorists. Several attacks that might have been committed by the same terrorist organization or individual at different times and in different locations were classified into one category, and the top five categories were selected according to the degree of sabotage inflicted by the organization or individual. Finally, the spatiotemporal evolution of terrorist attacks in the past three years was analyzed, considering the terrorist attack targets and key areas of terrorist attacks. The Middle East, Southeast Asia, Central Asia, and Africa were predicted to be the regions that will be most seriously affected by future global terrorist events. The terrorist attacks in Southeast Asia are expected to become more severe, and the scope of terrorist attacks in Africa is expected to widen. Civilians are the targets most at risk for terrorist attacks, and the corresponding risk index is considerably higher than it is for other targets. The results of this research can help individuals and the government to enable a better understanding of terrorism, improve awareness to prevent terrorism and enhance emergency management and rescue, and provide a solid and reliable basis and reference for joint counterterrorism in various countries and regions.

With the outbreak of the current global eco-environmental crisis, ensuring global and local ecological security (ES) has become a priority for many countries in the world. In the past few decades, social and economic development in China has induced many ecological and environmental problems, which have negatively impacted ES of China and the world. In recent years, with the increasing awareness of China’s ecological and environmental protection, the Chinese government has actively participated in global ecological and environmental governance and raised ES to the height of national security. A systematic and comprehensive assessment of ES is the basis of ES assurance, which can enable governments to accurately grasp the ES status of different regions and adopt targeted management measures. The ecological footprint (EF) model is a mature model that has been widely used for ES assessment. Thus, this study used an EF model with localized parameters analyzing the spatiotemporal changes in China’s ES from 2006 to 2016 on a provincial scale. Then, from an “occupation-carrying” perspective, this study explored the main aspect that induced changes in regional ES and identified the main type of ecological land that threatened regional ES. Results showed that a) during the study period, China’s ES status showed a deteriorating trend and the current ES is not optimistic. However, the ecological carrying capacity of most provinces in China has increased, indicating that China’s ecological and environmental protection has achieved initial results; b) currently, the provinces whose ES status are moderate unsafe and quite unsafe are mainly distributed in the eastern coastal region and the region near the boundary between the second and third ladders; c) the high-intensity occupation of the ecological environment and biological resources attributed to the rapid development of the social economy is the main cause for the negative changes in ES in most areas; d) for most provinces in China, cropland occupation and fossil energy consumption pose great threats to the regional ES status. China should jointly consider ES, energy security, and food security in its future development plans.

The problem of water pollution is a social issue in China requiring immediate and urgent solutions. In the Beijing–Tianjin–Hebei region, the contradiction between preserving the ecological environment and facilitating sustainable economic development is particularly acute. This study analyzed the spatiotemporal evolution of water pollutants and their factors of influence using statistics on the discharge of two water pollutants, namely chemical oxygen demand (COD) and NH3-N (ammonia nitrogen), in 154 counties in both 2012 and 2016 as research units in the region. The study employed Exploratory Spatial-Time Data Analysis (ESTDA), Standard Deviational Ellipse (SDE), and the Geographically Weighted Regression (GWR) models, as well as ArcGIS and GeoDa software, obtaining the following conclusions: (1) From 2012 to 2016, pollutant discharge dropped significantly, with COD and NH3-N emissions decreasing 65.9% and 47.2%, respectively, the pollutant emissions possessed the spatial feature of gradual gradient descent from the central districts to the periphery. (2) The water pollutants discharge displayed significant and positive spatial correlations. The spatiotemporal cohesion of the spatiotemporal evolution of the pollutants was higher than their spatiotemporal fluidity, representing strong spatial locking. (3) The level of economic development, the level of urbanization, and the intensity of agricultural production input significantly and positively drove pollutant discharge, the environmental regulations had a significant effect on reducing the emission of pollutants. In particular, the effect for NH3-N emissions reduction was stronger, the driving effect of the industrial structure and the distance decay was not significant.

With the rapid development of global tourism, identifying the vulnerability of tourism-based social-ecological systems (SESs) has become an important topic in sustainable development research. This study aimed to quantitatively evaluate the vulnerability, spatiotemporal evolution characteristics, and influencing factors of tourism-based SESs in the counties of the Three Gorges Reservoir Area (TGRA). A comprehensive evaluation system containing 46 indicators was constructed using a model that combines a social–economic–ecological model and a pressure–state–response model (SEE-PSR). The entropy and composite index methods were used to calculate the vulnerability values of the indicators, and Geodetector was used to explore the factors influencing system vulnerability in the whole study area. The results showed the following: (1) The mean value of the composite vulnerability index of the TGRA from 2010 to 2018 was 0.4849, indicating a moderate vulnerability state. The system vulnerability of the study area gradually decreased from moderately high to moderately low. (2) There were obvious differences in the spatiotemporal evolution of vulnerability in different counties, high and moderately high vulnerability continued to decrease, moderately low and low vulnerability increased, and moderate vulnerability showed a trend of increasing and then decreasing. Meanwhile, the relative differences in vulnerability among counties were small but gradually increasing. (3) System vulnerability was mainly caused by the social subsystem. Six factors, including the growth rate of the number of tourists and the amount of fiscal expenditure, were more likely to contribute to system vulnerability than other factors. The interaction types were mainly nonlinear enhancement types, supplemented by two-factor enhancement. This study presents an approach for evaluating the vulnerability of tourist destinations and constructing an evaluation index system. In this way, it has reference value for reducing regional vulnerability and promoting sustainable development.

