a b s t r a c tLand marketization and housing commodification have stimulated inner-city restructuring and urban expansion in China and have also induced a large amount of population displacement. Affordable housing, as part of compensation, tends to be the most common relocation housing for displaced households. It is allocated through two approaches: in-kind compensation and monetary compensation. Local government provides in-kind compensation to displaced households in the form of affordable housing, as direct compensation for demolished houses, and gives priority to those who have received monetary compensation to enable them to purchase affordable housing at a discount from the market price. The process of negotiation between local government and displaced households is complicated. As a result, uneven compensation occurs in terms of compensation approaches, as well as in how much displaced households are paid for similar new affordable houses. This study conducts a detailed analysis of the uneven displacement compensation and relocation process. It uses residential surveys conducted in Nanjing to examine uneven compensation along two dimensions: compensation approaches and the purchasing discount on new, compensated affordable housing.

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Quantifying the long-term trends of changes in terrestrial vegetation on a large scale is an effective method for detecting the effects of global environmental change. In view of the trend towards overall restoration and local degradation of terrestrial vegetation in China, it is necessary to pay attention to the spatial processes of vegetative restoration or degradation, as well as to clarify the temporal and spatial characteristics of vegetative growth in greater geographical detail. However, traditional linear regression analysis has some drawbacks when describing ecological processes. Combining nonparametric linear regression analysis with high-order nonlinear fitting, the temporal and spatial characteristics of terrestrial vegetative growth in China during 1982-2012 were detected using the third generation of Global Inventory Modeling and Mapping Studies (GIMMS3g) dataset. The results showed that high-order curves could be effective. The region joining Ordos City and Shaanxi Gansu Ningxia on the Loess Plateau may have experienced restoration-degradation-restoration processes of vegetative growth. In the Daloushan Mountains, degradation-restoration processes of vegetative growth may have occurred, and the occurrence of several hidden vegetative growth processes was located in different regions of eastern China. Changes in cultivated vegetation were inconsistent with changes in other vegetation types. In southern China and some high-altitude areas, temperature was the primary driver of vegetative growth on an interannual scale, while in the north, the effect of rainfall was more significant. Nevertheless, the influence of climate on vegetation activity in large urban areas was weak. The trend types of degradation-restoration processes in several regions were inconsistent with the implements of regional land development and protection strategy. Thus, the role of human activity cannot be ignored. In future studies, it will be still necessary to quantify the effects of human management on spatial patterns, develop trend-fitting methods, and explore more refined methods of analyzing the driving forces affecting large-scale changes in vegetative growth.

Schistosomiasis remains a major public health problem in the South China, particularly in lake and marshland regions. Modelling the spatio-temporal pattern of schistosomiasis guides disease prevention and control programs and is a research area of growing interest. However, few attempts have been made to evaluate the changing (nonlinear) effects of environmental determinants on schistosomiasis. In this context, a hierarchical spatiotemporal model was applied to evaluate how environmental determinants affect the changing trend of schistosomiasis in Anhui Province, China, based on annual parasitological and environmental data for the period 1997-2010. Results showed that – compared to changing effect – environmental factors had a constant (linear) effect on schistosomiasis. The disease was also found to fluctuate over time, which was due to the two latest national schistosomiasis control programs. In addition to statistical benefits of this approach, our analysis implied that climate change might not contribute to variation of schistosomiasis; rather, prevention activities affect schistosomiasis when the disease prevalence remains at a low level. Finally, the analytical method proposed in our study provides a template for modelling the spatio-temporal pattern of a disease whose transmission is largely determined by environmental determinants.