多回波点云数据解算单株木叶面积指数
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摘要
以行道树无患子为研究目标,采用地面激光扫描(TLS)技术提取单木分回波点云数据。获取全波形数据、单目标数据、首次回波数据、其余次回波数据,建立基于多回波点云的算法,利用消光系数法提取不同投影分辨率0.01 m、0.02 m和0.03 m的的单株树叶面积指数(LAI)。利用2维影像数据数字半球影像(DHP)和LAI2200提取对应单株树的叶面积指数,进行比较分析,以检验其精度。结果表明:点云投影的分辨率与激光回波都对LAI有极显著影响,其中分辨率为0.02 m和0.03 m的估算结果与LAI2200所得估算结果相近,且差异不显著;单目标回波数据用于LAI的解算,可以同LAI2200的2维影像数据结果进行相互验证。使用单目标回波数据,0.02 m投影分辨率可以最大程度的保证单株LAI的精度,其与LAI2200测定的数据进行截距为0的线性回归,斜率达到0.827。本研究所做多回波地面激光数据计算叶面积指数的算法拓展了地面激光扫描的应用领域,为立木生长量信息准确提取和树木精确建模提供了重要的技术参考。
This study aimed to extract the Leaf Area Index(LAI) of individual trees through multi-return terrestrial laser point cloud data,including single target, first-return waveform, intermediate, and last target data. The species was soapberry planted as street trees. An algorithm based on Beer–Lambert law was developed to divide return waveform,and the LAIs of individual trees with different projection resolutions of 0.01, 0.02, and 0.03 m were obtained. Two-dimensional digital hemispherical image data and LAI-2200 were used to extract the LAIs of corresponding single trees for accuracy comparison. Result shows that the resolutions and multiple return waveforms have significant influence on LAI. The results with 0.02 m and 0.03 m resolutions are similar to those obtained with LAI2200, and the difference is insignificant. However, the single target waveform point cloud data are used for the LAI solution and can be mutually verified with the results of the 2D image data of LAI2200. The LAI value of single target waveform point cloud was calculated with Beer– Lambert at 0.02 m resolution, and the intercept measured by LAI2200 data was subjected to a linear regression with an intercept of 0 and slope of 0.827, which is close to 1. Therefore, for the multi-return waveform ground laser scanning data, the single target waveform point cloud data with a projection resolution of 0.02 m can be used to obtain accurate LAI when using an extinction coefficient method. The algorithm for calculating the LAI based on multi-return waveform ground-based laser data in this study expands the application field of TLS and provides an important technical reference for the accurate extraction of the growth of standing trees and accurate tree modeling.
This study aimed to extract the Leaf Area Index(LAI) of individual trees through multi-return terrestrial laser point cloud data,including single target, first-return waveform, intermediate, and last target data. The species was soapberry planted as street trees. An algorithm based on Beer–Lambert law was developed to divide return waveform,and the LAIs of individual trees with different projection resolutions of 0.01, 0.02, and 0.03 m were obtained. Two-dimensional digital hemispherical image data and LAI-2200 were used to extract the LAIs of corresponding single trees for accuracy comparison. Result shows that the resolutions and multiple return waveforms have significant influence on LAI. The results with 0.02 m and 0.03 m resolutions are similar to those obtained with LAI2200, and the difference is insignificant. However, the single target waveform point cloud data are used for the LAI solution and can be mutually verified with the results of the 2D image data of LAI2200. The LAI value of single target waveform point cloud was calculated with Beer– Lambert at 0.02 m resolution, and the intercept measured by LAI2200 data was subjected to a linear regression with an intercept of 0 and slope of 0.827, which is close to 1. Therefore, for the multi-return waveform ground laser scanning data, the single target waveform point cloud data with a projection resolution of 0.02 m can be used to obtain accurate LAI when using an extinction coefficient method. The algorithm for calculating the LAI based on multi-return waveform ground-based laser data in this study expands the application field of TLS and provides an important technical reference for the accurate extraction of the growth of standing trees and accurate tree modeling.
