Much of China's cropland is located in fragile environments, making its rational use and protection essential for mitigating environmental risks and safeguarding food security. However, the diverse trajectories of cropland use change driven by unique natural conditions have not received sufficient attention. Taking Ordos as a case study, this study analyzes continuous land use data from 2010 to 2020 and identifies four cropland trajectories: very stably used, generally stably used, recurrently transitioning, and abandoned. We employ a multi-level regression model to examine the drivers of cropland use change, accounting for parcel- and regional-level factors and their interactions. The results show that: (1) In Ordos, 54% of cropland parcels remained very stably used between 2010 and 2020, while 25% showed general stability with intermittent fallowing. Recurrently transitioning and abandoned parcels accounted for 14% and 7%, respectively. This distribution significantly differs from the patterns observed in plains and mountainous regions. (2) Cropland use trajectories are primarily dictated by parcel-level natural conditions and accessibility, while the impact of regional-level processes is relatively weaker. (3) Interactions between regional and parcel-level factors significantly shape cropland use trajectories. Notably, rural depopulation exacerbates parcel-level constraints, focusing instability risks on cropland with poor conditions. Given the recurrent transitions in cropland use, we suggest replacing rigid regulations with more flexible management in fragile ecosystems. Such flexibility can better promote both sustainable utilization and ecological conservation.

High-speed rail (HSR) expansion has led to regional restructuring of industrial and population development. However, little is known about how these effects vary across regions with similar development levels. This study considers 132 cities in Jiangsu and Zhejiang, two developed provinces in eastern China, as examples to comparatively examine the effects of HSR on changes in employed and resident populations over the last decade. The HSR network expansion led to a decreasing ratio of the employed population to the resident population in Jiangsu, whereas an opposite trend was observed in Zhejiang. Large cities in Jiangsu reinforced their attractiveness to both employed and resident populations, and small cities are facing population loss. In contrast, small cities in Zhejiang benefited from HSR development, similar to large cities. These results suggest that regional disparity in Jiangsu amplified the siphoning effect of HSR network development, whereas the relatively balanced development in Zhejiang promoted the optimization effect of HSR network development. This study contributes to understanding the varied effects of HSR development and how they relate to the initial spatial structures of different regions.

Plateau basin, characterized by strong radiation, climate variability, and ecological fragility, pose complex challenges for agriculture, requiring a balance between production and ecological goals. The unclear mechanisms underlying the evolution and interaction of agricultural functions (AFs) constrain the formulation of spatial and environmental policies in plateau regions.This research aims to understand the dynamic changes and trade-offs among different AFs in a typical plateau basin. It quantitatively assesses three AFs (production, social, and ecological functions) and nine sub-functions in the Dianchi Lake Basin, examining their spatiotemporal evolution and interrelations, with a particular focus on trade-off analysis. It also identifies the factors influencing trade-offs between different AF pairs using the Random Forest algorithm and SHapley Additive exPlanations. The results indicate that in the Dianchi Lake Basin, agricultural functions exhibit significant spatial heterogeneity. The production and social functions have gradually declined, while ecological functions have strengthened. The trade-offs between production and ecological functions are pronounced, with high trade-off zones located in townships around the lake. This research reveals that socioeconomic development, natural factors, location, and environmental regulations influence AF trade-offs. Key thresholds include slopes of 5-12°, annual precipitation of 1010-1050 mm, and distances within 2 km of the lake. The results also highlight the interactive effects and threshold dynamics of influencing factors. These findings provide insights for sustainable agricultural development and ecological protection in plateau basins.

