An integration method to predict the impact of urban land use change on green space connectivity under different development scenarios using a case study of Nanjing, China

Abstract

Urbanization leads to land use change and fragmentation of green patches, affecting natural habitats and their connectivity. Scientific prediction and analysis of the impact of future land use change on green space connectivity are an effective tool for planning and evaluating urban sustainable development, especially for ecological protection in rapidly developing areas. In this study, an integrated method is proposed that uses the CA-Markov method and combines a morphological spatial pattern analysis (MSPA) with a graph theory analysis to jointly evaluate the impact of land use change on the habitat connectivity index under different urban development scenarios from two aspects of structural and functional connectivity. Using China's rapidly developing Nanjing as the study area, the land use changes under four scenarios in 2030 are forecast, and the connectivity index is analyzed. The results showed that only under the ecological land protection scenario will forest and grassland increase, but the strong barrier effect is still brought about by urban expansion from the analysis of the structural connectivity. At the level of functional connectivity, we identified the important connecting patches and future change trends of species with different diffusion distances. In addition, we identified the key connecting patches (i.e., stepping stones) and changes and suggested giving priority to the protection of these patches. This method can be applied to other rapidly developing cities, and the conclusions can be used as a spatial explicit tool for urban green space and land use planning.