基于无人机遥感的云南松林冠参数提取研究  

Parameter Extraction of Pinus yunnanensis Canopy Based on UAV Remote Sensing

作　　者：杨安蓉 张超 YANG An-rong;ZHANG Chao(Southwest Forestry University,Kunming 650224,Yunnan,China)

机构地区：[1]西南林业大学林学院,云南昆明650224

出　　处：《西北林学院学报》2024年第1期1-9,共9页Journal of Northwest Forestry University

基　　金：国家自然科学基金(32160405);云南省“万人计划”人才培养项目(YNWR-QNBJ-2018-334)。

摘　　要：以滇中地区典型天然云南松纯林为对象,结合无人机遥感影像获取和外业标准地调查,利用传统目视解译、多尺度分割和分水岭分割方法进行单木冠幅和郁闭度2个林冠参数的提取研究。结果表明,以地面实测数据为参考,3种单木分割方法的冠幅提取精度分别达91.48%、87.33%、84.04%;以目视解译结果为参考,多尺度分割方法提取郁闭度的精度达90.24%,且决定系数(R2)达0.8845;分水岭分割方法提取郁闭度的精度达87.40%,R2达0.7437。研究结果表明,基于无人机遥感影像的多尺度分割方法能很好地提取云南松纯林的林冠参数信息,且提取精度满足森林资源调查的要求,可有效提高森林资源调查的效率。Taking the typical natural Pinus yunnanensis pure forest in central Yunnan as the research object,combined with unmanned aerial vehicle(UAV)remote sensing image acquisition and field standard survey,the traditional visual interpretation,multi-scale segmentation and watershed segmentation methods were used to extract the two canopy parameters of single tree crown and canopy density.Based on the ground measured data,the rates of crown extraction accuracy of the three single tree segmentation methods were 91.48%,87.33%and 84.04%,respectively.Taking the visual interpretation results as a reference,the accuracy of multi-scale segmentation method to extract canopy density was 90.24%,and R2 was 0.8845.The accuracy of canopy density extracted by watershed segmentation method was 87.40%,and R2 was 0.7437.The results indicate that the multi-scale segmentation method based on UAV remote sensing image can extract the canopy parameter information of P.yunnanensis pure forest well,and the extraction accuracy meets the requirements of forest resource survey,which can effectively improve the efficiency of forest resource survey.

关 键 词：林冠参数 无人机遥感 目视解译 多尺度分割 分水岭分割 云南松 

分 类 号：S757.257[农业科学—森林经理学]