A robust ecological security network (ESN) is essential for ensuring regional ecological security, improving fragile ecological conditions, and promoting sustainable development. Climate change and land use/cover change (LUCC) influence the structure and connectivity of the ESN by impacting ecosystem services (ESs). Previous studies primarily focused on the overall effects of LUCC on ESN changes, but they largely overlooked the effects of detailed LUCC transitions. In this study, we evaluated changes in the structure and connectivity of the ESN in the Songnen Plain (SNP), Northeast China, over the past 30 yr (1990s-2020s) using circuit theory and graph theory. We further explored the effects of climate change, LUCC, and detailed LUCC transformations on ESN changes through factorial control experiments. Results revealed a 24.86% decrease in ecological sources and a 27.06% decrease in ecological corridors, accompanied by a decline in ESN connectivity from the 1990s to the 2010s. Conversely, from the 2010s to the 2020s, ecological sources increased by 14.71% and ecological corridors increased by 25.71% due to ecological projects such as returning farmland to wetlands, resulting in an overall increase in ESN connectivity. The changes in ESN structure were primarily attributed to LUCC effects, followed by climate change effects and their interactions. In contrast, the changes in connectivity were significantly affected by climate change, followed by interactive effects and LUCC. Through detailed examination of LUCC transformation effects, we further found that the changes in ESN structure were primarily attributed to wetland loss, followed by deforestation and urban expansion. Meanwhile, the changes in ESN connectivity were mainly due to the effects of wetland loss, urban expansion and deforestation. Notably, the adverse effects of wetland loss partly offset climate change benefits on ESN. Our study offers valuable insights for developing future land management policies and implementing ecological projects, aimed at maintaining a stable ESN and ensuring sustainable human development.

Effectively evaluating the carrying capacity of rural resources and the environment, and identifying key factors for its enhancement, are critical for rural sustainability. To meet this objective, a coupling model for rural resource and environmental carrying capacity (RRECC) was constructed using multi-source spatiotemporal data. The model incorporates the zonal division index of resources and environment (ZI), the categorization index of socioeconomic development (CI), and the grading index of population concentration (GI). Spatial autocorrelation and factor contribution analysis were employed to simulate the RRECC of China and identify key factors for enhancing this capacity. The results show that the overall carrying capacity status of China’s rural resources and environment is favorable. Out of 30,055 rural study units, 91.076% are in balance and surplus states, encompassing 90.044% of the population and 66.451% of the land. The carrying capacity exhibits a spatial pattern of higher capacity in the east and south, with significant spatial clustering. The contributions of socioeconomic development and ecological environment protection to carrying capacity are 28.018% and 27.625%, respectively. Therefore, enhancing carrying capacity requires synergistic advancement in both areas. This study advances the evaluation methods for resource and environmental carrying capacity (RECC) in rural areas, providing scientific guidance and support for the realization of the great goal of the Rural Revitalization Strategy.

In the context of industrial regionalization and globalization, biodiversity footprints are potentially transferred through supply chain networks. Current research on biodiversity footprints primarily focuses on global scales or developed regions, with limited understanding of biodiversity loss patterns in developing countries. We develop this dataset by constructing species threats satellite account to quantify threats posed by 19 industrial sectors across 30 provinces in China. We provide two versions of the biodiversity footprint dataset: one encompassing 446 species (including Near Threatened species) and the other limited to 352 species (excluding Near Threatened species). Results show that incorporating Near Threatened species significantly alters biodiversity footprint assessments across taxonomic, sectoral and provincial dimensions. Overall, there was a significant spatial variation in biodiversity footprint among provinces. While industry rankings differ regionally, agriculture remains a leading contributor in most provinces. This database supports the development of place-specific biodiversity protection strategies, and the integration of biodiversity conservation into the industrial relocation initiatives, particularly in biodiversity hotspot areas in Southwest China, such as provinces of Yunnan and Sichuan.

