文献类型：期刊文献

中文题名：结合可见光植被指数和分水岭算法的单木树冠信息提取

英文题名：Extraction of Individual Tree Crown based on UAV Tilt Photogrammetry

作者：陈树新[1] 刘炳杰[2] 王海熠[1] 苏勇[1,3] 艾遒一[2] 田昕[1]

第一作者：陈树新

机构：[1]中国林业科学研究院资源信息研究所,北京100091;[2]北京林业大学森林资源和环境管理国家林草局重点实验室,北京100083;[3]西南林业大学林学院,云南昆明650224

年份：2024

卷号：39

期号：1

起止页码：34-44

中文期刊名：遥感技术与应用

外文期刊名：Remote Sensing Technology and Application

收录：CSTPCD;;北大核心:【北大核心2023】；CSCD:【CSCD2023_2024】；

基金：中国林业科学研究院中央级公益性科研院所基本科研业务费专项资金项目“森林资源出数关键技术研究”(CAFYBB2021SY006);高分辨率对地观测系统重大专项“高分森林资源调查应用子系统(二期)”(21-Y30B02-9001-19/22-1)。

语种：中文

中文关键词：倾斜摄影;单木树冠;可见光植被指数;阈值分割;分水岭分割

外文关键词：Tilt photogrammetry;Individual tree crown;Visible vegetation index;Threshold segmentation;Watershed segmentation

分类号：TP79

摘要：相比于传统的人工实地调查的方法,通过无人机倾斜摄影测量技术多角度拍摄提取单木树冠信息,具有高效、准确和低成本等优势。以内蒙古自治区赤峰市喀喇沁旗西南部旺业甸林场的落叶松近成熟林为研究对象,以倾斜摄影测量技术获取的无人机影像为数据源,提出一种结合可见光植被指数和分水岭算法的单木冠幅提取方法。首先通过数字正射影像计算可见光波段超绿超红差分指数;选择合理阈值对图像进行二值化,并利用中值滤波对树冠区域图进行去噪处理,分离出植被与非植被区域;以植被区域为掩膜范围对冠层高度模型进行掩膜;最后,利用分水岭分割算法提取单木树冠进行精度验证。在树冠区域提取过程中,基于超绿超红差分指数结合阈值法成功分离出植被与非植被区域;通过中值滤波有效地去除了因亮度不均、阴影及非植被区域的纹理等信息所造成的斑点和噪声,保证了树冠边缘的完整性及树冠内部的连通性,同时减少了分水岭算法的过分割现象。单木尺度上,树冠参数信息提取的准确率分别为88.72%和79.38%,召回率分别为93.29%和88.60%,F测度分别为90.59%和83.74%;样地尺度上,相对误差分别为15.45%和22.92%。研究结果表明:基于数字正射影像采用可见光植被指数提取植被区域很好地消除了林内裸地等背景因素的影响,同时基于冠层高度模型利用分水岭分割算法能够精确的区分单木信息。基于无人机倾斜摄影测量技术得到的两种数据源结合发挥了各自的优势,能够高效、准确地提取较高郁闭度林分的单木树冠信息。
Compared with the traditional manual field survey method,the use of UAV tilt photogrammetry tech-nology for multiangle photography to extract individual tree crown information has the advantages of high effi-ciency,accuracy and low cost.In this study,an individual tree crown extraction method combined with a visible vegetation index and watershed algorithm was proposed by taking a larch near-mature forest in the Wangyedian forest farm in southwestern Karaqin Banner,Chifeng city,Inner Mongolia,as the research object and using UAV images obtained by tilt photogrammetry as the data source.First,the Excess Green minus Excess Red(ExGR)in the visible light band was calculated by a digital orthophoto model.The median filter was used to de-noise the tree crown area map,and a reasonable threshold was selected to binarize the image to separate the veg-etation and non-vegetation areas.Vegetation areas were used to mask the canopy height model.Finally,the ac-curacy of individual tree crowns was verified by the watershed segmentation algorithm.In the process of extract-ing the crown area,vegetation and non-vegetation areas are successfully separated based on the ExGR index and threshold method.Through median filtering,speckle and noise caused by uneven brightness,shadow and texture in the non-vegetation area are effectively removed,the integrity of the crown edge and the connectivity of the crown are ensured,and the over segmentation phenomenon of the watershed algorithm is reduced.At the individual tree scale,the accuracy rate of crown parameter information extraction was 88.72%and 79.38%,the recall rate was 93.29%and 88.60%,and the F-score was 90.59%and 83.74%.On the sample plot scale,the relative errors are 15.45%and 22.92%respectively.The results show that the visible vegetation index based on Digital Orthophoto Image can effectively eliminate the influence of bare land and other background factors in the forest,and the watershed segmentation algorithm based on the canopy height model can accurately distinguish individual tree information.The combination of the two data sources based on the UAV tilt photogrammetry technology gives full play to their respective advantages.The method of extracting the single tree crown informa-tion based on the UAV tilt photogrammetry technology is feasible and can extract the single tree crown informa-tion of the forest with high canopy density efficiently and accurately.