As one of the most widespread pollutants worldwide, nitrogen has long been a concern in the environment, including groundwater. However, due to the limitations of investigations and study progress, there is still a poor understanding of groundwater nitrogen pollution and its potential effects on human health in many areas, particularly in developing countries. The spatiotemporal evolution of groundwater nitrate nitrogen levels and potential human health risks in the Songnen Plain, Northeast China were comprehensively studied based on both our own test data and available published data that were collected by us over a study period from 1995 to 2015. Groundwater nitrate nitrogen concentrations exhibited significant temporal and spatial differences: there was an increasing trend with time; and the distribution of high concentration areas expanded from the central and western areas to the east with time. The similar pattern existed in the potential health risks posed to the residents considering the two exposure pathways including drinking water and dermal contact. The effects of groundwater nitrate nitrogen on human health depend on the nitrate concentration but there were also age differences, namely, in the order of infants > children > adult females ≈ adult males, according to the hazard quotient (HQ) used in the human health risk assessment (HHRA) model. The spatiotemporal evolution of groundwater nitrate nitrogen levels and potential human health risks indicate that the issue of nitrogen pollution in groundwater in the study area is worsening and needs further attention. The drivers that increased nitrate nitrogen concentrations in the groundwater of the study area were the increased fertilizer use due to the increased cultivated land area and implementation of a land fertility policy by the local government. It should be acknowledged that the results have uncertainties that not only come from the layout of sampling points and selection of spatial interpolation methods but also come from the parameter settings in the assessment model and assumptions of drinking water scenarios. However, the conclusions still have important reference value for groundwater pollution control and management and human health risk supervision and early warning.

Droughts are one of the primary natural disasters that affect agricultural economies, as well as the fire hazards of territories. Monitoring and researching droughts is of great importance for agricultural disaster prevention and reduction. The research significance of investigating the hysteresis of agricultural to meteorological droughts is to provide an important reference for agricultural drought monitoring and early warnings. Remote sensing drought monitoring indices can be employed for rapid and accurate drought monitoring at regional scales. In this paper, the Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices and the surface temperature product are used as the data sources. Calculating the temperature vegetation drought index (TVDI) and constructing a comprehensive drought disaster index (CDDI) based on the crop growth period allowed drought conditions and spatiotemporal evolution patterns in the Volgograd region in 2010 and 2012 to be effectively monitored. The causes of the drought were then analyzed based on the sensitivity of a drought to meteorological factors in rain-fed and irrigated lands. Finally, the lag time of agricultural to meteorological droughts and the hysteresis in different growth periods were analyzed using statistical analyses. The research shows that (1) the main drought patterns in 2010 were spring droughts from April to May and summer droughts from June to August, and the primary drought patterns in 2012 were spring droughts from April to June, with an affected area that reached 3.33% during the growth period; (2) local drought conditions are dominated by the average surface temperature factor. Rain-fed lands are sensitive to the temperature and are therefore prone to summer droughts. Irrigated lands are more sensitive to water shortages in the spring and less sensitive to extremely high temperature conditions; (3) there is a certain lag between meteorological and agricultural droughts during the different growth stages. The strongest lag relationship was found in the planting stage and the weakest one was found in the dormancy stage. Therefore, the meteorological drought index in the growth period has a better predictive ability for agricultural droughts during the appropriately selected growth stages.

Background Population ageing is an increasingly severe global issue. And this has been posing challenges for public health policies and medical resource allocation There are various features of population ageing in different regions worldwide. Methods All data were obtained from the health data of World Bank Open Data. Quantile linear regression was used to subtly measure the common variation tendency and strength of the global ageing rate and ageing population. The Bayesian space-time hierarchy model (BSTHM) was employed to assess the detailed spatial temporal evolution of ageing rate and ageing population in global 195 countries and regions. Results Annual growth of the ageing (65 and above) rate occurred on six continents: Europe (0.1532%), Oceania (0.0873%), Asia (0.0834%), South America (0.0723%), North America (0.0673%) and Africa (0.0069%). The coefficient of variation of the global ageing rate increased from 0.54 in 1960 to 0.69 in 2017. The global ageing rate and ageing population increased over this period, correlating positively with their quantiles. Most countries (37/39) in Europe belong to the top level with regard to the ageing rate, including the countries with the greatest degree of ageing—Sweden, Germany, Austria, Belgium and the UK—whose spatial relative risks of ageing are 3.180 (3.113–3.214), 3.071 (3.018–3.122), 2.951 (2.903–3.001), 2.932 (2.880–2.984) and 2.917 (2.869–2.967), respectively. Worldwide, 44 low ageing areas which were distributed mainly in Africa (26 areas) and Asia (15 areas) experienced a decreasing trend of ageing rates. The local trends of ageing population in the 195 areas increased. Conclusions The differentiation of global population ageing is becoming increasingly serious. Globally, all 195 areas showed an increasing local ageing trend in absolute terms, although there were 44 low-ageing areas that experienced a decreasing local trend of ageing rate. The statistical results may provide some baseline reference for developing public health policies in various countries or regions, especially in less-developed areas.

