In order to solve the problem of habitat fragmentation in the Beijing–Tianjin–Hebei region and realize the sustainable use of land, based on remote sensing data from 2010 to 2020, this paper uses GIS and the CA–Markov model to predict the land use structure in 2030, and uses the InVEST model to quantitatively analyze the changes in habitat quality in the Beijing–Tianjin–Hebei region from 2010 to 2030. The results indicate that (1) from 2010 to 2020, the area of construction land increased significantly, mainly from cultivated land, woodland and grassland; the proportion of cultivated land decreased by 7.2%. It was predicted that by 2030, the area of construction land will continue to expand, accounting for 19.6%. According to the results of land use dynamic degree, the conversion speed between land types in 2010–2015 was higher than that in 2015–2020. (2) The average habitat quality indexes of the study area in 2010, 2015, 2020 and 2030 were 0.57, 0.56, 0.55 and 0.52, respectively, and the habitat quality level was moderate and continued to decline. The habitat center of gravity moved in the north, from Fengning Manchu Autonomous County to the junction of Fengning Manchu Autonomous County and Longhua County, and then moved to the Mentougou District of Beijing. Therefore, in order to amendthe continuous decline in habitat quality, scientific measures should be taken according to local conditions to promote the improvement of habitat quality and the rational use of land.

The eco-efficiency of cultivated land use (ECLU) is an important indicator for ecological civilization construction in China. Exploring the spatiotemporal dynamic evolution of the ECLU is helpful for the sustainable use of arable land, ensuring food security and ecological security. However, previous studies have mostly focused on the use of a slacks-based measure (SBM) model for ECLU measurement, ignoring the more accurate epsilon-based measure (EBM) model. Therefore, in this study, first, we explored the conceptual framework of the ECLU, and then, based on 2005–2020 panel data covering the counties in the region around Beijing and Tianjin, we investigated the spatial and temporal evolution of the ECLU by using the Super-EBM model, kernel density estimation method, and spatial Markov chain model. The results show the following: 1) From 2005 to 2020, the ECLU in the region around Beijing and Tianjin displayed an increasing state, but the average value was only 0.55. 2) The temporal evolution of the ECLU has gradually polarized, and the internal gap has widened, but it tends to stabilize. 3) The ECLU in the region around Beijing and Tianjin was more inclined to remain the same, and there was a “club convergence” phenomenon, which was meaningfully affected by the background of neighboring areas. In this article, we emphasize the significance of the super‐efficient EBM model in measuring the ecological efficiency of arable land use, and discuss the spatiotemporal evolution of the ecological efficiency of arable land use at a deeper level. In light of local conditions, the government should reasonably formulate a path to optimize the ECLU, strengthen the linkage with surrounding cities, and bring into play the positive spillover effect.

Introduction: The objective of this study is to investigate the impact of land use changes on the coupling coordination of the regional water-food-carbon system in Hebei Province. Moreover, the findings aim to offer insights for achieving comprehensive and coordinated development of regional resources.Methods: By constructing an evaluation index system of the coupled coordinated development of the water-food-carbon system, using the coupled coordination model to study the coupled coordination of the water-food-carbon (WFC) system in Hebei Province from 2010 to 2020, and applying the Pearson correlation coefficient and ArcGIS to analyze the impacts of land-use changes on the degree of coupled coordination.Results: The results show that: (1) The most notable characteristics of land type changes include a decrease in cropland and an increase in construction land, primarily driven by the conversion of cropland to construction sites. The total area converted amounts to 8207.20 km². (2) The degree of coupled coordination of the water-food-carbon system in the study area as a whole shows an upward and then downward trend, and shows a spatial distribution pattern of “high in the north-east and low in the south-west”; (3) In Hebei Province, the degree of coupling coordination within the water-food-carbon system exhibits a stable positive correlation with forest land, grassland, and water area. Additionally, the transfer of forest land and grassland are significant factors influencing the delineation of cold and hot spots within the region.Discussion: Therefore, in addressing the coordinated development of the water-food-carbon system, it is essential to consider the influence of land. Resources should be allocated judiciously based on regional advantages to promote sustainable development effectively.

Focusing on Hebei Province in China, the work investigated the impact of implicit land use transition (ILUT) on land use carbon emissions (LUCEs) for dual carbon goals. A county-level evaluation system and a measurement model were constructed to explore ILUT and carbon emissions’ spatiotemporal progression, respectively. The optimal spatial econometric model was selected by employing different testing methods to elucidate how ILUT affected carbon emissions. LUCEs increased from 49.7964 million tons (2000) to 107.401 million tons (2015) and dropped to 92.2173 million tons by 2020. The overall exhibited an inverted V-shape. Values were generally higher in the southeast and lower in the northwest. ILUT index across counties increased from 2000 to 2020, with polarization of implicit indices intensified. Spatial distribution showed that the southeastern area exhibited notably higher values compared to the northwestern parts. Significant positive spatial correlation existed between ILUT and carbon emissions within the county, while a significant negative spatial correlation was observed with carbon emissions in neighboring counties. These findings provide scientific support for formulating differentiated land use policies and optimizing carbon emission control strategies in Hebei Province, holding significant practical value for regional dual carbon targets.

Exploring the interactions and coupling effects in the Population–Land–Industry–Facility (PLIF) system can help maximize resource allocation and promote the synergistic development of systems. This study constructs an index system for the PLIF system in Hebei Province, employing coupling coordination degree and spatial autocorrelation methods to investigate the spatio-temporal evolution of the system’s coordination. Furthermore, grey relational analysis is employed to examine the key factors influencing the coordination degree of the system. The results show the following: (1) The development levels of each subsystem and the overall development level of the PLIF system in Hebei Province have generally increased, but the overall level remains relatively low. (2) The PLIF system in Hebei Province exhibits a pattern of “low in the north and high in the south, high in the east and low in the west”, with most counties in a barely coordinated state and a generally high degree of coupling. (3) The main factors affecting the coordinated development of the PLIF system include population density, the proportion of the tertiary industry, and the degree of non-agriculturalization of rural labor force. The research results of this paper provide a reference for promoting the coordinated development of population, land, industry, and facilities in Hebei Province and facilitating the sustainable development of the region.