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Yu Donghai, Feng Zhongke. Tree crown volume measurement method based on oblique aerial images of UAV[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2019, 35(1): 90-97. DOI: 10.11975/j.issn.1002-6819.2019.01.011
Citation: Yu Donghai, Feng Zhongke. Tree crown volume measurement method based on oblique aerial images of UAV[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2019, 35(1): 90-97. DOI: 10.11975/j.issn.1002-6819.2019.01.011

Tree crown volume measurement method based on oblique aerial images of UAV

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  • Received Date: July 16, 2018
  • Revised Date: November 18, 2018
  • Published Date: December 31, 2018
  • Abstract: Tree crown volume is an important basis for monitoring tree growth and estimating tree biomass. Accurate measurement of tree crown volume has always been a difficult issue in forest measurement research. Traditional method of estimating tree crown volume is to bring crown breadth and tree height measurements to inherent empirical models, but it's faced with problems such as rough operation mode and no precision guarantee of measurement results. In recent years, the emergence of the modern equipments and technologies lay the foundation to achieve high precision tree crown volume measurements. Unmanned aerial vehicle (UAV) oblique aerial photography technology with high-resolution images changes traditional measurement ways, which can use oblique aerial images to generate point cloud data and extract different types of tree geometry parameters by point cloud information. In this paper, a consumer-level multi-rotor UAV named DJI Inspire-1 was used as data acquisition platform, which was equipped with RGB band of ordinary digital camera named Zenmuse-X3. In the Beijing Jiufeng Forest Farm, comprehensively considering the flight operating conditions of the UAV and tree size specifications, we selected eight target trees with different types and sizes. Using the UAV in the manner of spiral flying, we obtained multi-angle oblique aerial images of these target trees. During operation, the main remote controllor controlled the flight status of the UAV and the auxiliary remote controllor controlled the status of the camera haeundae. These two were operated at the same time to collect the oblique aerial images. The following points were the schemes for collecting UAV data: a) In the case of ensuring a safe distance, taking the trunk of the target tree as the center for low-speed flight photography. b) Adjusting the camera pose in real-time during the hovering process so that making sure obtain images of the target tree at different positions and angles. c) Ensuring the overlapping rate of adjacent images collected at the same height exceeded 90%, and the overlapping rate of images collected at different height exceeded 60%. The acquired images were processed through the principle of aerial triangulation for generating three-dimensional point cloud models of target trees. Based on three-dimensional point cloud models, the research segmented the tree crown point cloud by contour lines method and determined the optimal segment number of tree crown point cloud. To extract tree measurement factors, projection method was used to reduce the dimension of the point cloud data. And the measured values of tree height and the arbitrary cross-sectional area of tree crown were calculated by using the key points. According to the established algorithm, the measured volume of the entire tree crown was calculated by accumulating the volume of each rule body after segmentation. Taking actual values by total station as reference, the accuracy of the tree height and tree crown volume measurement results was examined. The results showed that it was a feasible and effective method that the oblique aerial images of UAV were used to establish the three-dimensional point cloud models of single trees and to calculate the tree crown volume. In addition, the average relative error of tree height and tree crown volume of eight target trees was 2.88% and 9.42%, respectively. The accuracy met the standard for tree height and tree crown volume measurement resulted in forestry surveys. In conclusion, three-dimensional point cloud models generated by oblique aerial images of multi-rotor UAV can realize the extraction of measurement factors of single trees, which could be applied to the investigation and protection of ancient and famous trees. This method provides a new approach for the extraction of single trees geometry parameters.