As the global population ages, enhancing community outdoor public spaces to accommodate the needs of senior citizens has emerged as a critical challenge. This research delves into the intricate relationship between community outdoor public spaces and the behavioral patterns of the elderly, seeking to inform strategies for optimizing these spaces. The complexity and diversity of the mechanisms linking elderly behaviors with the characteristics of their outdoor environments pose challenges in identifying clear guidelines for improvement. Traditional methods of collecting behavioral data, such as questionnaires and manual observations, are time-consuming and limit the scope and detail of data captured. In contrast, computer vision technologies offer an efficient alternative for gathering behavioral data. However, the application of computer vision to specifically identify various behaviors of the elderly population presents certain challenges. This study addresses two key issues: improving the use of computer vision to recognize diverse behaviors of the elderly; and elucidating how community outdoor public spaces shape the outdoor activities of seniors and identifying crucial influencing factors. The research proceeds by initially categorizing elderly behavior characteristics and typologies of outdoor public spaces based on the physiological and psychological needs of seniors. The spatial elements are classified into four metrics: spatial, greenness, functional facilities, and accessibility. A computer vision-based behavior detection algorithm is then constructed to effectively identify six typical activities of the elderly: exercising, jogging, sitting, standing, walking, and playing chess or cards. Subsequently, a set of quantifiable indicators for community outdoor public spaces is established, and nonlinear machine learning models (Random Forest, Gradient Boosting Decision Tree, and eXtreme Gradient Boosting) are employed to reveal the association mechanisms between these six behaviors and the four categories of spatial metrics. The findings highlight 16 major characteristics that have a significant impact on elderly behavior, such as area size, form, green enclosure, and types of workout equipment.

Based on the super-efficiency SBM model with unexpected output, this study calculated the urban carbon emission efficiency in order to study the regional differences and spatial spillover effects of urban carbon emission efficiency in the Yangtze River Delta. From 2001 to 2020, the highest average of urban carbon emission efficiency in the Yangtze River Delta was only 0.698, with a low overall level and a flat "Inverted-U" evolution trend. Pure technical efficiency became the main factor driving the change in carbon emission efficiency. The Gini coefficient was relatively high, fluctuating in different years and still dominated by growth. The regional differences in urban carbon emission efficiency increased. The contribution of inter group differences among the four provinces （city） was the main source of the differences in urban carbon emission efficiency. The Moran's I index was positive, which indicated that the positive autocorrelation of carbon emission efficiency was significant, and the spatial spillover effect was obvious. The population density, economic level, and technical level had significant effects. The direct, indirect, and total effects of industrial structure, road network density, and foreign capital intensity on carbon emission efficiency did not pass the significance test. Based on the perspective of factor input-output, the study accurately measured urban carbon emission efficiency in the Yangtze River Delta, identified the causes of the differences in urban carbon efficiency, and introduced the "spatial spillover effect" to analyze the mechanism of carbon emission efficiency. This study compensated for the lack of research on the urban carbon emission efficiency in the Yangtze River Delta and provided quantitative support and scientific inspiration for the low-carbon development.

To address the dilemma of China’s rural areas becoming increasingly homogeneous due to large-scale, campaign-style rural construction. This study proposes an innovative rural spatial pattern evaluation model that integrates geomancy theory with modern spatial analysis methods. Chawan village, Suzhou city, Jiangsu Province, China, is used as the study area, with the aim of better assessing and optimizing rural spatial patterns in China. The Analytic Hierarchy Process (AHP) is a method for ranking factors based on their relative importance, which is used to assign weights to indicators. Combined with the fuzzy comprehensive evaluation (FCE) method based on fuzzy set theory and ArcGIS weighted overlay analysis, it is used for evaluating rural spatial patterns. The results show that natural environmental indicators hold more weight than artificial ones. Among these, water body landscapes (0.111), water body buffer zones (0.103), and vegetation ecology (0.073) are the highest weighted indicators. The top three spatial pattern evaluation values are landscape environment (3.85), water bodies (3.52), and vegetation (3.51). The final result for the village is moderate, with an evaluation score of 3.385. This result suggests that the rural spatial pattern has a solid foundation for cultural continuity and significant potential for optimization, particularly in ecological and water body features. The AHP–GIS–FCE multi-method evaluation framework provides an effective tool for assessing and optimizing rural spatial patterns. This approach offers a systematic solution for rural development, promoting localized and diverse planning models, as opposed to the homogenized “one-size-fits-all” approach, and contributes to the protection of cultural heritage and sustainable development.