引文
Calders K,Origo N,Disney M,Nightingale J,Woodgate W,Armston Jand Lewis P.2018.Variability and bias in active and passive ground-based measurements of effective plant,wood and leaf area index.Agricultural and Forest Meteorology,252:231-240[DOI:10.1016/j.agrformet.2018.01.029]
Cao L,She G H,Dai J S and Xu J X.2013.Status and prospects of the LiDAR-based forest biomass estimation.Journal of Nanjing Forestry University(Natural Sciences Edition),37(3):163-169(曹林,佘光辉,代劲松,徐建新.2013.激光雷达技术估测森林生物量的研究现状及展望.南京林业大学学报(自然科学版),37(3):163-169)[DOI:10.3969/j.issn.1000-2006.2013.03.029]
Chen J M and Black T A.1992.Defining leaf area index for non-flat leaves.Plant,Cell and Environment,15(4):421-429[DOI:10.1111/j.1365-3040.1992.tb00992.x]
Deng Y B,Liu J,Yu K Y,Chen Z H,Yu X Y and Lin T Z.2017.Individual tree Lai inversion technique based on stratification theory and 3D laser scanning.Journal of Southwest Forestry University,37(6):148-155(邓洋波,刘健,余坤勇,陈樟昊,俞欣妍,林同舟.2017.基于分层理论与三维激光扫描的单木叶面积指数反演技术研究.西南林业大学学报,37(6):148-155)[DOI:10.11929/j.issn.2095-1914.2017.06.024]
Li Y M,Guo Q H,Su Y J,Tao S L,Zhao K G and Xu G C.2017.Retrieving the gap fraction,element clumping index,and leaf area index of individual trees using single-scan data from a terrestrial laser scanner.ISPRS Journal of Photogrammetry and Remote Sensing,130:308-316[DOI:10.1016/j.isprsjprs.2017.06.006]
Liu Y,Liu R G,Chen J M,Cheng X and Zheng G.2013.Current status and perspectives of leaf area index retrieval from optical remote sensing data.Journal of Geo-information science,15(5):734-743(刘洋,刘荣高,陈镜明,程晓,郑光.2013.叶面积指数遥感反演研究进展与展望.地球信息科学学报,15(5):734-743)[DOI:10.3724/SP.J.1047.2013.00734]
Ma L X,Zheng G,Eitel J U H,Moskal L M,He W and Huang H B.2016.Improved salient feature-based approach for automatically separating photosynthetic and nonphotosynthetic components within terrestrial lidar point cloud data of forest canopies.IEEETransactions on Geoscience and Remote Sensing,54(2):679-696[DOI:10.1109/TGRS.2015.2459716]
Ma L X,Zheng G,Eitel J U H,Magney T S and Moskal L M.2017.Retrieving forest canopy extinction coefficient from terrestrial and airborne lidar.Agricultural and Forest Meteorology,236:1-21[DOI:10.1016/j.agrformet.2017.01.004]
Ma Z Q,Liu Q J,Zeng H Q,Li X R,Chen Y R,Lin Y M,Zhang S H,Yang F T and Wang H Q.2008.Estimation of leaf area index of planted forests in subtropical China by Photogrammetry.Acta Ecologica Sinica,28(5):1971-1980(马泽清,刘琪璟,曾慧卿,李轩然,陈永瑞,林耀明,张时煌,杨风亭,汪宏清.2008.南方人工林叶面积指数的摄影测量.生态学报,28(5):1971-1980)[DOI:10.3321/j.issn:1000-0933.2008.05.011]
Martens S N,Ustin S L and Rousseau R A.1993.Estimation of tree canopy leaf area index by gap fraction analysis.Forest Ecology and Management,61(1/2):91-108[DOI:10.1016/0378-1127(93)90192-P]
Pirotti F,Guarnieri A and Vettore A.2013.Vegetation filtering of waveform terrestrial laser scanner data for DTM production.Applied Geomatics,5(4):311-322[DOI:10.1007/s12518-013-0119-3]
Wang H S,Li S H,Guo J W and Liang Z Q.2016.Retrieval of the leaf area density of Magnolia woody canopy with terrestrial Laserscanning data.Journal of Remote Sensing,20(4):570-578(王洪蜀,李世华,郭加伟,梁祖琴.2016.地基激光雷达的玉兰林冠层叶面积密度反演.遥感学报,20(4):570-578)[DOI:10.11834/jrs.20165061]
Wilkes P,Lau A,Disney M,Calders K,Burt A,de Tanago J G,Bartholomeus H,Brede B and Herold M.2017.Data acquisition considerations for Terrestrial Laser Scanning of forest plots.Remote Sensing of Environment,196:140-153[DOI:10.1016/j.rse.2017.04.030]
