Explore the vast range of titles available.

Promoting foreign trade development based on a circular economy is the key to dealing with the problems between the resource environment and economic growth. This paper first constructs a comprehensive evaluation index system of circular economy and foreign trade by taking 19 urban agglomerations in China as research objects. Secondly, the entropy value method is used to measure and analyze the circular economy development and foreign trade development of Chinese urban agglomerations from 2014 to 2021. Finally, the coupled coordination level of circular economy and foreign trade of Chinese urban agglomerations was measured using the coupled coordination degree model in physics, and the spatial and temporal evolution process of the synergistic development of circular economy and foreign trade of Chinese urban agglomerations was studied. The results show that the mean values of the coupling coordination degree of circular economy and foreign trade in the east and west regions of China from 2014 to 2021 are generally maintained above 0.85, and all tend to 0.95 equilibrium value, which is at a high coupling stage, indicating that there is an obvious interaction between the circular economy and foreign trade in China. This paper analyzes the spatial and temporal evolution of the coupling degree and coupling coordination degree of circular economy and foreign trade in Chinese urban agglomerations and provides a theoretical basis for governments at all levels to formulate policies and regulations on the synergistic development of circular economy and foreign trade in Chinese urban agglomerations.

Investigating the characteristics and mechanisms of the spatial and temporal variations of commercial land prices and its major subdivisions has great theoretical and practical significance in the study of urban economy and its spatial refinement management. Unlike general commodity prices, land prices are influenced by geographical location and tend to fluctuate over time. However, most scholars have not explored the influence mechanism of commercial land prices in both time and space. To help bridge this gap, this study takes the sample commercial land prices in the main urban area of Hangzhou from 2006 to 2015 as the empirical research object and investigates the spatiotemporal evolution mechanism of urban commercial land prices through a comparative analysis of the multiple regression analysis (MRA) with ordinary least squares (OLS), the geographically weighted regression (GWR), the temporally weighted regression (TWR), and the geographically and temporally weighted regression (GTWR) models. Results indicate that the land prices of land for financial facilities (Commercial Land Category 1) and commercial-business land (Commercial Land Category 2) in Hangzhou show different spatial and temporal evolutions and are influenced by the common factors of residential land price level (PL), maturity of living services (EN), and plot ratio (FRO) in the district. Meanwhile the main difference between the two influencing factors is the significant difference in sensitivity to locational centrality and industrial structure. Furthermore, we find that the spatial and temporal evolution of commercial land prices has three main mechanism: location selection, point-axis evolution, and function-promoting. Our findings will provide guidelines for scientifically guiding the coordinated development of urban land price and industrial economy and realizing the fine management and allocation of urban spatial resources.

The northern desert of China plays an important strategic role in land resource security and national economic development. Research on the spatio-temporal changes of ecological sensitivity can provide a scientific reference for desert management and ecological restoration in arid and semi-arid areas in northern China. This paper takes the northern desert of China as the research area, uses the spatial distance model to build a comprehensive ecological sensitivity evaluation index system, and discusses the spatio-temporal evolution characteristics of ecological sensitivity in the area from 1981 to 2022. The results show the following: (1) The land use types in the northern desert of China are mainly sandy land, grassland and other lands. The changing areas of grassland and other lands are 74,353.14 km2 and 50,807.97 km2, which is an important factor affecting the ecological sensitivity in the northern desert of China. (2) Five aspects, including terrain, climate, hydrology, soil and vegetation, influence and restrict each other, and jointly create the background conditions for the distribution and change of ecological sensitivity in the northern desert of China. Climate and terrain are the most important influencing factors affecting the ecological sensitivity of northern desert of China. Vegetation is the most active and basic factor affecting the ecological sensitivity of northern desert of China. Hydrology and soil have a certain limiting effect on the ecological sensitivity of northern desert of China. (3) The spatial heterogeneity of ecological sensitivity in the northern desert of China is significant, showing the characteristics of high volatility in the west, low volatility in the central region and low volatility in the east. (4) For nearly 42 years, ecological sensitivity of the northern desert of China shows first increasing and then decreasing characteristics. The area of the fluctuation reduction zone accounts for 26.34% of the total research area, of which the area of extreme sensitivity and mild sensitivity varies by 11.84% and 65.28%, respectively. (5) The spatial aggregation characteristics of ecological sensitivity have changed significantly, and the area of high–high and low–low agglomeration areas has also been decreasing, indicating that the environment is obviously improving. In the future, we should pay attention to the efficient use of natural resources in the northern desert of China and strengthen the protection of all kinds of land to achieve the sustainable development of the regional environment.

