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竹林信息遥感提取方法研究进展

Research Progress on Remote Sensing Extraction Method of Bamboo Forest Information

  • 摘要: 开展竹林信息遥感提取方法研究有利于竹林生态经济发展和生态环境保护。本文梳理了竹林信息遥感提取方法发展的三个阶段,包括传统的统计识别模型、机器学习分类、多源信息复合分类。指出受竹林生长特征、遥感数据源及遥感信息提取方法的诸多影响,竹林信息提取面临高时空分辨率遥感数据难获取、光学遥感信息提取具有不完备性、林冠下竹林信息提取难度大以及大空间尺度信息提取精度欠缺等不足。基于竹林信息提取发展历史和现状问题,展望未来发展趋势,亟待开展竹林基础研究、跟踪传感器改进、实现多源长时序数据动态监测、加深多种提取方法交叉融合。

     

    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.

     

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