Abstract: In recent years, with the aggravation of climate change and human activities, the global forest area continues to reduce, forest quality keeps declining, and the ecological and environmental events occur frequently. Thus, forest health issues have received unprecedented attention, and have become an important part of the ecological civilization strategy. China’s forest resources continue to grow, but it also faces some problems, such as single afforestation structure, low stand quality and weak ecological stability. How to evaluate forest health systematically and accurately is still a difficult problem. Compared with the traditional ground survey methods, remote sensing technology has the advantages of macroscopic, timeliness and economic efficiency. With the rapid development of high-resolution remote sensing and artificial intelligence technology, it is possible to overcome the problem of forest health assessment. In order to systematically evaluate the potential of new remote sensing technology, this paper points out the existing paths and methods on the basis of literature analysis, including: (1) through bibliometric analysis, four core contents of forest health assessment (vitality, organizational structure, resistance and resilience) and four key issues (tree species classification, forest vitality, forest pests, drought threat) were identified. (2) Systematically interpreting the advantages and disadvantages of existing remote sensing technologies from three angles, namely, different scales (single tree stand ecosystem landscape), different platforms (near ground remote sensing, aerial remote sensing satellite remote sensing) and different sensors (including RGB cameras, multi/hyperspectral cameras, lidar, thermal infrared cameras, microwave radars and chlorophyll fluorescence scanners). (3) Focusing on four key issues, this paper expounds the application path and method of remote sensing technology to evaluate forest health in recent years. Furthermore, this paper points out the challenges and opportunities, including multi-source fusion analysis, forest health monitoring network and near ground remote sensing, forest health big data application, in order to provide reference for the intelligent management of forest resources in China.