WANG Yan, XIE Donghui, WANG Xiangyu, et al. Simulation and analysis of point clouds from a terrestrial laser scanner. [J]. Journal of Remote Sensing 19(3):391-399(2015)
WANG Yan, XIE Donghui, WANG Xiangyu, et al. Simulation and analysis of point clouds from a terrestrial laser scanner. [J]. Journal of Remote Sensing 19(3):391-399(2015) DOI: 10.11834/jrs.20154087.
Simulation and analysis of point clouds from a terrestrial laser scanner
Terrestrial Laser Scanner( TLS) technology can quickly acquire three-dimensional information of targets with high precision. Given that TLS is a new data collection technique
it has been gradually applied to characterize the structural attributes of forest canopy. However
the inversion accuracy of Leaf Area Index( LAI) is highly dependent on the intrinsic configuration of the sensor
such as beam size and echo detection energy. In this paper
a computer simulation model was proposed to simulate point clouds from TLS and to analyze quantitatively the influence of beam characteristic on LAI inverted from TLS data.A realistic tree was generated with Onyx TREE BROADLEAF software. Moreover
a computer model was proposed to simulate the interactions of lasers with a single tree and to acquire the point clouds from a TLS Riegl VZ-1000 based on the ray tracing algorithm. This model consisted of the ray intersection with triangular patches of photorealistic trees
the coordinate system conversion
and the acceleration of the algorithm. The beam size at exit
beam divergence
and echo detection algorithm were considered in the computer simulation method. One laser beam was divided into multiple bins
and each bin was treated as a separate pulse with its location
propagation direction
and an initial energy changing into a Gaussian shape. We inverted the crown-level Leaf Area Index( LAI) by using gap fraction analysis with the simulated point clouds
and the influence of beam characteristics( such as beam diameter and minimum echo detection intensity) on the LAI inversion was analyzed. Finally
we conducted the validation with the measured points of a birch tree located in Root River. We analyzed the influences of beam characteristics
such as beam size
beam divergence
and echo detection energy
on LAI inversion. The inversion results indicate that beam size and detection limit greatly influence LAI inversion. The points are increased with the decrease of the corresponding gap fraction because several points can be returned from one beam when the beam width and divergence were considered
particularly when significant differences are achieved at the edge of leaves. A larger beam size means that components in the edge portion are intercepted more easily. Thus
the deviation of LAI inversion would be greater. When the detection intensity threshold was small
echo information could be returned even if only part of the spot edge was intercepted. Thus
gap fraction is undervalued. However
when the energy threshold setting was large
the returned energy may be below the threshold value and cannot be recorded
thereby resulting in overestimation of the gap fraction and underestimation of LAI. Therefore
the points caused by beam size and echo detection must be filtered
and suitable points must be chosen before inverting LAI with the gap fraction model.The simulation model based on the ray tracing algorithm was presented to explore the laser beam interceptions with an individual tree generated by using Onyx Tree software. The LAI was retrieved via gap fraction analysis with zenith slicing method. The beam characteristics
such as beam size
echo detection energy
and beam divergence
were considered. The simulation model enables efficient and cost-effective research that can avoid environmental and instrumental error. This model contributes to an improved understanding of the intersections of laser beams with the tree crown well
and the LAI inversion of an individual tree is facilitated.
关键词
光线追踪地面激光雷达计算机模拟间隙率模型叶面积指数
Keywords
terrestrial laser scannercomputer simulationray tracinggap fractionleaf area index
Beijing Engineering Research Center for Global Land Remote Sensing Products/Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal University
Beijing Normal University, State Key Laboratory of Remote Sensing Science
International Institute for Earth System Science, Nanjing University
Institute of Marine Technology and Surveying, Jiangsu Ocean University
Key Laboratory of Digital Earth, Aerospace Information Research Institute, Chinese Academy of Sciences