[目的]以无入机高清影像为数据源,结合样地实地调查数据,研究杨树冠幅提取及其与胸径和林分蓄积量的相关性,为无人机森林调查技术提供一种思路和方法.[方法]基于无人机高分影像及实地调查数据,采用面向对象法,对杨树林木冠幅进行分割与提取,通过实地测量数据建立冠幅-胸径模型,利用一元材积表计算样地蓄积量,并进行相关性分析与精度检验.[结果]影像分割效果良好,但提取得到的冠幅比实际值偏小,研究区最适宜的杨树冠幅分割尺度为10,平滑度0.1,紧致度0.5.杨树冠幅与胸径建立相关模型,其中一元线性方程拟合效果最好,相关系数为0.75.通过模型计算的样地蓄积与实测样地蓄积进行双侧T检验,结果sig =0.058 ＞0.05,两组数据差异不显著.[结论]采用面向对象法,通过无人机高分影像能自动分割并提取了杨树林木冠幅信息,提取效果良好;利用影像提取林木平均冠幅,通过冠幅-胸径相关关系模型得到林木胸径,进而推算林分蓄积的方法可以满足森林资源调查精度要求.%[Objective] To research poplar crown extraction and stand volume correlation based on UAV high resolution image and field investigation data,and to provide ideas and methods for UAV forest survey technology.[Method] Based on the data from the high resolution image acquired from UAV and the field investigation,the crown of poplar were segmented and extracted by object-oriented method,then modified it by field measured crown,and the crown-DBH model was established through field measurement data.Finally,the sample plot volume were calculated through single entry volume table and the correlation analysis and accuracy test were conducted.[Result] The crown image segmentation showed a good result,but the extraction of the crown was smaller than the actual value.The most suitable image segmentation scale,smoothness,and compactness of poplar crown were 10,0.1,0.5.Some poplar crown and DBH related models were established.It showed that linear equation had best fitting effect and its correlation coefficient was 0.75.T test of the volume which was calculated by related model and the field investigation volume showed sig =0.058 ＞ 0.05,indicating that no significant difference in the two groups data.[Conclusion] By object-oriented method,the poplar crown is extracted effectively through the UAV high-resolution image.The method is accord with the accuracy demands of forest resources survey,which extracts poplar average crown by image and obtains poplar DBH by crown and DBH relationship model,then calculates stand volume.
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