High-speed rail (HSR) serves as a low-carbon-dioxide mode of transportation, and its networked development aligns with the global trend toward green transportation transformation. While some studies have examined HSR's impact on carbon dioxide reduction, they have tended to overlook its spatial and temporal variations, and lack a comprehensive understanding of its varied mechanisms in different regions. This paper analyses how HSR network development in China affects transport and total carbon dioxide emissions through substitution and spillover effects. The study has the following main findings. (a) The development of China's HSR network over the past decade has reduced total carbon dioxide emissions by 0.232%, primarily through carbon dioxide savings from industrial restructuring. HSR has also reduced transport carbon dioxide emissions by 0.729%, mainly by substituting highways, conventional rail and civil aviation. (b) The impact of HSR network development on carbon dioxide emissions exhibits regional heterogeneity. The economically developed eastern region has experienced the most significant emission reduction effects, which mainly resulted from both substitution and spillover effects; whereas in central and western China, reductions in transport carbon dioxide emissions and total emissions were mainly driven by the spillover effect and substitution effect, respectively. This research provides scientific guidance for leveraging HSR network development to promote carbon dioxide reduction across different regions.

Urban sustainability has become the most important urban development issue globally. Facing the problem of spatial structure optimization during urbanization, how to effectively use public data access to promote urban polycentric development has become a new area of concern for urban planners and policy makers. To quantify how government open-data platforms shape polycentric urban spatial structure across Chinese cities, this study takes the launch of government data platforms as a quasi-natural experiment, constructs the multi-period differences-in-differences model, uses data of 271 Chinese prefectural-level cities from 2010 to 2021, and examines the impact and mechanism of public data access on urban spatial structure. We find that public data access promotes urban polycentric development, especially in large cities, those in urban agglomerations, and resource-abundant cities. The effect follows an inverted ‘N’ trend, which reflects the evolving role of PDA across different urban development stages, highlighting the need for adaptive policies to optimize its benefits. Mechanisms include information process radicalization and industrial structure upgrading, moderated positively by government intervention and regional competition. These insights can inform policies for optimizing urban spatial patterns and advancing sustainable urban development.

In recent years, the impact of urban form evolution on atmospheric pollution has become increasingly prominent. However, previous studies have rarely examined the combined influence of urban spatial forms and human perception on air pollution, while excluding emissions from natural sources. To address this gap, our study investigates the spatiotemporal dynamics of the relationship between anthropogenic PM2.5 pollution and urban form in China from 2000 to 2019. Using the Geographically and Temporally Weighted Regression (GTWR) model, we analyze the spatial heterogeneity of the impact of urban form on PM2.5 pollution. Our findings reveal that anthropogenic PM2.5 concentrations in China exhibited an initial increase, followed by a decline after 2013. In heavily polluted regions, such as the Beijing-Tianjin-Hebei area, annual average concentrations in most areas exceeded 60 μg/m3, with southern Hebei exceeding 100 μg/m3. The northern, southwestern, and Yangtze River Economic Belt regions had relatively lower concentrations, but still ranged between 20 and 60 μg/m3. Increasing urban compactness, reducing urban sprawl, and enhancing the complexity of urban form were found to contribute to lower anthropogenic PM2.5 levels in most cities. Additionally, climate conditions characterized by high precipitation and temperature, along with urban form patterns featuring high density, cohesion, and controlled expansion, were associated with reduced anthropogenic PM2.5 concentrations. In contrast, high humidity, dense populations, a thriving secondary sector, heavy traffic flow, and large, complex urban forms were likely to exacerbate anthropogenic PM2.5 pollution. These findings provide scientific insights for coordinated strategies to control atmospheric pollution in Chinese cities.

Quantifying the relationship between the extent of human impact and changes in ecological quality in the Yangtze River coastal area is essential for promoting sustainable development and ensuring the effective implementation of the Yangtze River Protection Policy. We incorporated aerosol optical depth (AOD) into the traditional remote sensing ecological index model and constructed an improved remote sensing ecological index (IRSEI). The spatio-temporal dynamics of human footprint (HFP) and ecological environmental quality within a 5 km buffer zone along the Yangtze River’s port, industrial and urban shorelines from 2001 to 2020 were examined. Based on the coupling coordination degree model and the four-quadrant model, we conducted a comparative and quantitative analysis of the spatial and temporal variations in the HFP and IRSEI. Finally, the causes of these spatio-temporal variations were discussed. The findings indicate that: (1) The HFP along the artificial shorelines of the Yangtze River increased steadily, while the IRSEI exhibited a gradual increase with fluctuations. (2) The HFP and IRSEI around urban shorelines were higher than those of the other two types of artificial shorelines. The level of coupling coordination between the HFP and IRSEI across the port, industrial, and urban shoreline zones demonstrated anl increasing trend, with growth rates of 8.5