  • [1]
    闫飞. 森林资源调查技术与方法研究[D]. 北京:北京林业大学,2014.Yan Fei. Research of Technology and Methord of Forest Resource Inventory[D]. Beijing: Beijing Forestry University, 2014. (in Chinese with English abstract)
    [2]
    何诚,冯仲科,袁进军,等. 基于数字高程模型的树木三维体积测量[J]. 农业工程学报,2012,28(8):195-199.He Cheng, Feng Zhongke, Yuan Jinjun, et al. Three- dimensional volume measurement of trees based on digital elevation model[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2012, 28(8): 195-199. (in Chinese with English abstract)
    [3]
    冯仲科,黄晓东,刘芳. 森林调查装备与信息化技术发展分析[J]. 农业机械学报,2015,46(9):257-265.Feng Zhongke, Huang Xiaodong, Liu Fang. Forest survey equipment and development of information technology[J]. Transactions of the Chinese Society for Agricultural Machinery, 2015, 46(9): 257-265. (in Chinese with English abstract)
    [4]
    赵芳,冯仲科,高祥,等. 树冠遮挡条件下全站仪测量树高及材积方法[J]. 农业工程学报,2014,30(2):182-190.Zhao Fang, Feng Zhongke, Gao Xiang, et al. Measure method of tree height and volume using total station under canopy cover condition[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactionsof the CSAE), 2014, 30(2): 182-190. (in Chinese with English abstract)
    [5]
    焦有权,冯仲科,赵礼曦,等. PSO嵌入SVM算法的活立木材积预报研究[J]. 光谱学与光谱分析,2014,34(1):175-179.Jiao Youquan, Feng Zhongke, Zhao Lixi, et al. Research on living tree volume forecast based on PSO embedding SVM[J]. Spectroscopy and Spectral Analysis, 2014, 34(1): 175-179. (in Chinese with English abstract)
    [6]
    于东海,冯仲科,曹忠,等. 全站仪测量立木胸径树高及材积的误差分析[J]. 农业工程学报,2016,32(17):160-167.Yu Donghai, Feng Zhongke, Cao Zhong, et al. Error analysis of measuring diameter at breast height and tree height and volume of standing tree by total station[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2016, 32(17): 160-167. (in Chinese with English abstract)
    [7]
    吴明钦,孙玉军,郭孝玉,等. 长白落叶松树冠体积和表面积模型[J]. 东北林业大学学报,2014,42(5):1-5.Wu Mingqin, Sun Yujun, Guo Xiaoyu, et al. Predictive models of crown volume and crown surface area for Korean Larch[J]. Journal of Northeast Forestry University, 2014, 42(5): 1-5. (in Chinese with English abstract)
    [8]
    Hildebrandt R, Iost A. From points to numbers: A database-driven approach to convert terrestrial LiDAR point clouds to tree volumes[J]. European Journal of Forest Research, 2012, 131(6): 1857-1867.
    [9]
    刘鲁霞,庞勇,李增元,等. 用地基激光雷达提取单木结构参数:以白皮松为例[J]. 遥感学报,2014,18(2):365-377.Liu Luxia, Pang Yong, Li Zengyuan, et al. Retrieving structural parameters of individual tree through terrestrial laser scanning data[J]. Journal of Remote Sensing, 2014, 18(2): 365-377. (in Chinese with English abstract)
    [10]
    Asner G P, Knapp D E, Boardman J, et al. Carnegie Airborne Observatory-2: Increasing science data dimensionality via high-fidelity multi-sensor fusion[J]. Remote Sensing of Environment, 2012, 124: 454-465. doi:10.1016/j.rse.2012. 06.012
    [11]
    Zhen Z, Quackenbush L, Zhang L. Trends in automatic individual tree crown detection and delineation-evolution of LiDAR data[J]. Remote Sensing, 2016, 8(4): 333. doi:10. 3390/rs8040333
    [12]
    徐伟恒,冯仲科,苏志芳,等. 一种基于三维激光点云数据的单木树冠投影面积和树冠体积自动提取算法[J]. 光谱学与光谱分析,2014,34(2):465-471.Xu Weiheng, Feng Zhongke, Su Zhifang, et al. An automactic extraction algorithm for indvidual tree crown projection area and volume based on 3D point cloud data[J]. Spectroscopy and Spectral Analysis, 2014, 34(2): 465-471. (in Chinese with English abstract)
    [13]
    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.Li Zengyuan, Liu Qingwang, Pang Yong. Review on forest parameters inversion using LiDAR[J]. Journal of Remote Sensing, 2016, 20(5): 1138-1150. (in Chinese with English abstract)
    [14]
    郭彩玲,宗泽,张雪,等. 基于三维点云数据的苹果树冠层几何参数获取[J]. 农业工程学报,2017,33(3):175-181.Guo Cailing, Zong Ze, Zhang Xue, et al. Apple tree canopy geometric parameters acquirement based on 3D point clouds[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2017, 33(3): 175-181. (in Chinese with English abstract)
    [15]
