Abstract: Research on remote sensing extraction method of bamboo forest information is beneficial to the development of bamboo forest ecological economic and the protection of ecological environment. In this paper, the development remote sensing extraction method of bamboo forest information was summarized into three stages, including traditional statistical recognition model, machine learning classification, and multi-source information composite classification. It was pointed out that due to the influences of bamboo forest growth characteristics, remote sensing data sources and remote sensing information extraction method, bamboo forest information extraction faced the difficulty of obtaining remote sensing data with high temporal and spatial resolution, the incompleteness of optical remote sensing information extraction, the difficulty of extracting bamboo forest information under the forest canopy, and the lack of precision of large spatial scale information extraction. Based on the development history, current situation and future development trend of bamboo forest information extraction, it is urgent to carry out more basic bamboo forest research, improve track sensors, realize dynamic monitoring of multi-source and multi-time series data, and deepen the cross-integration of various extraction methods.