Investigating nighttime tourism intensity in Thailand is crucial for the development of the local economy and related industries. Based on the satellite-observed nighttime light (NTL) data, points of interest data, and natural geographic condition data, this article explored the spatio-temporal distribution of the nighttime tourism intensity of 1594 tourist attractions within Thailand as well as their influencing factors by using the geographically weighted regression model. The results of this article demonstrate: First, regions with concentrated NTL are predominantly centered in the capital city, Bangkok, followed by Chiang Mai and Phuket, displaying a spatial distribution pattern that gradually diffuses from urban centers to the surrounding areas. Second, from 2013 to 2023, the level of nighttime tourism intensity in Thailand's tourist attractions has shown an upward trend with the average annual growth rate of 4.34% yr-1, except the negative impact of the pandemic on Thailand's tourism industry. Finally, it is found that higher levels of the catering and accommodation, shopping service, traffic service, leisure and entertainment were associated with higher levels of nighttime tourism intensity. These findings contribute to the sustainable development of Thailand's tourism industry and offer valuable insights into global tourism trends and patterns.

Employment center locations, the jobs-housing relationship, and commuting patterns are inextricably connected in a megacity that heavily relies on the urban transit system to shuttle commuters. Using a transit smartcard dataset, a machine learning method is employed as a preliminary filter to sift through commuter flows and isolate key data, then kernel density and topological analysis methods are implemented to delve into the primary research questions, providing a detailed look at how these patterns unfold. The results show that transit commuting behavior in Shanghai is a dispersal activity based on multi-level employment centers characterized as hierarchical, boundary-clear, and functionally oriented. Further analysis illustrates that the intensity of commuting linkages correlates with the employment center level, shaping a hybrid pattern that couples a core-periphery pattern with a spoke-hub pattern. The commuting network connections present corridor, neighborhood, capture, and replacement features, highlighting the importance of employment centers in shaping commuting patterns. From a daily flow perspective, these findings echo the central place theory and verify that the employment center distribution in Shanghai is also multi-layered and well-nested, forming the basis for commuting links. Policy implications are provided for polycentric megacities with progressively sophisticated urban transit systems.

Since the new century, the Association of Southeast Asian Nations (ASEAN) has managed to sustain stable economic growth, drawing global attention due to its robust performance. Nighttime light (NTL) observations have been recognized as a useful tool for monitoring the long-term socioeconomic development trends over large areas. Therefore, this study focused on analyzing the spatial and temporal distribution of NTL data in ASEAN countries from 2000 to 2022. The results reveal that NTL data are closely correlated with four key socioeconomic factors, including population, gross domestic product, industrial output, and service industry output. This demonstrates the viability of using NTL data as a proxy for assessing socioeconomic development levels in ASEAN countries. The study also observes significant variations in the spatial distribution of NTL within the ASEAN. Since 2000, there has been a continuous increase in NTL data across ASEAN countries, with a particularly rapid growth phase commencing post-2010. Notably, Laos, Cambodia, and Vietnam exhibited the fastest growth rates, with annual averages of 15.79%, 14.95%, and 14.81%, respectively. Furthermore, the relative changes in NTL values in ASEAN countries significantly surpassed those observed in South Korea, Japan, and the United States. The main reasons may be the implementation of open policies, optimized industrial structure, enhanced infrastructure development, and abundant labor resources in ASEAN countries. The insights from this study provide local governments and policymakers with a scientific basis to inform regional sustainable development planning in ASEAN countries, highlighting the importance of integrating NTL data analysis in socioeconomic development strategies.