    王佳,张芳菲,高赫,等. 地基激光雷达提取单木冠层结构因子研究[J]. 农业机械学报,2018,49(2):199-206.Wang Jia, Zhang Fangfei, Gao He, et al. Extracting crown structure parameters of individual tree by using Ground- based Laser Scanner[J]. Transactions of the Chinese Society for Agricultural Machinery, 2018, 49(2): 199-206. (in Chinese with English abstract)
    [16]
    谢鸿宇,赵耀龙,杨木壮,等. 基于无棱镜全站仪的树冠体积算法[J].中南林业科技大学学报,2014,34(1):12-17.Xie Hongyu, Zhao Yaolong, Yang Muzhuang, et al. Tree crown volume algorithm based on non-prism total station[J]. Journal of Central South University of Forestry & Technology, 2014, 34(1): 12-17. (in Chinese with English abstract)
    [17]
    李德仁,李明. 无人机遥感系统的研究进展与应用前景[J]. 武汉大学学报:信息科学版,2014,39(5):505-513,540.Li Deren, Li Ming. Research advance and application prospect of unmanned aerial vehicle remote sensing system[J]. Geomatics and Information Science of Wuhan University, 2014, 39(5): 505-513, 540. (in Chinese with English abstract)
    [18]
    Zarco-Tejada P J, Diaz-Varela R, Angileri V, et al. Tree height quantification using very high resolution imagery acquired from an unmanned aerial vehicle (UAV) and automatic 3D photo-reconstruction methods[J]. European Journal of Agronomy, 2014, 55: 89-99. doi:10.1016/ j.eja.2014.01.004
    [19]
    刘清旺,李世明,李增元,等. 无人机激光雷达与摄影测量林业应用研究进展[J]. 林业科学,2017,53(7):134-148.Liu Qingwang, Li Shiming, Li Zengyuan, et al. Review on the applications of UAV-based LiDAR and Photogrammetry in forestry[J]. Scientia Silvae Sinicae, 2017, 53(7): 134-148. (in Chinese with English abstract)
    [20]
    Gatziolis D, Lienard J, Vogs A, et al. 3D tree dimensionality assessment using photogrammetry and small unmanned aerial vehicles[J]. PLOS ONE, 2015, 10(9). doi:10.1371/journal. pone.0137765
    [21]
    Gaetano R, Masi G, Poggi G, et al. Marker-controlled watershed-based segmentation of multiresolution remote sensing images[J]. IEEE Transactions on Geoscience&Remote Sensing, 2015, 53(6): 2987-3004.
    [22]
    陈崇成,李旭,黄洪宇. 基于无人机影像匹配点云的苗圃单木冠层三维分割[J]. 农业机械学报,2018,49(2):149-155,206.Chen Chongcheng, Li Xu, Huang Hongyu. 3D segmentation of individual tree canopy in forest nursery based on drone image-matching point cloud[J]. Transactions of the Chinese Society for Agricultural Machinery, 2018, 49(2): 149-155, 206. (in Chinesewith English abstract)
    [23]
    Zahawi R A, Dandois J P, Holl K D, et al. Using lightweight unmanned aerial vehicles to monitor tropical forest recovery[J]. Biological Conservation, 2015, 186: 287-295. doi: 10.1016/j.biocon.2015.03.031
    [24]
    史洁青,冯仲科,刘金成. 基于无人机遥感影像的高精度森林资源调查系统设计与试验[J]. 农业工程学报,2017,33(11):82-90.Shi Jieqing, Feng Zhongke, Liu Jincheng. Design and experiment of high precision forest resource investigation system based on UAV remote sensing images[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2017, 33(11): 82-90. (in Chinese with English abstract)
    [25]
    刘文萍,仲亭玉,宋以宁. 基于无人机图像分析的树木胸径预测[J]. 农业工程学报,2017,33(21):99-104.Liu Wenping, Zhong Tingyu, Song Yining. Prediction of trees diameter at breast height based on unmanned aerial vehicle image analysis[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2017, 33(21): 99-104.(in Chinese with English abstract)
    [26]
    Puliti S, Orka H O, Gobakken T, et al. Inventory of small forest areas using an unmanned aerial system[J]. Remote Sensing, 2015, 7(8): 9632-9654.
    [27]
    Kachamba D, Orka H O, Gobakken T, et al. Biomass estimation using 3D data from unmanned aerial vehicle imagery in a tropical woodland[J]. Remote Sensing, 2016, 8(11): 968. doi: 10.3390/rs8110968
    [28]
    何游云,张玉波,李俊清,等. 利用无人机遥感测定岷江冷杉单木树干生物量[J]. 北京林业大学学报, 2016,38(5):42-49.He Youyun, Zhang Yubo, Li Junqing, et al. Estimation of stem biomass of individual Abies faxoniana through unmanned aerial vehicle remote sensing[J]. Journal of Beijing Forestry University, 2016, 38(5): 42-49. (in Chinese with English abstract)
    [29]
    国家林业局. 国家森林资源连续清查技术规定[S/OL]. 2014: 40-41. https://wenku.baidu.com/view/e0b332884bfe 04a1b0717fd5360cba1aa9118c35.html
    [30]
    冯仲科,何诚,姚山,等. 一种基于高程等值线法量测树冠体积的方法:201110164615.4[P]. 2011-11-23.
    [31]
    同济大学数学系. 高等数学(下册) [M]. 第六版. 北京:高等教育出版社,2007:132-135.
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