To promote the resilient and coordinated development of regional economies, in this study, to construct an index system, we used the entropy weight method to measure the agricultural economic resilience of 11 prefecture-level cities in Jiangxi province, China during 2011–2020, and we analyzed the characteristics of their spatial-temporal pattern evolution. We used the Theil index method to analyze the main sources of their spatial differences. The results showed that: First, the mean value of agricultural economic resilience of prefecture-level cities in Jiangxi trended upward during 2011–2020. Among the prefecture-level cities, Ganzhou had the highest mean agricultural economic resilience value, while Yingtan had the lowest. From the perspective of regional division, the agricultural economy in southern Jiangxi was the most resilient, whereas that in northeast Jiangxi was the least. Second, since 2011, the overall difference in agricultural economic resilience in the four regions of Jiangxi has trended downward, with the inter-regional difference being the main source of the overall difference. Based on this, we provide the following policy implications: first, to continuously enhance the intrinsic dynamics of the agricultural economic resilience and strengthen policy support in Jiangxi; second, to coordinate the development of regional agricultural economic resilience and achieve overall improvement.

Under the stress of the global change, rocky desertification has become a serious environmental problem in the Karst Mountain area. At present, few remote sensing monitoring research works on rocky desertification based on feature space model have been conducted and reported. In this study, the Albedo-LST feature space remote sensing monitoring index based on point-point model has been proposed, and subsequently the spatio–temporal evolution pattern and driving mechanism of rocky desertification in Dafang district from 1986 to 2019 were analyzed. The results show that: (1) The point-point Albedo-LST feature space model of rocky desertification has good applicability with the overall accuracy of 90.79%; (2) From 1986 to 2019, the rocky desertification in Dafang district first showed an increasing trend (1986–2005) and then a decreasing trend (2005–2019); (3) The comprehensive evolution frequency of rocky desertification during 2001–2005 was the largest with 7.51% a , which was related to the implementation of the Grain for Green Project; (4) The single factor with the largest contribution rates to rocky desertification are land use type, landform, and temperature. The interactive factors with the largest explanatory power are temperature ∩ land use type and landform ∩ land use type. The research results can provide decision support for the prevention and control of rocky desertification in Southwest China.

In today's digital economy, green innovation has become a focal point of global attention. This paper takes Anhui province as the research subject and discusses its carbon emission level through the method of space–time evolution. Moreover, it defines the role and impact relationship of green innovation, aiming to promote the development of green innovation in Anhui. This study adopts the spatio‐temporal evolution analysis method, integrating the green innovation data and digital economy development indicators in Anhui in recent years. Moreover, in order to deeply understand the internal interrelation between green innovation and the digital economy, geographic information system (GIS) technology and statistical knowledge are used. At the same time, the data from different periods and spatial scales are compared, and the spatio‐temporal evolution between them is understood using dynamic methods. It is found that in light of the current rapid economic progress, the level of green economy innovation in Anhui province is increasing overall, but at different spatial and temporal scales, the level of green innovation is slightly affected by the digital economy. In some periods and regions, the digital economy as a whole can promote green innovation levels, but the impact of this increase varies from region to region and over time. Through the analysis of temporal and spatial evolution, it is found that the level of green innovation in Anhui Province will be affected by the local digital economy, which is not regular, but presents the characteristics of diversity and complexity. Therefore, it is crucial to comprehensively consider the regional differences and progress of the digital economy to support the economic development and environmental protection of Anhui Province. Future research can be initiated by exploring the developmental mechanisms linking green innovation levels and the mode of digital development to provide more detailed policy recommendations for the advancement of green innovation. The digital economic level of different cities in Anhui from 2011 to 2022 was measured using the entropy weight method.

