激光与光电子学进展, 2018, 55 (8): 082805, 网络出版: 2018-08-13   

机载激光雷达单木识别研究进展 下载: 753次

Review on Individual Tree Detection Based on Airborne LiDAR
作者单位
1 北京林业大学林学院, 北京 100083
2 北京林业大学精准林业北京市重点实验室, 北京 100083
3 北京林业大学省部共建培育与保护重点实验室, 北京 100083
4 中国海监南海航空支队, 广东 广州 510310
5 北京鼎创力维科技有限公司, 北京 100083
摘要
随着激光雷达的发展,基于机载激光雷达提取单木及林分参数是目前的研究热点之一。准确的单木识别是后续林木参数提取的重要基础。机载激光雷达单木识别方法可以分为基于冠层高度模型(CHM)的单木识别法和基于点云分布的单木识别法两类。基于CHM的单木识别方法通过CHM分割确定树冠边界或通过局部最大值识别树冠顶点并且进行区域生长或图像分割。基于点云分布的单木识别法在三维空间上采用区域生长或聚类算法识别树冠。分析不同方法在单木识别中的优缺点,对比不同单木识别法对单木识别精度、欠分割误差、过分割误差的影响。分析数据类型、点云密度、季节和林木生长状况等多个影响识别精度的因素,分析可得全波形数据优于离散回波识别精度,点云数据密度10 pt/m2即可满足单木识别要求,冬季识别精度优于夏季识别精度。探讨机载激光雷达数据的局限性及其在单木识别中的缺陷,从数据获取时间、获取方式及类型、数据组织管理、多源数据融合、多种识别算法综合应用、机器学习增加训练集寻找最优模型等方面展望了未来单木识别的发展方向,拓宽我国森林资源调查及相关领域的研究思路。
Abstract
As light detection and ranging (LiDAR) develops, the extraction of forest structure parameters has been one of hot topics in related fields in the past years. However, the accuracy of detection is the key factor in obtaining the forest individual tree parameters. The individual tree detection methods can be divided to two types: one is based on the canopy height model (CHM) and the other is based on the point cloud distribution. We can identify an individual tree by using the method of the crown boundary segmentation. Also, we can identify the tree top by local maximum algorithms and then perform the regional growth or image segmentation. Based on the point cloud distribution, the canopy is identified by region growing or clustering algorithms in three-dimensional space. We analyze the advantages and disadvantages of different individual tree detection methods in terms of precision of individual tree detection, and compare their effects on omission errors and commission errors in different regions. The factors influencing the precision of data such as data type, point cloud density, season and tree growth status are discussed. It is found that the accuracy of the full-waveform data is higher than that of discrete-echo data. The density of the point cloud data of 10 pt/m2 can meet the individual tree detection requirement. The accuracy of data obtained in winter is higher than that in summer. The limitation of airborne LiDAR data and its shortcomings in individual tree detection are discussed. In the end, the future directions of individual tree detection are described, from the aspects of data acquisition type, data acquisition time, data organization and management, multi-source data fusion, comprehensive application of multi-detection algorithms, and machine learning increasing the training set to find the optimal model, to help with the research and management of forest and related fields.
参考文献

[1] 唐菲菲, 阮志敏, 刘星, 等. 基于机载激光雷达数据识别单株木的新方法[J]. 遥感技术与应用, 2011, 26(2): 196-201.

    Tang F F, Ruan Z M, Liu X, et al. A new method of individual tree recognition based on airborne LiDAR data[J]. Remote Sensing Technology and Application, 2011, 26(2): 196-201.

[2] 刘峰, 龚健雅. 基于机载激光雷达技术的茂密林地单株木识别[J]. 农业机械学报, 2011, 42(7): 200-203.

    Liu F, Gong J Y. Individual trees recognition in dense forest based on airborne LiDAR[J]. Transactions of the Chinese Society for Agricultural Machinery, 2011, 42(7): 200-203.

[3] Lefsky M A, Cohen W B, Parker G G, et al. Lidar remote sensing for ecosystem studies: lidar, an emerging remote sensing technology that directly measures the three-dimensional distribution of plant canopies, can accurately estimate vegetation structural attributes and should be of particular interest to forest, landscape, and global ecologists[J]. BioScience, 2002, 52(1): 19-30.

[4] Popescu S C. Estimating biomass of individual pine trees using airborne lidar[J]. Biomass and Bioenergy, 2007, 31(9): 646-655.

[5] Pang Y, Tan B, Solberg S, et al. Forest LAI estimation comparison using liDAR and hyperspectral data in boreal and temperate forests[J]. Proceedings of SPIE, 2009, 7454: 745490.

[6] Sheridan R, Popescu S, Gatziolis D, et al. Modeling forest aboveground biomass and volume using airborne LiDAR metrics and forest inventory and analysis data in the Pacific Northwest[J]. Remote Sensing, 2014, 7(1): 229-255.

[7] Koukoulas S, Blackburn G A. Quantifying the spatial properties of forest canopy gaps using LiDAR imagery and GIS[J]. International Journal of Remote Sensing, 2004, 25(15): 3049-3072.

