Wang Juan, Zhang Chao, Chen Qiao, Li Huayu, Peng Xi, Bai Mingxiong, Xu Zhiyang, Liu Haodong, Chen Yongfu. The Method of Extracting Information of Cunninghamia lanceolata Crown Combined with RGB and LiDAR Based on UAV[J]. Journal of Southwest Forestry University, 2022, 42(1): 133-141. DOI: 10.11929/j.swfu.202101013
Citation: Wang Juan, Zhang Chao, Chen Qiao, Li Huayu, Peng Xi, Bai Mingxiong, Xu Zhiyang, Liu Haodong, Chen Yongfu. The Method of Extracting Information of Cunninghamia lanceolata Crown Combined with RGB and LiDAR Based on UAV[J]. Journal of Southwest Forestry University, 2022, 42(1): 133-141. DOI: 10.11929/j.swfu.202101013

The Method of Extracting Information of Cunninghamia lanceolata Crown Combined with RGB and LiDAR Based on UAV

More Information
  • Received Date: January 06, 2021
  • Revised Date: July 04, 2021
  • Available Online: November 01, 2021
  • Published Date: January 19, 2022
  • With the Nianzhu forest field as the research area, the visible light image and lidar data of UAV were used as the data source, and the watershed segmentation algorithm and object-oriented method were used to extract single tree crown width information in different forest canopy densities and verify the extraction accuracy. First, tree crown was extracted from visible light image using object-oriented method which was to extract the canopy tree crown range. Then, the watershed segmentation method was used to obtain the preliminary segmentation results of single tree crown based on CHM. Finally, divided again to extract the information of single tree crown based on the preliminary segmentation boundary and crown area. The results of show that the extraction effect of individual tree crown and area is better in different density. The F-measure was between 88.07%–95.08% and 78.57%–88.29%; and a linear regression model was established between extracted crown area and the measured crown area, the R2 were 0.8591 and 0.7367 and RMSE were 2.49m² and 3.29m². A linear regression model was established between extracted crown diameter and the measured crown diameter, the R2 were 0.8306 and 0.7246, RMSE of which were 0.46 m and 0.57 m. Based on the visible light image of the UAV, the tree crown area extracted by object-oriented multi-scale segmentation method has eliminated the influence of naked and shrub in the forest. At the same time, the UAV-LiDAR data can accurately distinguish individual tree. The combination of the 2 data sources can take advantages of both and improves the extraction accuracy of single tree crown. This study can provide a reference for quickly obtaining individual tree crown information under different canopy density stands.
  • 张思玉, 胥辉. 树冠中的黄金分割初步探析 [J]. 西南林学院学报, 2001, 21(1): 14−19.
    李增元, 刘清旺, 庞勇. 激光雷达森林参数反演研究进展 [J]. 遥感学报, 2016, 20(5): 1138−1150.
    郭庆华, 吴芳芳, 胡天宇, 等. 无人机在生物多样性遥感监测中的应用现状与展望 [J]. 生物多样性, 2016, 24(11): 1267−1278. DOI: 10.17520/biods.2016105
    Yu X W, Hyyppä J, Vastaranta M, et al. Predicting individual tree attributes from airborne laser point clouds based on the random forests technique [J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2011, 66(1): 28−37. DOI: 10.1016/j.isprsjprs.2010.08.003
    Popescu S C. Estimating biomass of individual pine trees using airborne lidar [J]. Biomass and Bioenergy, 2007, 31(9): 646−655. DOI: 10.1016/j.biombioe.2007.06.022
    全迎, 李明泽, 甄贞, 等. 运用无人机激光雷达数据提取落叶松树冠特征因子及树冠轮廓模拟 [J]. 东北林业大学学报, 2019, 47(11): 52−58. DOI: 10.3969/j.issn.1000-5382.2019.11.011
    Chen Q, Baldocchi D, Gong P, et al. Isolating individual trees in a savanna woodland using small footprint lidar data [J]. Photogrammetric Engineering & Remote Sensing, 2006, 72(8): 923−932.
    李岩, 史泽林, 程坤, 等. 运用激光雷达数据的单木树冠提取算法对帽儿山林场单木参数估测的影响 [J]. 东北林业大学学报, 2019, 47(11): 59−65. DOI: 10.3969/j.issn.1000-5382.2019.11.012
    Culvenor D S. TIDA: an algorithm for the delineation of tree crowns in high spatial resolution remotely sensed imagery [J]. Computers & Geosciences, 2002, 28(1): 33−44.
    Hung C, Bryson M, Sukkarieh S. Multi-class predictive template for tree crown detection [J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2012, 68: 170−183. DOI: 10.1016/j.isprsjprs.2012.01.009
    施慧慧, 王妮, 滕文秀, 等. 结合Gabor小波和形态学的高分辨率图像树冠提取方法 [J]. 地球信息科学学报, 2019, 21(2): 249−258. DOI: 10.12082/dqxxkx.2019.180280
    李丹, 张俊杰, 赵梦溪. 基于FCM和分水岭算法的无人机影像中林分因子提取 [J]. 林业科学, 2019, 55(5): 180−187. DOI: 10.11707/j.1001-7488.20190520
    Mu Y, Fujii Y, Takata D, et al. Characterization of peach tree crown by using high-resolution images from an unmanned aerial vehicle [J]. Horticulture Research, 2018, 5: 74. DOI: 10.1038/s41438-018-0097-z
    Kang J, Wang L, Chen F, et al. Identifying tree crown areas in undulating Eucalyptus plantations using JSEG multi-scale segmentation and unmanned aerial vehicle near-infrared imagery [J]. International Journal of Remote Sensing, 2017, 38(8/9/10): 2296−2312.
    董新宇, 李家国, 陈瀚阅, 等. 无人机遥感影像林地单株立木信息提取 [J]. 遥感学报, 2019, 23(6): 1269−1280.
    Gougeon F A. A crown-following approach to the automatic delineation of individual tree crowns in high spatial resolution aerial images [J]. Canadian Journal of Remote Sensing, 1995, 21(3): 274−284. DOI: 10.1080/07038992.1995.10874622
    孙钊, 潘磊, 孙玉军. 基于无人机影像的高郁闭度杉木纯林树冠参数提取 [J]. 北京林业大学学报, 2020, 42(10): 20−26.
    赵勋, 岳彩荣, 李春干, 等. 基于DOM航空影像单木树冠提取 [J]. 西北林学院学报, 2020, 35(2): 160−168. DOI: 10.3969/j.issn.1001-7461.2020.02.24
    毛学刚, 陈文曲, 魏晶昱, 等. 分割尺度对面向对象树种分类的影响及评价 [J]. 林业科学, 2017, 53(12): 73−83. DOI: 10.11707/j.1001-7488.20171208
    郑鑫, 王瑞瑞, 靳茗茗. 基于形态学阈值标记分水岭算法的高分辨率影像单木树冠提取 [J]. 中南林业调查规划, 2017, 36(4): 30−35, 57.
    曾霞辉, 王颖, 曾掌权, 等. 无人机影像树冠信息提取研究 [J]. 中南林业科技大学学报, 2020, 40(8): 75−82.
    郭昱杉, 刘庆生, 刘高焕, 等. 基于标记控制分水岭分割方法的高分辨率遥感影像单木树冠提取 [J]. 地球信息科学学报, 2016, 18(9): 1259−1266.
    杨立岩. 多平台多源遥感测树因子提取技术与方法研究[D]. 北京: 北京林业大学, 2018.

Catalog

    Article views (858) PDF downloads (34) Cited by()

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return