Land use/cover change （LUCC） models are helpful tools for analyzing driving forces and processes of land use changes, assessing ecological impacts of land use change and decision-making for land use planning. However, no single model is able to capture all the essential key processes to explore land use change at different spatial-temporal scales and make a full assessment of driving factors and macro-ecological impacts. Taken Ganzhou District as a case study, this paper describes an integrated analysis （IA） ap- proach by combining with system dynamics （SD） model, the Conversion of Land Use and its Effects at Small regional extent （CLUE-S） model and landscape indices method to analyze land use dynamics at different spatial-temporal scales. The SD model was used to calculate and predict demands for different land use types at the macro-scale as a whole during 2000-2035. The LUCC process was simulated at a high spatial resolution with the spatial consideration of land use spatial policies and restrictions to satisfy the balance between land use demand and supply by using the CLUE-S model, and Kappa values of the map simulation are 0.86 and 0.81 in 2000 and 2005, respectively. Finally, we evaluated the macro-ecological effect of LUCC and optimized sce- nario managements of land use by using landscape indices method. The IA approach could be used for better understanding the complexity of land use change and provide scientific support for land use planning and management, and the simulation results also could be used as a source data for scenario analysis of different hydrological and ecological processes based on different un- derlying surface of LUCC.
Public willingness to pay （WTP） for urban rivers res- toration was investigated in Shanghai, Nanjing and Hangzhou in China with a sample of 1,285. The factors influencing positive WTP against zero WTP are analyzed using a binary logit model. The results indicate that income, Huff （residential registration） status, household size, home property ownership, riverfront access, and attitudes toward current water quality arc statistically signifi- cant in the likelihood of positive WTR It is also found that respon- dents without local Huff are less willingness to pay positively in pooled sample and Shanghai sample. In the group holding property right of house but without local Huff is less willingness to pay positively in Hangzhou. Respondents in Nanjing are more will- ingness to pay positively than those in Hangzhou. Most common arguments against to pay for the restoration are ＂government＇s duty＂, ＂low income＂, ＂non-local-Huji＂ and ＂lack of trust in the government in how it spends money＂. The results are generally consistent with the hypothesis and specific situations in China. The findings make some contributions to the non-market valua- tion studies as well as provide useful information for public policy making in China.
