Abstract: Forests, as the world’s largest terrestrial carbon sink, play an important role in mitigating greenhouse effects and regulating carbon balance. Analyzing and studying the current status and challenges of forest carbon sink estimation has profound significance.This article reclassifies and explores common forest carbon sink estimation methods based on data source types, and briefy analyzes the research progress and representative research results at home and abroad. The analysis reveals that the estimation of forest ecosystem carbon sinks is currently facing the challenges of data acquisition difficulties（such as remote sensing data quality and resolution issues, scarcity of ground data）, limitations on estimation models and algorithms（such as the limited applicability of existing algorithms, algorithm optimization and innovation）, as well as the obstacles of cross-disciplinary cooperation and data sharing（such as disciplinary barriers, incomplete data sharing mechanisms）. In response to these challenges, this article suggests strengthening the development of new remote sensing sensors and platforms, promoting the application of artificial intelligence and big data technology,deeply utilizing high-resolution remote sensing data, conducting long-term data analysis and prediction, strengthening research on carbon sink and climate change feedback mechanisms, in order to enhance the scientific and accurate estimation of forest carbon sinks,meet the complex needs of future forest carbon sink estimation, and provide scientific basis for global climate change assessment and carbon management strategy formulation.