Analyses of the scale and structural characteristics of construction land serve as the basis for optimizing the spatial pattern of territorial planning. Existing studies have focused mainly on the horizontal expansion of urban construction land. Therefore, based on the Google Earth Engine (GEE) platform, in this paper, we use high-precision land-use cover data, DEM data and socioeconomic data to construct the standard dominant comparative advantage index (NRCA) using the geological mapping analysis method and we systematically analyze the horizontal scale, slope spectrum characteristics, gradient effects and driving factors of construction land in the Lanzhou–Xining urban agglomeration (LXUA) from 1990 to 2020 at four scales: the urban agglomeration, provincial area, typical city and county (district) scales. The results of the study show that urban construction land, rural settlement land and other construction land in the LXUA show “linear”, inverted-“U” and “J” growth patterns, respectively. Three types of construction land show different spatial transfer characteristics. The scale and extent of climbing of urban construction land in the LXUA is gradually decreasing over time, and the number of climbing rural settlement lands in 2000–2010 was as high as 34 counties (districts), while the number of counties (districts) with strong climbing degrees of other construction land rose to 12 from 2010 to 2020. The relative hotspots of the slope-climbing phenomenon of the three types of construction land have gradually expanded spatially, with Lanzhou city and Xining city as the center, and the overall spatial characteristics are “more in the east and less in the west”. The population and GDP are the main factors influencing the slope-climbing phenomenon of urban construction land, while rural settlements are influenced mainly by natural conditions, and accessibility is the key factor affecting other construction land.

City health examination and evaluation of territorial spatial planning is a new policy tool in China. However, research on city health examination and evaluation of territorial spatial planning is still in the exploratory stage in China. Guided by sustainable cities and communities (SDG11), a reasonable city health examination and evaluation index system for Xining City in Qinghai Province is constructed in this paper. The improved technique for order preference by similarity to ideal solution (TOPSIS) was used to quantify the evaluation results, and the city health index was visualized using the city health examination signals and warning panel. The results show that the city health index of Xining City continuously rose from 35.76 in 2018 to 69.76 in 2020. However, it is still necessary to address the shortcomings in innovation, coordination, openness and sharing and to improve the level of city space governance in a holistic way. This study is an exploration of the methodology used in city health examination and the evaluation of territorial spatial planning in China, which can provide a foundation for the sustainable development of Xining City and also provide a case reference for other cities seeking to carry out city health examinations and evaluations of territorial spatial planning in China.

Exploring the spatiotemporal dynamics, spatial mismatch, and complex influencing mechanism of grain production and cropland productivity in the black soil region of northeast China (BSRNC) is essential for the synergistic protection and utilization of black soil cropland and sustainable grain production. The BSRNC has realized cropland expansion and grain production increases in the past decades. This implied a substantial investment has been made in the region’s agriculture. However, at present, knowledge on the spatial mismatch and influencing factors of grain production and cropland productivity is still unclear. This study analyzed the spatial–temporal mismatch characteristics of grain production and cropland net primary productivity (CNPP) using the gravity center model, spatial autocorrelation analysis, and spatial mismatch index (SMI), and identified the spatial heterogeneity and prediction–response relationships of influencing factors based on a geographically and temporally weighted regression (GTWR) model and boosted regression tree (BRT) machine learning algorithm. The findings indicated that grain production and CNPP have been increasing, but the overall spatial pattern of cold hotspots has not changed obviously in the BSRNC from 2000 to 2020. The SMI has shown a decreasing trend, indicating that the synergistic development of grain production and CNPP has been obvious, which plays an important role in sustainable food supply capacity. Agricultural production and the natural environment have always been critical factors influencing the spatial mismatch. Specifically, the marginal impact of fertilizer application has undergone a shift. This study may provide new clues for the formulation of regional strategies for sustainable food supply and black soil cropland system protection.

