With the rapid development of urbanization and industrialization in China, the expansion of construction land and irrational utilization of cultivated land have led to issues such as cultivated land marginalization, extensive use, non-grain conversion, and non-agriculturalization. These issues are a major threat to sustainable agricultural development, but existing research suffers from limitations including failure to assess the multifunctionality of cultivated land (MCL) from the perspective of sustainable agricultural development. This study constructed an agricultural production function (APF)-social security function (SSF)-ecological maintenance function (EMF)-landscape aesthetic function (LAF) classification system. Using this comprehensive evaluation model, the MCL values for typical provinces in southwestern mountainous areas of China (Guizhou, Sichuan, and Yunnan) were calculated in detail, and their spatiotemporal evolutionary characteristics were explored. Concurrently, the Spearman rank correlation coefficient, geographically weighted regression (GWR) and redundancy model were used to deeply explore the relationships among cultivated land functions and their influencing factors. The results showed three important points. (1) Over the past two decades, the comprehensive values and four sub-functional values of cultivated land in southwestern mountainous areas have shown increasing trends in the order of SSF > EMF > LAF > APF. The values and rates of change of each sub-functional value show obvious spatial variation. However, the spatial gap in cultivated land functions has adverse effects on sustainable agricultural development. (2) There are clear correlations between each pair of the four major functions of cultivated land during the study period, and the number of results reaching significance among the six correlations between the four main cultivated land functions increased significantly from 2000 to 2020. Simultaneously, there are noticeable spatiotemporal differences in the trade-offs and synergies among the MCLs. (3) The development of MCL is most significantly influenced by socioeconomic factors such as the per capita net income of rural residents. Therefore, formulating reasonable land protection policies is imperative for promoting the sustainable development of agriculture. The results of this study can provide guidance for the rational layout and coordinated development of MCL space, for promoting sustainable agricultural development and ensuring food security.

Rapid population growth, industrialization, and urbanization are driving an increasing demand for land in various industries, which is reducing the available cultivated land resources. This study used the Land-use Dynamic Degree Model and Geo-Detector to explore the spatial and temporal variations in cultivated land resources and the driving factors of cultivated land changes in Anhui Province from 2009 to 2018, using data on cultivated land area and socio-economic indicators. The findings showed reductions in both the total cultivated land area and the per capita cultivated land area in Anhui Province from 2009 to 2018. Most prefecture-level cities experienced reductions in their cultivated land area, with only a few showing increases. All prefecture-level cities except Wuhu City showed decreasing trends in per capita cultivated land area. The changes in the cultivated land area in Anhui Province have been influenced by various socio-economic factors. The impacts of interaction factors were more significant than those of any single factor during the study period. Among these interaction factors, the regional economic structure, level of agricultural technology, state of agricultural production, status of rural development, condition of the rural labor force, and governmental investment and regulation were shown to be crucial and prioritized. These factors significantly contributed to the variations in cultivated land area within Anhui Province. Therefore, balancing the relationship between economic growth and cultivated land preservation, especially strictly implementing cultivated land protection policies, is significantly beneficial for achieving sustainable socio-economic development.

Understanding and managing the changing landscape of our planet requires analyzing land use and land cover (LULC) transitions. This study combines remote sensing data and GIS analysis to uncover the intricate patterns and drivers behind these transitions. By integrating GIS analysis, we identify factors such as urbanization, agricultural expansion, deforestation, and natural resource management contributing to these changes. Accurate data preprocessing and calibration are emphasized to reduce errors and uncertainties in LULC maps. The study covers the period from 2017 to 2022, utilizing digitized LULC maps created with GIS tools and satellite data interpretation, specifically Sentinel-2 images. The landscape was classified into seven land cover types: agricultural land, built-up areas, barren or degraded land, flooded vegetation areas, forests, vegetation or shrub-covered areas, and waterbodies. Findings revealed a decrease of 1063.73 km² in barren land between 2017 and 2022. Agricultural land expanded by 228.93 km², forest land increased by 632.90 km², and waterbodies grew by 33.05 km². These changes suggest a conversion of areas likely influenced by the high intensity of rainfall between 2017 and 2022, leading to notable ecological consequences such as reduced soil erosion and improved biodiversity protection. The study's results have significant implications for land management, environmental protection, and sustainable development. The extensive analysis of spatial and temporal data equips policymakers, urban planners, and researchers with crucial knowledge to make well-informed decisions. This research provides a solid basis for monitoring and managing LULC transitions, offering valuable methodologies and insights to promote a resilient and harmonious coexistence between human activities and the environment.