By constructing a land ecological evaluation index system at the village scale and using models such as spatial correlation analysis, hotspot analysis, and obstacle factor diagnosis, the basic characteristics, spatial differentiation, and obstacle factors of land ecological status in Jiangsu Province were studied. This study sought to clarify the foundation, structure, function, and benefit characteristics of land ecosystems and optimize land management and policy regulation. The results showed that： ① The spatial distribution of land ecological status in Jiangsu Province was high in the north and low in the south, with multiple high-value areas radiating outward and decreasing, with low value centers radiating outward and increasing. The distribution area of the highest and lower values was relatively small, whereas the area of the middle value area was the largest. The higher values were mainly distributed in the suburbs and edge areas of each county. ② The spatial autocorrelation of land ecological status in Jiangsu Province was significant, with hot spots mainly concentrated in northern Jiangsu and cold spots concentrated in southern Jiangsu, as well as some areas of Taizhou and Nantong. The spatial distribution of cold and hot spots showed a complementary pattern with the level of regional development. The comprehensive index value of land ecology in developed areas was lower, whereas the index value in underdeveloped areas was higher. ③ The natural background conditions of Class Ⅰ land ecological zone in Jiangsu Province were superior, with good ecological construction and benefits and a high level of ecological status. The obstacle factors mainly included the proportion of water bodies and the average annual degradation rate of forest land. The Class Ⅱ land ecological zone was mostly located in the Huainan region and mainly composed of plain landforms. The Class Ⅲ land ecological zone had the largest area, located in the riverside areas of southern Jiangsu. The obstacle factors mainly included the average annual degradation rate of arable land and the proportion of soil pollution area. By controlling land ecological risks, the early warning level of ecological crisis could be improved.

The coastal region of China is a typical area characterized by a developed economy, yet it faces prominent resource and environmental issues, and it is of great significance to quantitatively assess the ecological effects resulting from rapid urbanization and industrialization. Based on the land use data from 1985 to 2020, and the InVEST modeling and relevant spatial data sources, the paper analyzed the spatial and temporal changes in land use cover and habitat quality in the coastal China over the past 30 years. The results show that: 1) land use cover in the coastal China has changed significantly during the study period, with the area of cultivated land continuing to decrease and construction land expanding; 2) the trend of habitat quality degradation in was obvious, with the area of low-value habitat quality continuing to increase. Spatially, they were mainly located in the three major urban agglomerations undergoing rapid industrialization and urbanization; 3) The average degradation of habitats increased significantly between 1990 and 2000 and 2010-2020. The rate of change in areas with different degradation levels from 1990 to 2000 was higher than in other periods. The low-value areas of habitat degradation are mainly located in hilly and mountainous regions. 4) The transfer of habitat grades was generally characterized by a shift from high grade to low grade. This trend of conversion was due to the largescale occupation of cultivated land by construction land and the long-term encroachment of ecological land by cultivated land. For future development, it is recommended to improve the land use regulation system based on the principles of sustainable development, with a particular focus on habitat protection. Additionally, efforts should be made to strengthen the development of ecological agriculture, carry out ecological protection and restoration, and improve the mechanisms for coordinating land and sea management.

Different from the market-led urbanization in western countries, China's urbanization process has the characteristics of being state-led, in which county-to-district conversion (CTDC) policy plays a key role in promoting urbanization. Our study uses the data of 279 cities as a simple to explore the effect of the state-led urbanization of CTDC on technological innovation. We find that CTDC significantly promote innovation, and this promoting effect is enhanced with the improvement of urban innovation ability. The mechanism test shows that financial expenditure on education and science, population agglomeration, information and communication technology industry are three channels for CTDC to boost technological innovation. We also find that this promotion effect is more obvious in eastern cities and the cities with higher administrative hierarchy, and is weakest in western cities, however, CTDC adjustment in northeastern cities significantly inhibited technological innovation. Further research shows that when the distance between merged county and city administrative center within 20 km, the effect is negative, after the distance is more than 20 km, with the increase of distance, the promoting effect of CTDC increases.