The future of the ecologically fragile areas on the Qinghai-Tibet Plateau (QTP) is a matter of concern. With the implementation of the Western Development Strategy, the Lanzhou-Xining Urban Agglomeration (LXUA) has encountered conflicts and compromises between urban expansion, ecological protection, and farmland protection policies in the rapid development of the past 2 decades. These deeply affect the land use layout, making the ecological sustainable development of the ecologically fragile areas of the QTP a complex and urgent issue. Exploring the impact of different policy-led land use patterns on regional ecosystem services is of great significance for the sustainable development of ecologically fragile areas and the formulation of relevant policies. Following the logical main line of “history-present-future”, the Patch-level Land Use Simulation (PLUS) model, which explores potential factors of historical land use, and the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model were used to construct three future scenarios for the modernization stage in 2031 dominated by different land use policies in this study. These scenarios include the Business-as-Usual Scenario (BS), the Cropland Protection Scenario (CP), and the Ecological Protection Scenario (EP). The study analyzed and predicted land use changes in the LXUA from 2001 to 2031 and assessed carbon storage, habitat quality at different time points, and water yield in 2021. The results indicated that land use changes from 2001 to 2021 reflect the impacts and conflicts among the Western Development Strategy, ecological protection policies, and cropland preservation policies. In 2031, construction land continues to increase under all three scenarios, expanding northwards around Lanzhou, consistent with the actual “northward expansion” trend of Lanzhou City. Changes in other land uses are in line with the directions guided by land use policy. By 2031, carbon storage and habitat quality decline under all scenarios, with the highest values observed in the EP scenario, the lowest carbon storage in the BS scenario, and the lowest habitat quality in the CP scenario. Regarding water yield, the LXUA primarily relies on alpine snowmelt, with construction land overlapping high evapotranspiration areas. Based on the assessment of ecosystem services, urban expansion, delineation of ecological red lines, and improvement of cropland quality in the LXUA were proposed. These findings and recommendations can provide a scientific basis for policy makers and planning managers in the future.

Analyses of the scale and structural characteristics of construction lands serve as the basis for delineating urban development boundaries and optimizing the spatial pattern of territorial planning. Existing studies have focused mainly on the horizontal expansion of urban construction lands, while few comprehensive studies have explored the slope gradient effects of urban construction land, rural settlement land or other construction land in the horizontal-expansion dimension or vertical slope-spectrum dimension. Therefore, based on the Google Earth Engine (GEE) platform, in this paper, we use high-precision land use cover data, DEM data and socioeconomic data to construct the standard dominant comparative advantage index (NRCA) using the geological mapping analysis method and systematically analyze the horizontal scale, slope spectrum characteristics, gradient effects and driving factors of construction lands in the Lanzhou-Xining urban agglomeration (LXUA) from 1990 to 2020 at four scales: the urban agglomeration, provincial area, typical city and county (district) scales. The results of the study show that urban construction land, rural settlement land and other construction land in the LXUA show "linear", inverted "U" and "J" growth patterns, respectively. The areas of rural settlements in 9 counties (districts) are decreasing, and the number of counties (districts) with decreasing areas is increasing, while the areas of other construction land in most counties (districts) are increasing. The center of urban construction gravity continues to shift northwestward, and the standard deviation ellipse is becoming flatter; the center of gravity of rural settlement lands continues to shift southeastward. The center-of-gravity distribution and standard deviation elliptical characteristics of construction land at other scales also vary to different degrees. The scale and extent of the increase in urban construction land in the LXUA is gradually decreasing over time, and the number of rural settlement lands in 2000–2010 was as high as 34 counties (districts), while the number of counties (districts) with strong degrees of other increased construction land rose to 12 from 2010 to 2020. The relative hotspots of the three types of increasing construction land have gradually expanded spatially, with Lanzhou city and Xining city as the center, and the overall spatial characteristics are “more in the east and less in the west”. The population and GDP are the main factors influencing urban construction land increases, while rural settlements are influenced mainly by natural conditions, and accessibility is the key factor affecting other construction land.

Against the backdrop of dietary structure evolution and the “big food concept” strategy, there has been a shift from the traditional grain-centric perspective toward a diversified supply system. Taking Hubei Province—a major grain-producing region in China—as a case study, this research establishes a multi-criteria evaluation system and conducts analysis using statistical yearbooks and land survey data. By integrating natural conditions, economic benefits, and production capacity, the suitability of cultivated land for growing grain crops, cash crops, and forage crops is assessed. Concurrently, landscape pattern indices were applied to quantify the degree of farmland fragmentation. Employing a self-organizing mapping (SOM) neural network model, we synthesized suitability and fragmentation data to delineate differentiated farmland conservation zones. The results revealed significant spatial heterogeneity in crop suitability and fragmentation levels. High-suitability zones for grain crops were concentrated in the Jianghan Plain, while forage crops exhibited higher suitability in northeastern and southeastern Hubei. Farmland fragmentation showed a spatial pattern of lower levels in central Jianghan Plain, gradually increasing toward surrounding hilly and mountainous areas. SOM clustering effectively partitioned farmland into six functional zones: multifunctional agricultural zones, mixed farming zones, grain crop zones, cash crop zones, forage crop zones, and production improvement zones. This multi-source geographic and statistical data-driven zoning framework provides scientific basis for targeted policy interventions. It enables the quantitative management, quality enhancement, and spatial optimization of farmland resources, thereby operationalizing the big food concept to strengthen regional food security.