Studying canopy structure through 3-D reconstruction of point clouds from full-waveform terrestrial lidar

Yang, Xiaoyuan; Schaaf, Crystal B.; Strahler, Alan H.; Ли, Жан; Wang, Zhuosen; Yao, Tian; Zhao, Feng; Saenz, E. J.; Paynter, Ian; Douglas, Ewan S.; Chakrabarti, Supriya; Cook, Timothy A.; Martel, Jason; Howe, Glenn A.; Woodcock, Curtis E.; Jupp, David L.B.; Culvenor, Darius; Newnham, Glenn; Lovell, Jenny

doi:10.1109/igarss.2013.6723552

“…Of the 87, only 15 studies worked in the savanna biome [39,145,146]. The most frequently employed methods to derive vegetation attributes are the RANdom SAmple Consensus (RANSAC) algorithm for extracting DBH, stem curve profiles and the detection of stems [97,147], the use of the highest z coordinate of the point cloud for estimating heights [61,148], voxel-based and radiative transfer models for assessing LAI [149,150], Canopy Height Models (CHMs) for delineating crown attributes [91,92], and Quantitative Structure Models (QSMs) for computing tree volume and branch parameters [151,152]. Popular software packages to implement and work with these methods are Lastools [153], Matlab [154], R [155] and Python Programming [156], Cyclone [157], FARO Scene [158], RiscanPro [159], CompuTree [160] and Cloud Compare [161].…”

Section: Methods Used With Tls Point Cloudsmentioning

confidence: 99%

“…However, only limited overall evidence can be found in the literature so that a number of unresolved scientific questions still remain. In particular, more research is needed on the improved retrieval of the LAI with TLS intensity [80,150]. Among others, this could be achieved by a better separation of leaf and wood material [176].…”

Section: Future Outlookmentioning

confidence: 99%

Terrestrial Laser Scanning for Vegetation Analyses with a Special Focus on Savannas

Muumbe

¹

,

Baade

²

,

Singh

³

et al. 2021

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Savannas are heterogeneous ecosystems, composed of varied spatial combinations and proportions of woody and herbaceous vegetation. Most field-based inventory and remote sensing methods fail to account for the lower stratum vegetation (i.e., shrubs and grasses), and are thus underrepresenting the carbon storage potential of savanna ecosystems. For detailed analyses at the local scale, Terrestrial Laser Scanning (TLS) has proven to be a promising remote sensing technology over the past decade. Accordingly, several review articles already exist on the use of TLS for characterizing 3D vegetation structure. However, a gap exists on the spatial concentrations of TLS studies according to biome for accurate vegetation structure estimation. A comprehensive review was conducted through a meta-analysis of 113 relevant research articles using 18 attributes. The review covered a range of aspects, including the global distribution of TLS studies, parameters retrieved from TLS point clouds and retrieval methods. The review also examined the relationship between the TLS retrieval method and the overall accuracy in parameter extraction. To date, TLS has mainly been used to characterize vegetation in temperate, boreal/taiga and tropical forests, with only little emphasis on savannas. TLS studies in the savanna focused on the extraction of very few vegetation parameters (e.g., DBH and height) and did not consider the shrub contribution to the overall Above Ground Biomass (AGB). Future work should therefore focus on developing new and adjusting existing algorithms for vegetation parameter extraction in the savanna biome, improving predictive AGB models through 3D reconstructions of savanna trees and shrubs as well as quantifying AGB change through the application of multi-temporal TLS. The integration of data from various sources and platforms e.g., TLS with airborne LiDAR is recommended for improved vegetation parameter extraction (including AGB) at larger spatial scales. The review highlights the huge potential of TLS for accurate savanna vegetation extraction by discussing TLS opportunities, challenges and potential future research in the savanna biome.

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“…Of the 87, only 15 studies worked in the savanna biome [39,145,146]. The most frequently employed methods to derive vegetation attributes are the RANdom SAmple Consensus (RANSAC) algorithm for extracting DBH, stem curve profiles and the detection of stems [97,147], the use of the highest z coordinate of the point cloud for estimating heights [61,148], voxel-based and radiative transfer models for assessing LAI [149,150], Canopy Height Models (CHMs) for delineating crown attributes [91,92], and Quantitative Structure Models (QSMs) for computing tree volume and branch parameters [151,152]. Popular software packages to implement and work with these methods are Lastools [153], Matlab [154], R [155] and Python Programming [156], Cyclone [157], FARO Scene [158], RiscanPro [159], CompuTree [160] and Cloud Compare [161].…”

Section: Methods Used With Tls Point Cloudsmentioning

confidence: 99%

“…However, only limited overall evidence can be found in the literature so that a number of unresolved scientific questions still remain. In particular, more research is needed on the improved retrieval of the LAI with TLS intensity [80,150]. Among others, this could be achieved by a better separation of leaf and wood material [176].…”

Section: Future Outlookmentioning

confidence: 99%

Remote Sensing of Savannas and Woodlands

2021

0

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“…Besides traditional satellite laser scanning (e.g., ICESat-GLAS) [ 1 , 2 ] and airborne laser scanning (e.g., SLICER, LVIS) [ 3 , 4 ], small and portable terrestrial laser scanning (TLS) devices, which can be mounted on a static tripod or transported by a forestry vehicle, have been readily introduced into the field [ 5 ]. For forestry resource survey purposes, TLS has generally been a fast, efficient and automatic tool for determining basic properties and structural parameters of forests such as discrimination of plant components [ 6 ], stem count density [ 7 ], three-dimensional forest reconstruction [ 8 ], canopy height modelling [ 9 ], chlorophyll level measurement [ 10 ] as well as variables recognition [ 11 ]. Especially, the living-tree diameter at breast height (DBH) is the basic parameter in forestry resources surveys [ 12 ] and is a good predictor for many features of interest (e.g., above-ground biomass) [ 13 , 14 ].…”

Section: Introductionmentioning

confidence: 99%

New Hybrid Algorithms for Estimating Tree Stem Diameters at Breast Height Using a Two Dimensional Terrestrial Laser Scanner

Kong

¹

,

Ding

²

,

Liu

³

et al. 2015

Sensors

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In this paper, a new algorithm to improve the accuracy of estimating diameter at breast height (DBH) for tree trunks in forest areas is proposed. First, the information is collected by a two-dimensional terrestrial laser scanner (2DTLS), which emits laser pulses to generate a point cloud. After extraction and filtration, the laser point clusters of the trunks are obtained, which are optimized by an arithmetic means method. Then, an algebraic circle fitting algorithm in polar form is non-linearly optimized by the Levenberg-Marquardt method to form a new hybrid algorithm, which is used to acquire the diameters and positions of the trees. Compared with previous works, this proposed method improves the accuracy of diameter estimation of trees significantly and effectively reduces the calculation time. Moreover, the experimental results indicate that this method is stable and suitable for the most challenging conditions, which has practical significance in improving the operating efficiency of forest harvester and reducing the risk of causing accidents.

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Studying canopy structure through 3-D reconstruction of point clouds from full-waveform terrestrial lidar

Cited by 4 publications

References 6 publications

Terrestrial Laser Scanning for Vegetation Analyses with a Special Focus on Savannas

Terrestrial Laser Scanning for Vegetation Analyses with a Special Focus on Savannas

Remote Sensing of Savannas and Woodlands

New Hybrid Algorithms for Estimating Tree Stem Diameters at Breast Height Using a Two Dimensional Terrestrial Laser Scanner

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