Land use and land cover (LULC) models are essential for analyzing LULC change and predicting land use requirements and are valuable for guiding reasonable land use planning and management. However, each LULC model has its own advantages and constraints. In this paper, we explore the characteristics of LULC change and simulate future land use demand by combining a CLUE-S model with a Markov model to deal with some shortcomings of existing LULC models. Using Beijing as a case study, we describe the related driving factors from land-adaptive variables, regional spatial variables and socio-economic variables and then simulate future land use scenarios from 2010 to 2020, which include a development scenario (natural development and rapid development) and protection scenarios (ecological and cultivated land protection). The results indicate good consistency between predicted results and actual land use situations according to a Kappa statistic. The conversion of cultivated land to urban built-up land will form the primary features of LULC change in the future. The prediction for land use demand shows the differences under different scenarios. At higher elevations, the geographical environment limits the expansion of urban built-up land, but the conversion of cultivated land to built-up land in mountainous areas will be more prevalent by 2020; Beijing, however, still faces the most pressure in terms of ecological and cultivated land protection.

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The coordinated promotion of industry–city integration and carbon emission reduction is of great significance to the construction of a green economic system and deep participation in global environmental governance. Based on the overall framework of the “production–life–ecology” system, the theoretical mechanism of the impact of industry–city integration on carbon emissions is systematically clarified. Taking the Yellow River basin as a sample, the spatiotemporal heterogeneity of the effect of industry–city integration on carbon emissions is empirically tested by using the methods of the dispersion coefficient coordination function, standard deviation ellipse and STIRPAT model. The results show the following: (1) The coordinated integration of industry and city has significant carbon emission reduction effects, thus indicating that industry–city integration and carbon neutralization can achieve both, and that the conclusion is still valid after endogenous treatment and a series of robustness tests. (2) The development of an export-oriented economy and informatization can significantly promote carbon emission reduction. The process of economic development, infrastructure construction and population quality improvement may aggravate regional carbon emissions in the short term. (3) Further analysis shows that the carbon emission reduction effect of industry–city integration has significant spatial heterogeneity, especially in the upper and lower reaches of the Yellow River and regions with moderate carbon emission intensity. Scientific and technological innovation and environmental regulation play a positive role in regulating the carbon emission reduction effect of industry–city integration.

It is of great significance to study the interactive relationship between urban transportation and land use for promoting the healthy and sustainable development of cities. Taking Jinan, China, as an example, this study explored the interactive relationship between street centrality (SC) and land use intensity (LUI) in the main urban area of Jinan by using the spatial three-stage least squares method. The results showed that the closeness centrality showed an obvious “core-edge” pattern, which gradually decreased from the central urban area to the edge area. Both the betweenness centrality and the straightness centrality showed a multi-center structure. The commercial land intensity (CLUI) showed the characteristics of multi-core spatial distribution, while the residential land intensity (RLUI) and public service land intensity (PLUI) showed the characteristics of spatial distribution with the coexistence of large and small cores. There was an interactive relationship between SC and LUI. The closeness centrality and straightness centrality had positive effects on LUI, and LUI had a positive effect on closeness centrality and straightness centrality. The betweenness centrality had a negative impact on LUI, and LUI also had a negative impact on betweenness centrality. Moreover, good location factors and good traffic conditions were conducive to improving the closeness and straightness centrality of the regional traffic network. Good location factors, good traffic conditions and high population density were conducive to improving regional LUI.

Tibet is the main consist of the Tibetan Plateau and also inhabited by minorities in China. How to promote its road accessibility and narrow the gap between different ethnic groups should draw more attention. This study analyzes both territorial accessibility (At) and potential accessibility (Ap) in Tibet from 2010 to 2020, as well as the disparities within and between main ethnic groups, exploring whether ethnic minorities undertook the accessibility disparity or loss. The findings are as follows: (1) At and Ap are characterized by a center‐periphery structure with a remarkably improvement and spatial difference from 2010 to 2020. The disparity between counties tends to widen slightly, whereas the increment of At shows the opposite feature. (2) The Hui and Han ethnic groups enjoy better accessibility than Tibetans, and the other ethnic minorities have insufficient accessibility, though with prominent improvement. The disparity in At within ethnic groups is smaller but tends to widen; by contrast, that of Ap is larger but tends to narrow. The Hui ethnic group enjoys relative equal accessibility, which tends to be more so, while Tibetans face unequal accessibility with no obvious improvement. (3) The proportion of Tibetans is negatively correlated with the improved accessibility, but those of the other ethnic minorities are positively correlated with the increment of At, indicating that the accessibility improvement in Tibet tilts to the ethnic minorities in remote areas. The overall spatial disparities in accessibility in Tibet tend to widen, but this does not totally apply to those between and within ethnic groups. Nonetheless, the construction of transport infrastructure alone may not be able to achieve equality. Above results may provide reference for related research and policy making for remote and minority areas in China and other similar regions.

Accompanied by the monetisation of housing allocation, the Housing Provident Fund (HPF) has become an important part of China’s housing security system. As of 2020, HPF has been implemented for almost 30 years, but limited effort has been made to examine its performance, especially from a spatial (regional) perspective. Taking 287 Chinese cities as a sample and using the “access–process–outcome” framework, this study explores the inter-city differences in the performance of HPF and their relevant influencing factors. The results show that (1) there is significant spatial heterogeneity in the performance of HPF in China; (2) from 2015 to 2020, regional variation in the process and outcome performance showed a convergence trend, but the access performance between cities tended to widen and diverge; (3) regression results show that process-relevant variables (i.e., the contribution rate and the capital utilization level) are positively associated with the loan beneficiary rate (the HPF outcome performance), whereas access-relevant attributes (i.e., the HPF participation rate) exert negative influences. The study contributes to revealing the spatial heterogeneity of China’s HPF development. It highlights that more regionally oriented policy interventions are needed for policy makers and practitioners to optimize the development of HPF.