Wu H S.2015.Research and implementation of fisheye camera image processing.Xi’an:Xidian University(吴火森.2015.鱼眼相机图像处理及校正算法研究与实现.西安:西安电子科技大学)
Xing Y Q,Yao S T,You H T,Tian X,Peng T,Li M Y,Xie J and Yan C.2018.A inversion on birch forest LAI based on airborne LiD-AR full waveform data.Journal of Northwest Forestry University,33(1):11-18(邢艳秋,姚松涛,尤号田,田昕,彭涛,李梦颖,谢杰,闫灿.2018.基于机载LiDAR全波形数据白桦林林分LAI反演研究.西北林学院学报,33(1):11-18)[DOI:10.3969/j.issn.1001-7461.2018.01.02]
Yang W X,Fu W X,Zhou Z W,Yu W and Ma J.2014.Fast three dimensional LIDAR target recognition based on projection dimension reduction.Infrared and Laser Engineering,43(S1):1-7(杨文秀,付文兴,周志伟,余巍,马杰.2014.基于投影降维的激光雷达快速目标识别.红外与激光工程,43(S1):1-7)[DOI:10.3969/j.issn.1007-2276.2014.z1.001]
Yin G F,Liu Q H,Li J,Zeng Y L and Xu B D.2014.Effect of crown shape on the estimation of gap probability and leaf area index.Journal of Remote Sensing,18(4):752-759(尹高飞,柳钦火,李静,曾也鲁,徐保东.2014.树冠形状对孔隙率及叶面积指数估算的影响分析.遥感学报,18(4):752-759)[DOI:10.11834/jrs.20143205]
Yun T,An F,Li W Z,Sun Y,Cao L and Xue L F.2016.A novel approach for retrieving tree leaf area from ground-based LiDAR.Remote Sensing,8(11):942[DOI:10.3390/rs8110942]
Zhao K G,García M,Liu S,Guo Q H,Chen G,Zhang X S,Zhou Y Yand Meng X L.2015.Terrestrial lidar remote sensing of forests:Maximum likelihood estimates of canopy profile,leaf area index,and leaf angle distribution.Agricultural and Forest Meteorology,209-210:100-113[DOI:10.1016/j.agrformet.2015.03.008]
Zheng G,Moskal L M and Kim S H.2013.Retrieval of effective leaf area index in heterogeneous forests with terrestrial laser scanning.IEEE Transactions on Geoscience and Remote Sensing,51(2):777-786[DOI:10.1109/TGRS.2012.2205003]
Zou J and Yan G J.2010.Optical methods for in situ measuring leaf area index of forest canopy:a review.Chinese Journal of Applied Ecology,21(11):2971-2979(邹杰,阎广建.2010.森林冠层地面叶面积指数光学测量方法研究进展.应用生态学报,21(11):2971-2979)
Cao L,She G H,Dai J S and Xu J X.2013.Status and prospects of the LiDAR-based forest biomass estimation.Journal of Nanjing Forestry University(Natural Sciences Edition),37(3):163-169(曹林,佘光辉,代劲松,徐建新.2013.激光雷达技术估测森林生物量的研究现状及展望.南京林业大学学报(自然科学版),37(3):163-169)[DOI:10.3969/j.issn.1000-2006.2013.03.029]
Chen J M and Black T A.1992.Defining leaf area index for non-flat leaves.Plant,Cell and Environment,15(4):421-429[DOI:10.1111/j.1365-3040.1992.tb00992.x]
Deng Y B,Liu J,Yu K Y,Chen Z H,Yu X Y and Lin T Z.2017.Individual tree Lai inversion technique based on stratification theory and 3D laser scanning.Journal of Southwest Forestry University,37(6):148-155(邓洋波,刘健,余坤勇,陈樟昊,俞欣妍,林同舟.2017.基于分层理论与三维激光扫描的单木叶面积指数反演技术研究.西南林业大学学报,37(6):148-155)[DOI:10.11929/j.issn.2095-1914.2017.06.024]
Li Y M,Guo Q H,Su Y J,Tao S L,Zhao K G and Xu G C.2017.Retrieving the gap fraction,element clumping index,and leaf area index of individual trees using single-scan data from a terrestrial laser scanner.ISPRS Journal of Photogrammetry and Remote Sensing,130:308-316[DOI:10.1016/j.isprsjprs.2017.06.006]
Liu Y,Liu R G,Chen J M,Cheng X and Zheng G.2013.Current status and perspectives of leaf area index retrieval from optical remote sensing data.Journal of Geo-information science,15(5):734-743(刘洋,刘荣高,陈镜明,程晓,郑光.2013.叶面积指数遥感反演研究进展与展望.地球信息科学学报,15(5):734-743)[DOI:10.3724/SP.J.1047.2013.00734]
Ma L X,Zheng G,Eitel J U H,Moskal L M,He W and Huang H B.2016.Improved salient feature-based approach for automatically separating photosynthetic and nonphotosynthetic components within terrestrial lidar point cloud data of forest canopies.IEEETransactions on Geoscience and Remote Sensing,54(2):679-696[DOI:10.1109/TGRS.2015.2459716]
