China is vigorously promoting the strategy of rural revitalization, encouraging farmers to revitalize their idle houses and developing rural tourism. In rural China, kinship networks are essential in farmers’ willingness and decision–making tools. It is significant to explore the influence of kinship networks on farmers’ willingness to revitalize idle houses. This study constructs a research framework of “kinship networks–revitalization willingness–revitalization action”. It describes farmers’ kinship networks from five aspects: kinship networks structure, kinship networks relationship, kinship networks cognition, kinship networks members’ sense of belonging, and their social participation enthusiasm. Taking Bishan Village, a typical rural tourism–type ancient village, as an example, this study surveyed 197 farmers to demonstrate the influence of kinship networks on farmers willingness to revitalize idle houses. This paper uses a multiple regression model to empirically study the influence of kinship networks on farmers’ willingness to revitalize idle houses. The results show that: (1) In addition to the kinship networks structure having no significant positive impact on farmers’ willingness to revitalize idle houses, kinship networks relationship, kinship networks cognition, kinship networks members’ sense of belonging, and kinship networks members’ social participation enthusiasm all have positive effects on farmers’ willingness. (2) Considering the critical influence of kinship networks on farmers’ willingness to revitalize idle houses, the government should use the structure of kinship networks to formulate relevant policies to guide farmers to increase their willingness to revitalize their idle houses.

With the expansion of the scale of industrial land, China’s industrial economy continues to grow at a high speed, but the long-term homogeneous land supply policy has led to low land use efficiency. Exploring differentiated industrial land supply policy (DILSP) innovations can effectively address this issue. However, due to the limited practical cases, there are few studies on the policy innovations of industrial land supply. Based on the life cycle management (LCM) of industrial land (LCMIL), this study uses the policy analysis method to reform and innovate industrial land supply policy to solve the disadvantages of the current industrial land supply policy and proposes the DILSP as its basis. The research shows the following: (1) there are many problems in China’s current land supply policy, but policy innovation in some economically developed cities has achieved positive results, indicating that an effective institutional supply is the best way to solve these problems; (2) the process of industrial land utilization has obvious cyclical characteristics, and a complete process and differentiated supply policy framework based on “differentiated access evaluation, differentiated supply method, differentiated supply period, differentiated supply price, differentiated post-supply supervision” has a certain rationality and feasibility. This study provides an innovative solution to the shortcomings of China’s existing industrial land supply policy, and the idea of applying LCM theory to government policy-making also has a certain reference significance.

The requisition–compensation balance of farmland (RCBF) policy proposes that all farmland requisitioned for development must be compensated with new farmland, of which the continued implementation in economically developed counties in China faces great challenges. The extent to which a balance of potential crop production can be achieved merely through farmland consolidation has important theoretical and practical significance. This study proposes measurement procedures to investigate this degree and takes seven counties in southeastern coastal China as examples on which to conduct an empirical study. The results show the following: (1) there is a significant negative correlation between GDP and the index of the balance of potential crop production of each county, that is, the more developed the county, the lower the potential to achieve the balance; (2) with an increase in elevation, the possibility of increasing potential crop production shows an inverted U-shaped curve, with the maximum values occurring at elevations between 50 and 500 m and more attention should be paid to farmland with an elevation of between 50 m and 500 m when implementing farmland consolidation projects; (3) although it is difficult for economically developed counties to strike a balance of potential crop production merely through farmland consolidation, the potential of which to compensate for the loss of potential crop production from requisition is great, reaching more than 40%, which plays an important role in realizing the requisition–compensation balance of potential crop production; and (4) the potential of farmland consolidation to compensate for the loss of potential crop production and the difference of which between counties should be paid adequate attention when implementing RCBF policy adjustment. Therefore, the proposed approach illustrated in this study clearly reveals the relationship between the loss of potential crop production from requisition and the compensation of potential crop production by farmland consolidation, which has important implications for the adjustment of the RCBF policy in China.

