The major grain-producing areas will be the key areas of future China fallow. It is important to explore the influence of farmers’ value perceptions on their fallow willingness in these areas. We analyzed this impact of value perception by using an ordered PROBIT model and survey data from the major grain-producing areas of Hubei and Hunan, China. The conclusions of this study are as follows: (1) A considerable proportion of farmers are willing to participate in farmland fallow, while a considerable proportion of farmers are neutral; (2) farmers’ value perceptions of farmland fallow have a significant positive impact on their fallow willingness; (3) farmers’ ages and education levels have a positive impact on farmers’ willingness to directly participate in farmland fallow, while per capita farmland area has a negative impact; (4) the key factors for successful fallow are solving the problem of non-agricultural employment of farmers and appropriately formulating fallow mode, scale, and subsidy standards. This study proposes that the government can develop farmers’ good value perceptions of fallow through appropriate subsidies and adequate publicity to strengthen their fallow consciousness.

The rapid and disorderly expansion of urban construction land has exacerbated the contradiction between land use and low-carbon development. In this paper, we use the spatial autocorrelation model and coupling model to analyze the spatial characteristics of the coupled coordination degree of land transfer and carbon emissions in 291 cities in China. The multi-scale geographically weighted regression (MGWR) model is used to explore the spatial heterogeneity of the influence of socioeconomic factors on their coupled coordination degree. The results show that: from 2005 to 2015, the scale of land transfer and carbon emissions has been increasing quantitatively and spatially showing a shift from the southeast coast to the central and western regions. In 2005, 2010, and 2015, the global Moran’s I of the coupled coordination degree are .3045, .3725, and .3388, respectively, indicating that the coupled coordination degree between land transfer and carbon emissions has a significant positive spatial autocorrelation. The MGWR model indicates that the influence of socioeconomic factors on the coupling coordination degree has significant spatial heterogeneity at different time nodes. In 2005 and 2015, the coefficients of the NGR on the coupling coordination of land transfer and carbon emissions have obvious stratification characteristics, with the coefficients decreasing from northeast to southwest. In 2010, the high coefficient (.924∼.989) of GPC is mainly distributed in the central region. The coefficient of the PD ranges from .464 to .918, but the difference of influence degree between the southeast coast and the northwest is obvious. This study may provide new clues for sustainable urban development and carbon reduction.

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Studying the spatial-temporal distribution industrial sprawl in China is important to solve industrial sprawl problems and promote urban sustainable development. This paper constructed a multi-level spatial analysis of the Chinese industrial sprawl during 2010–2019 by mainly using urban scaling law, supplemented by GIS methods. Results showed that: (1) China had obvious industrial sprawl with a growth rate of 31.79%, reaching 2762.37 km2 between 2010 and 2019. (2) There was a stronger industrial sprawl in large cities with a larger population according to urban scaling law, especially in the East. (3) The industrial sprawl was mainly concentrated in the cities in the Northeast, Beijing-Tianjin-Hebei region, Shandong Peninsula, Yangtze River Delta region, Pearl River Delta region, Middle Yangtze River region, Fujian Province, and some cities in the West. (4) The gravity center of industrial sprawl generally moved southwest and distributed in Hubei Province. This study provided references for improving the efficiency of industrial land use and promoting high-quality urban development.