The rainfall erosivity in China have shown different change characteristics and patterns at different spatial-temporal scales. In this article, we introduced a gravity centre model for use in studying and analyzing the spatial-temporal distribution patterns of rainfall erosivity in China in the past 58 years combined with traditional geostatistical analysis methods at different spatial-temporal scales. During 1961-2018, rainfall erosivity in China showed a decreasing trend from southeast to northwest in spatial distribution. Moreover, the spatial distribution patterns of the annual average rainfall erosivity had been negatively affected by altitude. In terms of interannual variability, rainfall erosivity had shown a fluctuating upward trend in the past 58 years, with a steep upward slope in 1982 and a steep downward slope in 1990. In the past 58 years, the gravity centre of rainfall erosivity in China had moved southeastward, which indicated that the increment and increasing rate of rainfall erosivity in eastern and southern China were greater than those in western and northern China. These results could provide important data to support decisions regarding the prevention and control of soil erosion at regional and national scales.

The spatio–temporal evolution of the Pacific blocking frequency (PBF) that is based on a two–dimensional blocking index is investigated during the recent 40–winter (1979/80–2018/19) months (December–January–February). It is found that maximum PBF appears in January within the key area of 140° E–160° W, 50°–70° N. The key–area Pacific blocking in January is more active during the first (1980–1988) and the third (2009–2019) periods than during the second period (1989–2008). There is a positive 500 hPa–geopotential height (Z500) anomaly over the mid–latitude Pacific and a negative one over the high latitude area between the first two periods (second minus first). This pattern can cause an anomalous westerly circulation over the mid–high Pacific sector, which indicates a weakening of the Pacific blocking activity during the second period. This connects to a positive two–meter air temperature (T2m) anomaly over the northeastern Asia and mid–western Pacific, and a negative one over the high–latitude area. The difference of Z500 between the third and the second periods (third minus first) is opposite to that between the second and the first periods, which leads to more Pacific blocking events during the third period. This is related to a positive T2m anomaly over the high–latitude area and a negative one over the mid–latitude area of Asia and the western Pacific. Furthermore, the correlation coefficient between the variables (Z500, T2m, 200 hPa–zonal wind) and the key–area PBF confirms the above results.

Despite achieving remarkable development, China’s agricultural economy has been under severe environmental pressure. Based on previous studies, the present study further considers the sources of agricultural carbon emissions in depth, estimates China’s agricultural carbon emissions from 1997 to 2016, and analyzes the agricultural pollution faced by China and its provinces. The study estimates the amount and intensity of agricultural carbon emissions in China from five carbon sources—agricultural materials, rice planting, soil N2O, livestock and poultry farming, and straw burning—and analyzes their spatial and temporal characteristics. The following results were obtained: (1) between 1997 and 2016, the amount of agricultural carbon emissions in China generally increased, while the intensity of agricultural carbon emissions decreased; (2) in the same period, the amount of carbon emissions from each category of carbon source generally increased, with the exception of rice planting; however, the amount of emissions fluctuated; (3) the amount and intensity of carbon emissions varied greatly among provinces; (4) the emissions from different categories of carbon source showed different concentration trends and agglomeration forms; (5) China’s agricultural carbon emissions showed obvious spatial correlation, which overall was high–high agglomeration; however, its carbon emissions gradually weakened, and the spatial agglomeration of agricultural carbon emissions in each province changed between 1997 and 2016.

The Qinghai-Tibetan Plateau (QTP) is the highest plateau in the world. Under the background of global change, it is of unique significance to study the net primary productivity (NPP) of vegetation on the QTP. Based on the Google Earth Engine (GEE) cloud computing platform, the spatio-temporal variation characteristics of the NPP on the QTP from 2001 to 2017 were studied, and the impacts of climate change, elevation and human activity on the NPP in the QTP were discussed. The mean and trend of NPP over the QTP were “high in the southeast and low in the northwest” during 2001–2017. The trend of NPP was mostly between 0 gC·m−2·yr−1 and 20 gC·m−2·yr−1 (regional proportion: 80.3%), and the coefficient of variation (CV) of NPP was mainly below 0.16 (regional proportion: 89.7%). Therefore, NPP was relatively stable in most regions of the QTP. Among the correlation coefficients between NPP and temperature, precipitation and human activities, the positive correlation accounted for 81.1%, 48.6% and 56.5% of the QTP area, respectively. Among the two climatic factors, the influence of temperature on NPP was greater than that of precipitation. The change of human activities and the high temperature at low altitude had positive effects on the increase of NPP.