[8] MacMillan R A, Martin T C, Earle T J, et al.Automated analysis and classification of landforms using high-resolution digital elevation data: applications and issues[J]. Canadian Journal of Remote Sensing, 2014, 29(5): 592-606.

[9] Ben-Arie J R, Hay G J, Powers R P, et al. Development of a pit filling algorithm for LiDAR canopy height models[J]. Computers & Geosciences, 2009, 35(9): 1940-1949.

[10] 赵旦. 基于激光雷达和高光谱遥感的森林单木关键参数提取[D]. 北京: 中国林业科学研究院, 2012.

    Zhao D. Individual tree parameters extraction based on liDAR and hyper-spectrum data[D]. Beijing: Chinese Academy of Forestry, 2012.

[11] 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 Z Y, Liu Q W, Pang Y. Review on forest parameters inversion using lidar[J]. Journal of Remote Sensing, 2016, 20(5): 1138-1150.

[12] Popescu S C. Seeing the trees in the forest: using liDAR and multispectral data fusion with local filtering and variable window size for estimating tree height[J]. Photogrammetric Engineering & Remote Sensing, 2004, 70(5): 589-604.

[13] Koch B, Heyder U, Welnacker H. Detection of individual tree crowns in airborne liDAR data[J]. Photogrammetric Engineering & Remote Sensing, 2006, 72(4): 357-363.

[14] Chen Q. Isolating individual trees in a savanna woodland using small footprint liDAR data[J]. Photogrammetric Engineering & Remote Sensing, 2006, 72(8): 923-932.

[15] 刘清旺. 机载激光雷达森林参数估测方法研究[D].北京: 中国林业科学研究院, 2009.

    Liu Q W. Research on the estimation method of forest parameters using airborne lidar[D]. Beijing: Chinese Academy of Forestry, 2009.

[16] 尹艳豹. 基于机载激光雷达测量的森林资源调查因子联立估计研究[D]. 北京: 中国林业科学研究院, 2010.

    Yin Y B. Study on simultaneous estimation of forest resource survey factors based on airborne lidar measurement data[D]. Beijing: Chinese Academy of Forestry, 2010.

[17] Duncanson L I, Cook B D, Hurtt G C, et al. An efficient, multi-layered crown delineation algorithm for mapping individual tree structure across multiple ecosystems[J]. Remote Sensing of Environment, 2014, 154: 378-386.

[18] Wu B, Yu B, Wu Q, et al. Individual tree crown delineation using localized contour tree method and airborne lidar data in coniferous forests[J]. International Journal of Applied Earth Observation & Geoinformation, 2016, 52: 82-94.

[19] Morsdorf F, Meier E, Allgwer B, et al. Clustering in airborne laser scanning raw data for segmentation of single trees[C]∥International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 3-D Reconstruction from Airborne Laser Scanner and InSAR Data. Dresden, Germany, 2003.

[20] Wang Y, Weinacker H, Koch B. A lidar point cloud based procedure for vertical canopy structure analysis and 3D single tree modelling in forest[J]. Sensors, 2008, 8(6): 3938-3951.

[21] Reitberger J, Schnrr C, Krzystek P, et al. 3D segmentation of single trees exploiting full waveform LIDAR data[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2009, 64(6): 561-574.

[22] Reitberger J, Krzystek P, Stilla U, et al. 3D segmentation and classification of single trees with full waveform LIDAR data.[C]∥ International Conference on Lidar Applications in Forest Assessment and Inventory, 2008: 17-19.

[23] Ferraz A, Bretar F, Jacquemoud S, et al. 3-D mapping of a multi-layered Mediterranean forest using ALS data[J]. Remote Sensing of Environment, 2012, 121(138): 210-223.

[24] Li W, Guo Q, Jakubowski M K, et al. A new method for segmenting individual trees from the LiDAR point cloud[J]. Photogrammetric Engineering and Remote Sensing, 78(1): 75-84.

[25] 刘峰, 谭畅, 张贵, 等. 长白落叶松单木参数与生物量机载LiDAR估测[J]. 农业机械学报, 2013, 44(9): 219-224.

    Liu F, Tan C, Zhang G, et al. Estimation of forest parameter and biomass for individual pine trees using airborne LiDAR[J]. Transactions of the Chinese Society for Agricultural Machinery, 2013, 44(9): 219-224.

[26] Vega C,Hamrouni A, El Mokhtari S, et al. PTrees: a point-based approach to forest tree extraction from lidar data[J]. International Journal of Applied Earth Observation and Geoinformation, 2014, 33: 98-108.

[27] Lu X C, Guo Q H, Li W K, et al. A bottom-up approach to segment individual deciduous trees using leaf-off lidar point cloud data[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2014, 94: 1-12.

[28] Mongus D, alik B. An efficient approach to 3D single tree-crown delineation in LiDAR data[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2015, 108: 219-233.

[29] Wolf (né Straub) B M, Heipke C. Automatic extraction and delineation of single trees from remote sensing data[J]. Machine Vision and Applications, 2007, 18(5): 317-330.

