<p>In the context of accelerated urbanization, ecological and agricultural lands are continuously sacrificed for urban construction, which may severely affect the urban ecological environment and the health of citizens in cities in the long-term. To explore the sustainable development of cities, it is of considerable significance to study the complex and non-linear coupling relationship between urban expansion and the ecological environment. Different from static quantitative analysis, this paper will establish a spatial dynamic modeling approach couples the urban land-use change and ecosystem services. The spatial dynamic modeling approach combines a network-based analysis method with accurate environmental assessments, which includes a causal change mechanism that simplifies the complex interaction between the urban system and the surrounding environment. Because the model can use a pre-determined cell transformation rules to simulate the conversion probability of land cells at a specific point in time, it provides the opportunity to test the impact of changes in different policy scenarios. In the phase of the environmental impact assessment, the change probability will be converted into an environmental impact based on the calculation of the ecosystem services values under different development scenarios. Taking Nanjing, a rapidly developing city in China as an example, this paper will set up a variety of sustainable development policy scenarios based on the feedback relationship of local land use driving factors. We will test and evaluate the &#8220;what-if&#8221; consequences through a comparative study to help design the optimal environmental regulation scheme. Planning and decision support will be made to further guide the rational allocation of land use parcel and land development intensity towards a sustainable development future. As a result, this study can support policy decision makings on urban land-use planning and achieve ecological and agricultural land preservation strategies.</p>
Cellular automata-based spatial dynamic modeling for analyzing urban land use change