天山云杉林无人机可见光影像树冠信息提取方法研究
收稿日期: 2019-10-23
修回日期: 2019-12-04
网络出版日期: 2020-05-18
基金资助
新疆维吾尔自治区自然科学基金面上项目(2018D01A20)
Study on Extraction of Tree Crown Information from UAV Visible Light Image of Piceaschrenkiana var.tianschanica Forest
Received date: 2019-10-23
Revised date: 2019-12-04
Online published: 2020-05-18
高精度轻小型无人机森林树冠参数信息提取方法是森林资源监测和生态功能评估的重要基础。以新疆山地森林优势树种天山云杉为研究对象,在南山实习林场采集积雪背景下无人机遥感影像并进行预处理,对比分析3种方法(以光谱为特征空间的面向对象法、以光谱+纹理为特征空间的面向对象法、随机森林法)提取天山云杉林树冠参数信息的精度。结果表明:3种方法提取天山云杉林分郁闭度精度均高于93%,其中以光谱为特征空间的面向对象法最优,精度可达93.73%;3种方法自动提取单木树冠面积与目视解译结果的 R 2 均大于0.91,虽然随机森林法的统计指标最优,但面向对象法可获得完整的单木树冠闭合曲线,故以光谱+纹理为特征空间的面向对象法效果较优;面向对象法的最优分割尺度为29,纹理特征的加入会导致郁闭度提取精度降低0.66%,但会优化单木树冠面积提取效果。
金忠明 , 曹姗姗 , 王蕾 , 孙伟 . 天山云杉林无人机可见光影像树冠信息提取方法研究[J]. 林草资源研究, 2020 , 0(1) : 125 -135 . DOI: 10.13466/j.cnki.lyzygl.2020.01.016
The extraction method of forest tree crown parameter information obtained by high-precision light and miniature unmanned aerial vehicle(UAV)is an important basis for forest resource monitoring and ecological function evaluation.Taking the Piceaschrenkiana var.tianschanica,the dominant tree species in the mountainous forests of Xinjiang,as the research object.Collecting and preprocessing remote sensing images of UAV with the background of snow in the Nanshan Internship Forest Farm.The three methods(object-based method with spectral feature space,object-based method with spectral+texture as feature space and random forest method)were compared and analyzed to extract the accuracy of forest tree crown parameter information of Piceaschrenkiana var.tianschanica forest.The results show:the accuracy of the canopy density to be extracted by the three methods is higher than 93%,and object-based method with spectral+texture as feature space is the best,its accuracy reaches 93.73%.The R 2 of the visual interpretation result and the single tree crown area to be extracted by the three methods aremore than 0.91.Although the results to be extracted by random forest method are closest to the visual interpretation value,the object-based method obtains the complete single tree crown closure curve,so the object-based method with spectral+texture as the feature space is the best method for extracting the single tree crown area.The optimal segmentation scale for extracting canopy density and single tree crown area using object-based method is 29,and adding texture features reduces the accuracy of canopy density extraction by 0.66%,but optimizes the extraction effect of single tree crown area.Therefore,the UAV image is an effective way to extracting theforest tree crown parameter information accurately,quickly and automatically,and optimal extraction method can be selected according to different crown parameter information.
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