基于RGB模式的一种草地盖度定量快速测定方法研究

盖度是研究植物群落结构的一个重要数量指标,传统目视估算法精度低且受人的影响较大。本研究分析了大量荒漠草地实地照片的RGB颜色模式特征,构造了RGB颜色判别决策树区分植被与非植被像元来计算植被的覆盖度,同时在Matlab 7.0平台上将数码照片的导入、地物判别、盖度计算、划分结果显示、对照等功能模块集成,构建用户界面友好、人机交互便捷软件模块,从而能够准确、高效地计算草地盖度,方便了草原实地调查工作。与针刺法相比,该方法计算得到的植被覆盖度最大偏差绝对值不超过5%,精度在95%以上,解决了常规人工方法中估测草地盖度工作量大、不能准确定量测定的问题。

A quantitative analysis method for measuring grassland coverage based on the RGB model

Coverage is an important quantitative index for plant community structure. Traditional visual estimation of the coverage of plant communities not only had low precision but was also influenced by subjectivity. After analyzing the RGB (red-green-blue) mode of field photographs from desert grassland, the algorithms of an RGB color decision tree were constructed to calculate the vegetation coverage through distinguishing plant and non-plant digital pixels. Software was constructed with a friendly interface after: integrated human-computer interaction convenience, integrated function blocks of digital photograph import, object identification, coverage calculation, results display, and comparisons in the Matlab 7.0 platform, had achieved accurate and efficient calculation of grass coverage and facilitated grassland field investigations. Compared with acupuncture, the maximum absolute deviation of this algorithms was less than 5%, and the resulting vegetation coverage accuracy was more than 95%. This method could solve the problems of the heavy workload and inaccurate quantitative determination in normal manual estimation of grassland coverage.