Bangrong Shu

Understanding the impact of the three pilot reforms of the rural land system (TRRLS) on rural residential land use transition (RRLUT) based on the land use transition (LUT) theory is crucial for promoting rural land system reform. However, there is still a lack of research on this, and the LUT theory also needs to be improved from a systematic perspective to eliminate the misunderstanding of LUT in academia. To address this, this study firstly attempts to deepen the conceptual model and the understanding of characteristics of LUT from a regime shifts perspective. LUT is the transformation of the land use system as one regime passes into another, where a difference in the analytical perspective of land use morphology generates different transition results. The process of LUT can simultaneously or solely involve dominant morphology and recessive morphology transitions, and there are two types of LUT: positive and negative transitions. Moreover, LUT in different regions may have pathway differences and the convergence of results. Then, a theoretical analysis framework of the pathways of RRLUT under the TRRLS is constructed to detect the impact mechanism by using Wujin district, China to obtain empirical evidence. The results reveal that the recessive morphology transition of rural residential land in Wujin under the TRRLS is significant, while the dominant morphology transition in land quantity structure and spatial distribution is relatively slow. Furthermore, two internal factors of population urbanization and migration, the demand for rural collective economic development, as well as the two external factors of the TRRLS and market factors, such as nonlocals’ demand for housing and rural enterprises’ demand for land, have, to a certain extent, weakened the resilience of the rural land use system and promoted RRLUT. Here, the TRRLS have, by removing the institutional barrier to RRLUT, become the key to the transition.

Understanding land-expropriated farmers’ welfare change and the determinants of their willingness to change is very important for sustainable urbanization and social stability in developing countries. However, this issue has been seldom explored in previous studies, especially in China. This paper aims to enrich this field by conducting an empirical study using a household survey in 2014 in Nanjing, a major city in the Yangtze River Delta. The impacts of land expropriation on the variation of land-expropriated farmers’ employment and inhabitance are explored, while the determinants of land-expropriated farmers’ willingness are estimated using ordered logistic regression. Results show that the land-expropriated farmers pay more attention to the changes of employment and inhabitance after land expropriation, rather than land expropriation itself. While employment aspects were key determinants of the farmers’ willingness in 1996, factors relating to inhabitance aspects have become more important nowadays. Moreover, it is necessary to grasp the changing rules of land-expropriated farmers’ interest appeals in order to adjust the compensation and resettlement policies according to local conditions. Thus, this will improve land-expropriated farmers’ willingness. Meanwhile, the government should create a better expectation of employment and inhabitance after land expropriation for farmers. Furthermore, the government should also build a land expropriation information sharing and feedback mechanism in addition to improve the employment and housing security system.

Simulation models based on cellular automata (CA) are widely used for understanding and simulating complex urban expansion process. Among these models, logistic CA (LCA) is commonly adopted. However, the performance of LCA models is often limited because the fixed coefficients obtained from binary logistic regression do not reflect the spatiotemporal heterogeneity of transition rules. Therefore, we propose a variable weights LCA (VW-LCA) model with dynamic transition rules. The regression coefficients in this VW-LCA model are based on VW by incorporating a genetic algorithm in a conventional LCA. The VW-LCA model and the conventional LCA model were both used to simulate urban expansion in Nanjing, China. The models were calibrated with data for the period 2000–2007 and validated for the period 2007–2013. The results showed that the VW-LCA model performed better than the LCA model in terms of both visual inspection and key indicators. For example, kappa, accuracy of urban land and figure of merit for the simulation results of 2013 increased by 3.26%, 2.96% and 4.44%, respectively. The VW-LCA model performs relatively better compared with other improved LCA models that are suggested in literature.