Ecological Security Assessment Based on Remote Sensing and Landscape Ecology Model

The various ecological processes of human beings are not only restricted by the landscape pattern on the regional scale but also affect the local and regional landscape together with global climate change. To date, most of the research on ecological security is based on the pressure-state-response (PSR) model, while there were a few studies based on the landscape ecology model approach. In addition, there has been little literature focus on the dynamic change process of ecological security, especially the simulation and prediction of the future development trend of ecological security. The purpose of this research is to establish a landscape ecological security evaluation method based on grid division, be aimed at breaking the inherent drawbacks of the administrative region as a unit mode approach, anticipated to better reflect the landscape ecological security status of the study area. A complex framework was constructed by integrating random forest algorithm, Fishnet model, landscape ecology model, and CA-Markov model. Multitemporal remote sensing data were selected as a data source, and land use maps of the study area were obtained through the random forest machine learning algorithm firstly. And then, the study area is divided into 307 grids of 2 kmx2 km using the Fishnet model. Next, the landscape disturbance index, landscape vulnerability index, and landscape loss index are used on the grid scale to establish a landscape ecological security evaluation model. Finally, ecological security assessment of Zhengzhou city was carried out, and the distribution map of the landscape ecological status in 1986, 1996, 2006, 2016, and predicted for 2026 was obtained. The results of the study showed that, as time goes by, the areas with high ecological safety gradually decrease. It is predicted that by 2026, the ecological security level of Zhengzhou will be dominated by lower ecological security areas. The research results can provide basic information and decision support for government agencies and land use planners to ensure responsible and sustainable development of the urban environment and ecology.