The efficient use of urban land is one of the key factors for high-quality urban development, especially in large cities that lack land resources. By constructing an analysis framework of the land use benefit system and the transfer matrix of land use type, this study identified the evolutionary law governing the land use benefit system and its dynamic coupling coordination relationship with the rapidly expanding city by taking Zhengzhou, a national central city in China, as a case study. The results show that the urban land use (ULU) benefit system of Zhengzhou gradually shifted from the eco-environmental benefit type (1998-2005) to the socio-economic benefit type (2006-2019), with the coupling degree presenting a typical inverted U-shaped evolutionary process. In the same period, the urban area of Zhengzhou expanded by about 461 square kilometers. A further transfer matrix analysis shows that the main source of expansion has been the conversion of arable land, grassland, woodland and water areas to construction land. Therefore, the local government should implement a differentiated land use strategy according to the characteristics of the land use benefit system and the evolution of the coupling and coordination relationship, exploit the opportunity of urban boundary delimitation, and promote urban transformation and upgrading as well as eco-city construction.

Exploring the driving mechanism and factors influencing farmers’ decisions regarding farmland abandonment is fundamental for the targeted control of land abandonment and the adjustment of land management policies, especially for ecologically fragile areas. This study used Guyuan, a typical hilly and gully region, as a study area and employed the framework of a participatory assessment workshop, key informant interviews, and questionnaires to obtain data from stakeholders at multiple levels. The descriptive statistical analyses were carried out from social, economic, and natural aspects to explore the factors affecting farmers’ decisions to abandon farmland in the hilly and gully regions. By combining multiple levels of stakeholders and multiple sources of data, the multi-spatial-temporal analysis effectively allowed us to conduct a comprehensive and thorough exploration of the potential factors affecting farmers' land abandonment decisions using this framework. The results revealed important aspects of the main social, economic and environmental factors. (1) Among the social factors, the influence of neighbours is the most influential, owing to the herd mentality of farmers and the negative impact of abandoned farmland on surrounding farmland. Additional factors are declining employment opportunities and grain subsidies. (2) The main economic factors affecting farmers’ abandonment of farming are land productivity, farming costs, and grain price. (3) The main environmental factors include road accessibility, slope and terrain relief, and farmers living in hilly and mountainous areas are more sensitive. This research provides comprehensive knowledge about the trade-offs associated with land abandonment and local stakeholders in the Loess hilly and gully region of China, a reference for finding possible pathways to halt the negative impacts, and a solid foundation for the statistical and spatial model building to simulate the abandonment scale, spatial-temporal evolutionary process, and the risk of abandonment for political reference.

With the implementation of the national policy of “High-quality development of the Yellow River Basin”, urban growth on the Loess Plateau is expected in the future. However, studies involving spatiotemporal simulations of urban growth at the regional scale are limited. We proposed an integrated modeling method, using the SLEUTH model and indicator-based spatial mapping, to quantify and map urban growth based on a dataset of urban cover from 1995 to 2050 with 1 km resolution. The results showed that the rates and spatial patterns of urban growth varied across multi-level cities, and were affected by urban development policies, the physical environment and administrative functions. The overall urban area in 2050 will be approximately 8.12 times that in 1995 among the 15 prefectural and capital cities, and the overall urban growth rates are 5.97% and 3.2% for the periods of 1995-2015 and 2015-2050, respectively. Leapfrogging was the major urban growth pattern during the period of 1995?2015, while edge-growth will become the dominant urbanization pattern by 2030s, and the infilling growth pattern shows a minimal contribution to the urban growth in most of the cities during the study period, except for the plain-limited cities (e.g., Lanzhou and Xining). The spatiotemporal changes in the multi-level urban growth based on high resolution maps can provide essential information for promoting regional urban planning and sustainable city management on the Loess Plateau.

