Objectives: (1) to explore what kind of green infrastructure (GI) meets the demand for urban ecological security of rapid urbanization areas; (2) to figure out how to determine the specific function and configuration of GI from ecosystem service requirements of urban ecological security. Methods: (1) Through the literature review, this article summarizes the function and structure evolution of GI in order to adapt to urban growth. (2) Standing on the imperfect ecological functions and unreasonable spatial configurations, this article builds up a conceptual model for the optimization of green infrastructure ecosystem services to meet the demand for the green infrastructure pattern needed by urban growth. Results: The optimization framework consists of four central function modules and its regulating and controlling mechanisms, including: (1) Balancing supply and demand of GI’s ecosystem service; (2) Measuring and evaluating GI’s ecosystem services; (3) Elevating and optimizing GI’s ecosystem service; (4) Building urban ecological security pattern with high efficiency of GI’s ecosystem services. Moreover, this framework provides guidance for the planning and design of GI and the urban ecological security pattern building in rapid urbanization areas based on balancing supply and demand of GI’s ecosystem services. Conclusion: The conceptual model of GI’s ecosystem service optimization based on balancing supply and demand shows a new path to meet the needs of urban growth and build a city's ecological security pattern through upgrading and optimizing GI.

The method presented is helpful for assessing effects of land use policy and unfolding the action mechanism and implementation effect of policies on land use changes. The backcasting method is based on the re-simulation of the historical real changes of land use. By observing the error between the real and simulated states, adjust the parameters for many times, and a variety of land use scenarios are obtained, and the scenario with the minimum and acceptable error is selected to assess the effects of land use policy represented by its parameters. The method is structured in four sequential stages, including expressing the policy action mechanism as the parameter combinations to control land use changes, and then translating the parameter combination that can reflect the effect of land use policies into the policy effectiveness. This process is realized by ArcGIS and GeoSOS-FLUS software developed based on Cellular Automata (CA) model. The method was successfully tested in the peri-urban region near Shanghai metropolitan area. The raw material is Land-Use/Cover (LULC) data of study area in 2000 and 2015. This method assessed the effects of land use policies during fifteen years, and analyzed the mechanism of effective policies, as well as the types and reasons of failure policies. This presented method is useful in land governance and the formulation and implementation of land use policy. •This article developed a backcasting approach to evaluate the effectiveness of land use policies on land use changes in a certain period of time.•The policy action mechanism was transformed into controllable, visible, and adjustable parameter combinations.•The method built an analytical framework for the assessment of land use policy effectiveness in any regions.

Urban development and human activities have greatly changed the appearance of urban landscapes, and also affect urban river water environments. Rapidly urbanized regions in China face particularly severe pressures and challenges in alleviating degradation of river water quality. Information is needed on which indexes of landscape development intensity in rapidly-urbanized areas are the key factors affecting the quality of river water environments, and how these factors affect water quality. In order to answer these questions, this research selected six indexes belonging to three dimensions for landscape development intensity evaluation. Based on five water quality parameters of 20 rivers and the land use data of 20 small watersheds of Liangjiang New Area, Chongqing, China in 2014, this research explored the correlation between the landscape development intensity indexes and river water quality through redundancy analysis. We found that the impervious surface rate and the land average fixed asset investment are the key indexes to affect river water quality. Regulating the corresponding indexes at the urban planning and design level, as well as the decision making level, can effectively achieve the goal of improving urban river water quality. The conclusions inspire strategies in planning and design, and are helpful for government decision making to effectively protect river water environment in rapidly urbanized areas in the developing countries.

Global urbanization and post-industrialization have resulted in the emergence of a large number of brownfields. The integration of brownfields into green infrastructure (GI) has been widely recognized as a sustainable development strategy in metropolitan areas. It is important to spatially prioritize brownfields catering for GI, which can enable the greatest enhancement of urban functions. Various studies have assessed brownfield site attributes or urban demands to define the priority of brownfields transformed into GI, but it is key to consider the coupling coordination between urban demands and site attributes in order to achieve more accurate matches. In this paper, an approach is proposed for assessing the priority of brownfields catering for GI in Xuzhou, China; this involved calculating the coupling coordination degree between site attributes and urban function demands, including heat island mediation, stormwater regulation, disaster prevention, landscape aesthetics improvement, and leisure and recreation increments. The results showed that 42.52% of the brownfields have a high degree of coupling coordination (“good coordination” and “primary coordination”) between site attributes and urban demands. Furthermore, 40.82% of the brownfields (120 plots) were selected to be integrated into urban GI; these are not only located in high urban functional demand areas, but also have a high coupling coordination degree. These brownfields were divided into three priority levels, and 4.42% and 17.69% of the total brownfields are of very high and high priority. Our proposed approach offers an accurate decision-making tool for urban GI optimization in high-density built-up metropolitan areas, and offers guidance for brownfield redevelopment.