文献类型：期刊文献

英文题名：Improving Measurement of Forest Structural Parameters by Co-Registering of High Resolution Aerial Imagery and Low Density LiDAR Data

作者：Huang, Huabing[1,2] Gong, Peng[1,2,3] Cheng, Xiao[1,2] Clinton, Nick[1,2] Li, Zengyuan[1,2,4]

第一作者：Huang, Huabing

通信作者：Gong, P[1]

机构：[1]Chinese Acad Sci, State Key Lab Remote Sensing Sci, Inst Remote Sensing Applicat, Beijing 100101, Peoples R China;[2]Beijing Normal Univ, Beijing 100101, Peoples R China;[3]Univ Calif Berkeley, Div Ecosyst Sci, Berkeley, CA 94720 USA;[4]Chinese Acad Forestry, Inst Forest Resources Informat Technol, Beijing 100091, Peoples R China

年份：2009

卷号：9

期号：3

起止页码：1541-1558

外文期刊名：SENSORS

收录：;EI(收录号：20131816278834);Scopus(收录号：2-s2.0-63849173912);WOS:【SCI-EXPANDED(收录号:WOS:000264572700018)】；

基金：This work was supported by a Key Project of Knowledge Innovation Program of the Chinese Academy of Sciences (KZCX2-YW-313), an NSFC grant (40671125) and Youth Scientists Project of State Key Laboratory of Remote Sensing Science. The research data was provided by General Technology Research on Remote Sensing Applications Demonstration Project and Local Demonstration of Remote Sensing Applications.

语种：英文

外文关键词：LiDAR; Aerial image; Forest structural parameters extraction

摘要：Forest structural parameters, such as tree height and crown width, are indispensable for evaluating forest biomass or forest volume. LiDAR is a revolutionary technology for measurement of forest structural parameters, however, the accuracy of crown width extraction is not satisfactory when using a low density LiDAR, especially in high canopy cover forest. We used high resolution aerial imagery with a low density LiDAR system to overcome this shortcoming. A morphological filtering was used to generate a DEM (Digital Elevation Model) and a CHM (Canopy Height Model) from LiDAR data. The LiDAR camera image is matched to the aerial image with an automated keypoints search algorithm. As a result, a high registration accuracy of 0.5 pixels was obtained. A local maximum filter, watershed segmentation, and object-oriented image segmentation are used to obtain tree height and crown width. Results indicate that the camera data collected by the integrated LiDAR system plays an important role in registration with aerial imagery. The synthesis with aerial imagery increases the accuracy of forest structural parameter extraction when compared to only using the low density LiDAR data.