The protection of cultivated land resources is critically important for maintaining food production capacity, economic development, and social stability in China. This study analyzed the spatiotemporal characteristics of cultivated land variation in Jilin Province from 1980 to 2015 by taking Jilin Province as the study area, employing the remote sensing images captured in 1980, 1990, 1995, 2000, 2005, 2010, and 2015 and the statistical data from 1980 to 2015 as the basic data, and using a transfer matrix and the cultivated land pressure index model. The results revealed that on the temporal scale from 1980 to 2015, the area of cultivated land increased from 701.88×10⁴ ha to 762.82×10⁴ ha, the area of cultivated land per capita increased from 0.1524 ha to 0.1707 ha, and the cultivated land pressure index rose from 0.7922 to 0.7953. On the spatial scale, the cultivated land pressure in Jilin Province was mainly concentrated in the southern section in both 1980 and 1990, the southern and eastern sections in 1995, the southwestern and eastern sections in 2000, the southern and southeastern sections in 2005, and the southern, southeastern, and central sections in both 2010 and 2015. The change in the direction of the cultivated land pressure force in Jilin Province during the study period was mainly from northwest to southeast.

The purpose of this paper is to explore the trade-offs and synergies of multifunctional cultivated land (MCL) at multiple scales. The study area is Wuhan Metropolitan Area, China. The entropy method and the method of Spearman's rank correlation were employed for the analysis of combined land use/cover data, administrative division data, population data and statistical yearbook data, from the multi-scale perspectives of cities, counties and townships. The results showed that: (1) The multi-functionality of cultivated land had obvious spatial differences and its overall spatial patterns were relatively robust, which did not change very much at the single scale. (2) At each single scale, the MCL's trade-offs and synergies had spatial heterogeneity. (3) Scale effects existed in the MCL's trade-offs and synergies. From the prefecture-level city scale, to the county scale, and to the township scale, the MCL's trade-offs were changed to synergies, and some synergic relationships were enhanced. This article contributes to the literature by deepening the multiscale analysis of trade-offs and synergies of multifunctional cultivated land. The conclusions might provide a basis for helping policy-makers to implement protection measures for the multi-functionality of cultivated land at the right spatial scale, and to promote the higher-level synergies of multifunctional cultivated land to realize its sustainable use.

Delimiting ecological space scientifically and making reasonable predictions of the spatial-temporal trend of changes in the dominant ecosystem service functions (ESFs) are the basis of constructing an ecological protection pattern of territorial space, which has important theoretical significance and application value. At present, most research on the identification, functional partitioning and pattern reconstruction of ecological space refers to the current ESFs and their structural information, which ignores the spatial-temporal dynamic nature of the comprehensive and dominant ESFs, and does not seriously consider the change simulation in the dominant ESFs of the future ecological space. This affects the rationality of constructing an ecological space protection pattern to some extent. In this study, we propose an ecological space delimitation method based on the dynamic change characteristics of the ESFs, realize the identification of the ecological space range in Qionglai City and solve the problem of ignoring the spatial-temporal changes of ESFs in current research. On this basis, we also apply the Markov-CA model to integrate the spatial-temporal change characteristics of the dominant ESFs, successfully realize the simulation of the spatial-temporal changes in the dominant ESFs in Qionglai City's ecological space in 2025, find a suitable method for simulating ecological spatial-temporal changes and also provide a basis for constructing a reasonable ecological space protection pattern. This study finds that the comprehensive quantity of ESF and its annual rate of change in Qionglai City show obvious dynamics, which confirms the necessity of considering the dynamic characteristics of ESFs when identifying ecological space. The areas of ecological space in Qionglai city represent 98307 ha by using the ecological space identification method proposed in this study, which is consistent with the ecological spatial distribution in the local ecological civilization construction plan. This confirms the reliability of the ecological space identification method based on the dynamic characteristics of the ESFs. The results also show that the dominant ESFs in Qionglai City represented strong non-stationary characteristics during 2003-2019, which showed that we should fully consider the influence of the dynamics in the dominant ESFs on the future ESF pattern during the process of constructing the ecological spatial protection pattern. The Markov-CA model realized the simulation of spatial-temporal changes in the dominant ESFs with a high precision Kappa coefficient of above 0.95, which illustrated the feasibility of using this model to simulate the future dominant ESF spatial pattern. The simulation results showed that the dominant ESFs in Qionglai will still undergo mutual conversions during 2019-2025 due to the effect of the their non-stationary nature. The ecological space will still maintain the three dominant ESFs of primary product production, climate regulation and hydrological regulation in 2025, but their areas will change to 32793 ha, 52490 ha and 13024 ha, respectively. This study can serve as a scientific reference for the delimitation of the ecological conservation redline, ecological function regionalization and the construction of an ecological spatial protection pattern.