【摘要】 针对以往无人机遥感用于城市植被分类时多利用影像光谱、纹理和形状等特征,影像重建点云数据未能充分利用的问题,提出一种综合影像重建点云与光谱信息的城市植被分类方法。首先,基于运动恢复结构(structure from motion,SFM)、多视图聚簇(cluster multi view stereo,CMVS)和基于面片模型的密集匹配(patch based multi view stereo,PMVS)算法重建研究区密集点云;然后,经滤波、插值生成研究区数字高程模型(digital elevation model,DEM)和归一化数字表面模型(normalized digital surface model,n DSM),同时结合影像光谱信息对不同高度的城市植被进行分类提取;最后,采用面向对象的影像分析方法,根据n DSM信息与归一化绿红差异指数(normalized greenred difference index,NGRDI)及可见光波段差异植被指数(visible-band difference vegetation index,VDVI)等光谱信息,分别建立了水生植被、草地、灌木、小乔木和乔木等不同植被的分类规则。实验结果表明综合利用影像重建点云得到的n DSM信息与影像光谱信息提取不同高度的植被是可行的,总体分类精度达到92. 08%。该方法可为城市植被分类与制图提供理论支持和应用参考。更多还原

【Abstract】 In order to solve the problem that unmanned aerial vehicle(UAV) remote sensing for urban vegetation classification usually uses the spectral texture and shape features information,while the reconstruction point cloud data of image fail to be fully used,the authors put forward a new method of comprehensive reconstruction point cloud and spectral information of image to extract the vegetation.The dense cloud of the study area was reconstructed based on structure from motion(SFM),cluster multi view stereo(CMVS) and patch based multi view stereo(PMVS) algorithm,and the digital elevation model(DEM) and normalized digital surface model(n DSM)of the study area were generated based on filtering and interpolation,meanwhile in combination with the spectral information of image the urban vegetation with different heights was extracted.On the basis of object-oriented image analysis method in combination with the nDSM information and spectral information including normalized green-red difference index and visible-band difference vegetation index,the classification rules of different vegetation,such as aquatic vegetation,grassland,shrub,small tree,and tree,were established.The experimental results show that the integration of the nDSM from point cloud data of image and spectral information to extract the vegetation with different heights is feasible,and the overall classification accuracy is 92.08%.The results obtained by the authors can provide theoretical support and application reference for urban vegetation classification and mapping.更多还原