树冠是树种识别、估测树木胸径、估算森林蓄积量、监测树木生长情况的重要指标。无人机遥感具有低成本高精度等优势,非常适合高分辨率影像的获取。以杭州市临安区青山湖风景区的水杉林为研究对象,采用无人机获取不同飞行高度以及不同郁闭度的遥感影像为数据源,基于面向对象法提取平均冠幅。以地面实测的平均冠幅作为参考,在相对低郁闭度的情况下飞行高度在65,70,75m时冠幅提取精度分别为:95.39%,94.80%,94.29%。在相对高郁闭度的情况下冠幅提取精度分别为:89.10%,88.10%,88.03%。研究结果表明,在研究范围内,随着无人机高度的增加,冠幅提取的精度逐渐降低,且在两种不同郁闭度的情况下同样适用,其精度都在88%以上。该方法高效可靠,在森林资源调查中有重要的现实意义。

Tree crown is an important index for tree species identification,estimation of tree DBH and forest volume,and monitoring tree growth. UAV remote sensing has the advantages of low cost and high precision,which is very suitable for obtaining high-resolution images. This paper took Metasequoia glyptostroboides forest in Qingshan Lake scenic spot,Lin'an District,Hangzhou as the research object,used UAV to obtain remote sensing images with different flight heights and different canopy density as the data source,and extracted the average crown width based on object-oriented method. Taking the average crown width measured on the ground as a reference,under the condition of relatively low canopy density,when the flight altitude were 65m,70m and 75m,the crown extraction accuracy were 95.39%,94.80% and 94.29% respectively. Under the condition of relatively high canopy density,the extraction accuracy of crown width were 89.10%,88.10% and 88.03% respectively. The results showed that within the research range,with the increase of UAV height,the accuracy of crown width extraction gradually decreased,and it was also applicable in two different canopy closures,which was more than 88% in two models. This method is efficient and reliable,and has important practical significance in forest resources investigation.