Forest health is an important aspect of sustainable forest management. The practical significance of health assessments of forest ecosystems is becoming more and more prominent because good knowledge about the health level of forests and the causes of unhealthy forests enables the identification of proper actions for enhancing sustainable development of forest ecosystems. This paper evaluated the health status of the forest ecosystem of Mount Taishan using the spatial analysis technique of GIS (Geographic Information System) and local forest inventory data. A comprehensive indicator system that reflects the health status of forestsin the study areawas established. Based on this indicator system, the health level of each sub-compartment of the forests in the study area was assessed. The results show that the high-quality grade forest (80.4 ha) and healthy grade forest (2671 ha) accounted for only 23.5% of the total forest area of Mount Taishan. About 60.5% of Mount Taishan forest was in a sub-health status. The area of unhealthy forests was 1865 ha (accounting for 16% of the total forest area), of which about 98 ha was inextremely unhealthy conditions.Asmore than two-thirds of the forests in Mount Taishan are in a sub-health or unhealthy state, effective measures for improving forest health are in urgent need in the study area.

Located in the Mount Tai state-owned forest farm, this study adopted Landsat multispectral remote sensing data in 2000 and 2016 on the GEE (Google Earth Engine) platform and selected four phases of images each year according to the phenological period. By dealing with the current situation map of forestry resources in 2000 and the field survey data in 2016, the samples of tree species distribution in 2000 and 2016 were obtained. On the basis of topographic correction with the empirical rotation model, this study used the random forest (RF) classifier to classify tree species from remote sensing images in 2000 and 2016, achieving high classification accuracy. The results showed that, after 16 years of evolution, the percentage of pine species in the forest decreased from 55.69% to 50.22%, with a percentage decrease as high as 5.47%. The percentage of black locust (Robinia pseudoacacia) increased from 10.15% in 2000 to 13.75% in 2016, with an increase of 3.60%. Quercus also had a positive growth in the area. This result reflected the expansion of black locust.