Velike pogibeljne nesreće u ugljenokopima u osnovi se pripisuju nedovoljnom razumijevanju ili propustu stvaranja potpunog prostornog strukturnog mehaničkog modela iskopa tijekom eksploatacije kao i prostornom gibanju do kojeg je tijekom vremena došlo zbog samog iskapanje, iskapanja u krivo vrijeme, kao i neodgovarajućeg održavanja kolnika i pomicanja radne površine. U svrhu učinkovitog proučavanja i analize mehanizma zbog kojeg dolazi do velikih nesreća, primijenjena je metoda zasnovana na praćenju naprezanja i pomicanja iskopa da bi se izveo postupak koji dovodi do loma gornjih slojeva, te je dalje predložena metoda utvrđivanja stabilnosti iskopa na temelju kvalitativne identifikacije dinamike. Proučavanjem se ustanovilo da se stabilnost iskopa tijekom vađenja rude može podijeliti u dvije faze: (1) nesigurna faza t.j. udaljenost za koju je radna površina pomaknuta Lx < širine radne površine L0; (2) sigurna faza t.j. udaljenost za koju je radna površina pomaknuta Lx > širine radne površine L0. Ti rezultati istraživanja čine osnovu za razumno određivanje odnosa prostor-vrijeme u postupku rudarenja., Major hazardous accidents in coal mines are basically attributable to a lack of understanding of or the failure to establish a complete spatial structural mechanical model of the stope during the course of exploitation, as well as of the spatial movement over time caused by the mining itself, mining at the wrong time, as well as improper roadway maintenance and advance of the work face. To efficiently study and analyze the mechanism behind major stope disasters, a method based on monitoring the stress and displacement of stopes was adopted to deduce the process whereby the overlying strata fracture, and a method of ascertaining stope stability based on qualitative identification of the dynamics was further proposed. The study found that the stability of stopes during the process of mining the face can be divided into two stages: (1) Unstable stage: i.e. the distance the work face has advanced Lx < width of work face L0; (2) Stable stage: i.e. the distance work face has advanced Lx > width of work face L0. These research results provide a basis for reasonable determination of a space-time relationship for the mining process.

The Guangdong−Hong Kong−Macau Greater Bay Area (GBA) of China is one of the major bay areas in the world. However, the spatiotemporal characteristics and rationalities of urban expansions within this region over a relatively long period of time are not well-understood. This study explored the spatiotemporal evolution of 11 cities within the GBA in 1987−2017 by integrating remote sensing, landscape analysis, and geographic information system (GIS) techniques, and further evaluated the rationalities of their expansion using the urban area population elastic coefficient (UPEC) and the urban area gross domestic product (GDP) elastic coefficient (UGEC). The results showed the following: (1) Guangzhou, Shenzhen, Foshan, Dongguan, Zhongshan, and Zhuhai experienced unprecedented urbanization compared with the other cities, and from 1987 to 2017, their urban areas expanded by 10.12, 11.48, 14.21, 24.90, 37.07, and 30.15 times, respectively; (2) several expansion patterns were observed in the 11 cities, including a mononuclear polygon radiation pattern (Guangzhou and Foshan), a double-nucleated polygon pattern (Macau and Zhongshan), and a multi-nuclear urbanization pattern (Shenzhen, Hong Kong, Dongguan, Jiangmen, Huizhou, Zhaoqing, and Zhuhai); (3) with regard to the proportion of area, the edge-expansion and outlying growth types were the predominant types for all 11 cities, and the infilling growth type was the one of the important types during 2007−2017 for Shenzhen, Hong Kong, Dongguan, Zhongshan, and Foshan; (4) the expansion of most cities took on an urban-to-rural landscape gradient, especially for Guangzhou, Shenzhen, Foshan, Zhongshan, Dongguan, and Zhuhai; and (5) the rationalities of expansion in several time periods were rational for Guangzhou (1997−2007), Hong Kong (2007−2017), Foshan (1987−2007), Huizhou (1987−1997), and Dongguan (1997−2007), and the rationalities of expansion in the other cities and time periods were found to be irrational. These findings may help policy- and decision-makers to maintain the sustainable development of the Guangdong−Hong Kong−Macau Greater Bay Area.