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.

No abstract

No abstract

No abstract

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.