Ma L X,Zheng G,Eitel J U H,Magney T S and Moskal L M.2017.Retrieving forest canopy extinction coefficient from terrestrial and airborne lidar.Agricultural and Forest Meteorology,236:1-21[DOI:10.1016/j.agrformet.2017.01.004]
Ma Z Q,Liu Q J,Zeng H Q,Li X R,Chen Y R,Lin Y M,Zhang S H,Yang F T and Wang H Q.2008.Estimation of leaf area index of planted forests in subtropical China by Photogrammetry.Acta Ecologica Sinica,28(5):1971-1980(马泽清,刘琪璟,曾慧卿,李轩然,陈永瑞,林耀明,张时煌,杨风亭,汪宏清.2008.南方人工林叶面积指数的摄影测量.生态学报,28(5):1971-1980)[DOI:10.3321/j.issn:1000-0933.2008.05.011]
Martens S N,Ustin S L and Rousseau R A.1993.Estimation of tree canopy leaf area index by gap fraction analysis.Forest Ecology and Management,61(1/2):91-108[DOI:10.1016/0378-1127(93)90192-P]
Pirotti F,Guarnieri A and Vettore A.2013.Vegetation filtering of waveform terrestrial laser scanner data for DTM production.Applied Geomatics,5(4):311-322[DOI:10.1007/s12518-013-0119-3]
Wang H S,Li S H,Guo J W and Liang Z Q.2016.Retrieval of the leaf area density of Magnolia woody canopy with terrestrial Laserscanning data.Journal of Remote Sensing,20(4):570-578(王洪蜀,李世华,郭加伟,梁祖琴.2016.地基激光雷达的玉兰林冠层叶面积密度反演.遥感学报,20(4):570-578)[DOI:10.11834/jrs.20165061]
Wilkes P,Lau A,Disney M,Calders K,Burt A,de Tanago J G,Bartholomeus H,Brede B and Herold M.2017.Data acquisition considerations for Terrestrial Laser Scanning of forest plots.Remote Sensing of Environment,196:140-153[DOI:10.1016/j.rse.2017.04.030]
Wu H S.2015.Research and implementation of fisheye camera image processing.Xi’an:Xidian University(吴火森.2015.鱼眼相机图像处理及校正算法研究与实现.西安:西安电子科技大学)
Xing Y Q,Yao S T,You H T,Tian X,Peng T,Li M Y,Xie J and Yan C.2018.A inversion on birch forest LAI based on airborne LiD-AR full waveform data.Journal of Northwest Forestry University,33(1):11-18(邢艳秋,姚松涛,尤号田,田昕,彭涛,李梦颖,谢杰,闫灿.2018.基于机载LiDAR全波形数据白桦林林分LAI反演研究.西北林学院学报,33(1):11-18)[DOI:10.3969/j.issn.1001-7461.2018.01.02]
Yang W X,Fu W X,Zhou Z W,Yu W and Ma J.2014.Fast three dimensional LIDAR target recognition based on projection dimension reduction.Infrared and Laser Engineering,43(S1):1-7(杨文秀,付文兴,周志伟,余巍,马杰.2014.基于投影降维的激光雷达快速目标识别.红外与激光工程,43(S1):1-7)[DOI:10.3969/j.issn.1007-2276.2014.z1.001]
Yin G F,Liu Q H,Li J,Zeng Y L and Xu B D.2014.Effect of crown shape on the estimation of gap probability and leaf area index.Journal of Remote Sensing,18(4):752-759(尹高飞,柳钦火,李静,曾也鲁,徐保东.2014.树冠形状对孔隙率及叶面积指数估算的影响分析.遥感学报,18(4):752-759)[DOI:10.11834/jrs.20143205]
Yun T,An F,Li W Z,Sun Y,Cao L and Xue L F.2016.A novel approach for retrieving tree leaf area from ground-based LiDAR.Remote Sensing,8(11):942[DOI:10.3390/rs8110942]
Zhao K G,García M,Liu S,Guo Q H,Chen G,Zhang X S,Zhou Y Yand Meng X L.2015.Terrestrial lidar remote sensing of forests:Maximum likelihood estimates of canopy profile,leaf area index,and leaf angle distribution.Agricultural and Forest Meteorology,209-210:100-113[DOI:10.1016/j.agrformet.2015.03.008]
Zheng G,Moskal L M and Kim S H.2013.Retrieval of effective leaf area index in heterogeneous forests with terrestrial laser scanning.IEEE Transactions on Geoscience and Remote Sensing,51(2):777-786[DOI:10.1109/TGRS.2012.2205003]
Zou J and Yan G J.2010.Optical methods for in situ measuring leaf area index of forest canopy:a review.Chinese Journal of Applied Ecology,21(11):2971-2979(邹杰,阎广建.2010.森林冠层地面叶面积指数光学测量方法研究进展.应用生态学报,21(11):2971-2979)