摘要：Wetlands are important ecosystems but face a grim future due to the impacts of human activities, such as lost area and function. Their landscape patterns and the environment quickly respond to external disturbance. This paper selected Jiaozhou Bay as the study area and used man-machine interactive remote sensing to extract information from wetlands. Human disturbance indices and landscape transition methods were used to conduct a scenario analysis of the evolution of landscape disturbance in Jiaozhou Bay wetlands from 1973 ~ 2018. The quantitative and spatial changes in landscape disturbance types on the wetlands were also analyzed, the changes were clustered and merged, and the dynamic change types of disturbance in the study area were summarized. Among landscape disturbance types, anthropogenic renewable and non-renewable landscapes increased continuously: in particular, the anthropogenic non-renewable type had the largest area increase, a testament to continued human disturbance. After these types of changes are sorted out, a K-Means clustering algorithm was used to classify the dynamic characteristics of disturbance transition into nine types. Due to their superior physiographic conditions, the wetlands of Jiaozhou Bay have been more vulnerable to disturbance by human activities, national industrial policies, socio-economic development, and other factors have also contributed to intensified disturbance.