[30] Ene L, Nsset E, Gobakken T. Single tree detection in heterogeneous boreal forests using airborne laser scanning and area-based stem number estimates[J]. International Journal of Remote Sensing, 2012, 33(16): 5171-5193.

[31] Pitknen J, Maltamo M, Hyypp J, et al. Adaptive methods for individual tree detection on airborne laser based canopy height model[C]∥Proceedings of ISPRS Workshop Laser-Scanners for Forest and Landscape Assessment , 2004: 187-191.

[32] Baatz M, Benz U, Dehghani S, et al. eCogonition Version 4 User Guide[EB/OL].[2018-02-01]. http://www.irfanakar.com/gis_remote_sensing_files/eCognition%20Definiens/Elementd%204.0%20User%20Guide.pdf

[33] Yu X W, Hyypp 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.

[34] Kaartinen H, Hyypp J, Yu X W, et al. An international comparison of individual tree detection and extraction using airborne laser scanning[J]. Remote Sensing, 2012, 4(4): 950-974.

[35] Vauhkonen J, Ene L, Gupta S, et al. Comparative testing of single-tree detection algorithms under different types of forest[J]. Forestry, 2011, 85(1): 27-40.

[36] Vastaranta M, Kankare V, Holopainen M, et al. Combination of individual tree detection and area-based approach in imputation of forest variables using airborne laser data[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2012, 67: 73-79.

[37] 徐光彩. 机载LIADR波形数据处理及分类研究[D].南京: 南京林业大学, 2010.

    Xu G C. Research on airborne LIDAR waveform data processing and classifying[D]. Nanjing: Nanjing Forestry University, 2010.

[38] Hfle B, Hollaus M, Hagenauer J. Urban vegetation detection using radiometrically calibrated small-footprint full-waveform airborne LiDAR data[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2012, 67: 134-147.

[39] Yang X Y, Strahler A H, Schaaf C B, et al. Three-dimensional forest reconstruction and structural parameter retrievals using a terrestrial full-waveform lidar instrument (Echidna)[J]. Remote Sensing of Environment, 2013, 135: 36-51.

[40] Rees W G.Characterisation of Arctic treelines by LiDAR and multispectral imagery[J]. Polar Record, 2007, 43(4): 345-352.

[41] Thieme N, Bollandss O M, Gobakken T, et al. Detection of small single trees in the forest-tundra ecotone using height values from airborne laser scanning[J]. Canadian Journal of Remote Sensing, 2011, 37(3): 264-274.

[42] Stumberg N, Bollandss O, Gobakken T, et al. Automatic detection of small single trees in the forest-tundra ecotone using airborne laser scanning[J]. Remote Sensing, 2014, 6(10): 10152-10170.

[43] 庞勇, 李增元, 谭炳香, 等. 点云密度对机载激光雷达林分高度反演的影响[J]. 林业科学研究, 2008, 21(S1): 14-19.

    Pang Y, Li Z Y, Tan B X, et al. The effects of airborne LiDAR point density on forest height estimation[J]. Forest Research, 2008, 21(S1): 14-19.

[44] Smits I, Dagis S, Dubrovskis D, et al. Individual tree identification using different LIDAR and optical imagery data processing methods[J]. Biosystems and Information Technology, 2012, 1(1): 19-24.

[45] Yao W,Krull J, Krzystek P, et al. Sensitivity analysis of 3D individual tree detection from LiDAR point clouds of temperate forests[J]. Forests, 2014, 5(6): 1122-1142.

[46] Baltsavias E P. Airborne laser scanning: existing systems and firms and other resources[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 1999, 54(2/3): 164-198.

[47] Brandtberg T, Warner T A, Landenberger R E, et al. Detection and analysis of individual leaf-off tree crowns in small footprint, high sampling density lidar data from the eastern deciduous forest in North America[J]. Remote Sensing of Environment, 2003, 85(3): 290-303.

[48] Khosravipour A, Skidmore A K, Wang T J, et al. Effect of slope on treetop detection using a LiDAR canopy height model[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2015, 104: 44-52.

[49] Yao W,Krzystek P, Heurich M. Tree species classification and estimation of stem volume and DBH based on single tree extraction by exploiting airborne full-waveform LiDAR data[C]∥Proceedings of the 12th WSEAS International Conference on Automatic Control, Modelling & Simulation. World Scientific and Engineering Academy and Society (WSEAS), 2012: 248-252.

[50] Amiri N, Yao W, Heurich M, et al. Estimation of regeneration coverage in a temperate forest by 3D segmentation using airborne laser scanning data[J]. International Journal of Applied Earth Observation and Geoinformation, 2016, 52: 252-262.

刘会玲, 张晓丽, 张莹, 朱云峰, 刘辉, 王龙阳. 机载激光雷达单木识别研究进展[J]. 激光与光电子学进展, 2018, 55(8): 082805. Liu Huiling, Zhang Xiaoli, Zhang Ying, Zhu Yunfeng, Liu Hui, Wang Longyang. Review on Individual Tree Detection Based on Airborne LiDAR[J]. Laser & Optoelectronics Progress, 2018, 55(8): 082805.

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