Cultivated land fragmentation (CLF) has evolved from a physical landscape phenomenon into a systemic constraint on agricultural sustainability, especially in rapidly urbanizing regions such as the Yangtze River Delta (YRD). Existing studies are limited by static “snapshot” comparisons that obscure continuous trajectories and by linear models that fail to capture nonlinear interactions and threshold effects. This study integrates the Space–Time Cube (STC) model with an interpretable machine learning framework (Extreme Gradient Boosting–Shapley Additive Explanations, XGBoost–SHAP) to explore the spatiotemporal dynamics and driving mechanisms of CLF in the YRD (1990–2020) at a 1 km² resolution. The STC identifies a distinct north–south gradient, with persistent hotspots in low-lying plains and intensifying fragmentation at peri-urban interfaces. SHAP interpretation suggests a “Base–Stabilizer–Amplifier” structure in the modeled relationships: hydrological accessibility and soil fertility form the dominant background linked to higher CLF, whereas topography correlates with lower CLF, and socioeconomic variables exhibit nonlinear, threshold-like increases in fragmentation beyond higher development levels. Overall, CLF reflects coupled natural–anthropogenic interactions with pronounced nonlinear responses. This mechanism-oriented framework provides actionable guidance for adaptive farmland governance. It also offers a transferable methodology for analyzing land system changes in other deltaic agricultural regions worldwide.

Fine-scale evidence remains scarce regarding where ecological quality has improved or deteriorated in the Yangtze River Delta (YRD) and which landscape conditions are associated with these trajectories. We developed a 1 km² hexagon-based diagnostic framework integrating the Remote Sensing Ecological Index (RSEI), Sen–Mann–Kendall trend analysis, Local Moran’s I clustering, recurrence-based ecological stress typology, and XGBoost–SHAP interpretation for 2000–2025. Annual RSEI was standardized by year to capture relative trajectories of ecological quality rather than absolute change under a fixed loading system. The regional mean RSEI fluctuated markedly and declined only slightly, from 0.639 in 2000 to 0.632 in 2025, suggesting that long-term ecological change was nonlinear. At the hexagon scale, 64.77% of valid units showed positive RSEI trends, with significant improvement covering 15.08% of units and significant degradation covering 5.47%. Local Moran’s I identified distinct High–High and Low–Low clusters; persistent low-quality clusters and stable high-quality areas accounted for 10.0% and 7.8% of valid hexagons, respectively. XGBoost–SHAP results indicated statistical associations between RSEI trends and soil moisture, elevation, impervious surface change, and nighttime light change, rather than direct causal effects. This framework provides a spatially explicit basis for identifying priority monitoring areas, ecological stress zones, and differentiated land management units across rapidly urbanizing megaregions.

Rural homestays, core land-use carriers driving rural revitalization in mountainous tourist regions, exhibit pronounced price-tiered spatial disparities, yet their tier-specific driving mechanisms remain underexplored—particularly the cross-tier gradient from resource dependence to ecological amenity in locational logic. Taking the Mountainous Tourism Zone of Southern Anhui as the study area, we investigate the spatial patterns and driving factors of rural homestays across price tiers. Based on a dataset of 5724 rural homestay entities, we employ Kernel Density Estimation, Hotspot Analysis, Standard Deviational Ellipse, and the Geodetector model to characterize spatial agglomeration and quantify tier-specific driving factors. Results reveal pronounced tier-specific heterogeneity: economy-tier homestays are diffusely distributed, comfort-tier ones agglomerate in resource-rich villages, and premium-tier homestays form isolated clusters around high-quality landscapes—mirroring a tier-differentiated pattern from resource dependence to ecological amenity. Factor detection confirms industrial foundation as the primary overall determinant, followed by economic development, tourism resources, natural environment, and traffic conditions. However, tier-disaggregated analysis uncovers a cross-tier gradient in locational logic: resource dependence dominates economy-tier siting, multi-factor balance characterizes comfort-tier decisions, and preference for ecological amenities defines premium-tier locations. Compared with plain areas, the natural environment exerts stronger constraints on mountainous homestay layout, reflecting distinctive human–land interactions in mountain land-use systems. By empirically documenting the cross-tier gradient from resource dependence to ecological amenity, this study provides scientific guidance for tier-specific spatial planning, rational land utilization, and sustainable homestay development in mountainous tourist destinations.