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Agriculture is important for economic development in most poverty-stricken areas in China, but cropland use is facing challenges due to rapid industrialization and urbanization, causing serious issues for poverty alleviation and sustainable socioeconomic development. Cropland Use Transition (CUT) is one way to alleviate poverty and develop the economy in poverty-stricken areas. This paper chose 16 typical poverty-stricken counties in Western Hubei province as the case area. A morphology index system was established to evaluate CUT, and geographic information system software was used to analyze the temporal-spatial variations in CUT. Using the Radial Basis Function Neural Network (RBFNN) model, contributions of driving factors of population, economy, and industrial structure to CUT were analyzed. The results show that: (1) cropland use morphology can be divided into functional morphology and spatial morphology; (2) the spatial distribution of CUT was high in the north and low in the south, the temporal variation of CUT from 1995 to 2013 showed fluctuations, and the coefficient of CUT changed from 0.460 to 0.649 with a growth rate of 41%; (3) for the driving factors, population factors most significantly contributed to CUT, followed by industrial structure and economic factors. The results obtained in this study are in line with the findings of previous studies. The RBFNN model is suitable for evaluating the contributions of driving factors, which can solve the deficiency in previous studies caused by ignoring the internal relationship and target orientation of driving factors. This study suggests that poverty-stricken counties should narrow the urban–rural divide, encourage balanced labor and investment flow into cropland by formulating relevant economic policies, motivate farmers’ agricultural engagement, and use science and technology to promote CUT and the growth of the agricultural economy, poverty alleviation, and to coordinate urban–rural development.

Urban growth and shrinkage constitute the overall pattern of growing urbanization across the globe. Studies on urban vacant land (UVL) are few, and have proved to be mainly rudimentary and subjective. This paper first presents the definition of UVL based on bibliometric analysis. Typology, morphology, proximate causes, and the multiple functions of UVL are then analyzed at parcel, transect, city, and national levels based on an international review. Results show that UVL can be categorized by land cover, land usage, and land ownership. Worldwide, UVL has been widespread and extensive. For example, the occurrence probabilities of UVL in the cases of Guangzhou and New York are 8.46%-8.88% and 3.17%-5.08%, respectively. The average vacancy rate of residential land amounts to 11.48% in 65 U.S. cities. Generally, UVL shows fragmentation and irregular shape, and significant spatial differences exist at parcel, transect, city, and national levels. Proximate causes, such as excessive land division, irregularly shaped land parcels, decreases in resident population, deindustrialization, land speculation, insufficient investment, and environmental concerns, can all result in UVL. Currently, UVL has become a gray area of social, economic, and ecological space. However, it can also be considered a potential resource for enhancing urban sustainability. Policy implications to promote urban sustainability using monitoring, control, and differential revitalization of UVL are presented.

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The terrestrial ecosystem plays an important role in maintaining an ecological balance, protecting the ecological environment, and promoting the sustainable development of human beings. The impacts of precipitation, temperature, and other natural factors on terrestrial ecosystem pattern change (TEPC) are the basis for promoting the healthy development of the terrestrial ecosystem. This paper took the Yangtze River Economic Belt (YREB) as the study area, analyzed the temporal and spatial characteristics of TEPC from 1995 to 2015, and used spatial transfer matrix and terrestrial ecosystem pattern dynamic degree models to analyze the area transformation between different terrestrial ecosystem types. A bivariate spatial autocorrelation model and a panel data regression model were used to study the impacts of precipitation and temperature on TEPC. The results show that: (1) The basic pattern of the terrestrial ecosystem developed in a relatively stable manner from 1995 to 2005 in the YREB, and transformations between the farmland ecosystem, forest ecosystem, and grassland ecosystem were more frequent. The temporal and spatial evolution of precipitation and temperature in the YREB showed significant regional differences. (2) There was a significant negative bivariate global spatial autocorrelation effect of precipitation and temperature on the area change of the forest ecosystem, and a positive effect on the area change of the settlement ecosystem. The local spatial correlation between precipitation or temperature and the terrestrial ecosystem showed significant scattered distribution characteristics. (3) The impacts of precipitation and temperature on TEPC showed significant regional characteristics on the provincial scale. The impact utility in the tail region is basically negative, while both positive and negative effects exist in the central and head regions of the YREB. Moreover, the impact showed significant spatial heterogeneity on the city scale. (4) The Chinese government has promulgated policies and measures for strategic planning, ecological environment protection, and economic support, which could effectively promote ecological and sustainable development of the YREB and promote the coordinated development of the ecology, economy, and society in China.