Automatic identification of rock discontinuity and stability analysis of tunnel rock blocks using terrestrial laser scanning

Local geometric information and discontinuity features are key aspects of the analysis of the evolution and failure mechanisms of unstable rock blocks in rock tunnels.This study demonstrates the integration of terrestrial laser scanning(TLS)with distinct element method for rock mass characterization and stability analysis in tunnels.TLS records detailed geometric information of the surrounding rock mass by scanning and collecting the positions of millions of rock surface points without contact.By conducting a fuzzy K-means method,a discontinuity automatic identification algorithm was developed,and a method for obtaining the geometric parameters of discontinuities was proposed.This method permits the user to visually identify each discontinuity and acquire its spatial distribution features(e.g.occurrences,spac-ings,trace lengths)in great detail.Compared with hand mapping in conventional geotechnical surveys,the geometric information of discontinuities obtained by this approach is more accurate and the iden-tification is more efficient.Then,a discrete fracture network with the same statistical characteristics as the actual discontinuities was generated with the distinct element method,and a representative nu-merical model of the jointed surrounding rock mass was established.By means of numerical simulation,potential unstable rock blocks were assessed,and failure mechanisms were analyzed.This method was applied to detection and assessment of unstable rock blocks in the spillway and sand flushing tunnel of the Hongshiyan hydropower project after a collapse.The results show that the noncontact detection of blocks was more labor-saving with lower safety risks compared with manual surveys,and the stability assessment was more reliable since the numerical model built by this method was more consistent with the distribution characteristics of actual joints.This study can provide a reference for geological survey and unstable rock block hazard mitigation in tunnels subjected to complex geology and active rockfalls.

Study on the LAI Single Tree Model Based on Terrestrial Laser Scanning

Leaf area index (LAI) is a key parameter for studying global terrestrial ecology and environment and has great ecological significance. How to accurately measure and calculate structural parameters of trees has become an urgent matter. This paper reports the use of terrestrial laser scanning (TLS) as a measurement tool to achieve accurate LAI estimation through point cloud preprocessing measures, the LeWos algorithm, and voxel methods. The accuracy and feasibility of this indirect measurement method were explored. It is found that the single wood structure parameters extracted from TLS have a good linear relationship with manual measurement, and the extraction errors meet the requirements of real-scene conversion. The study also found when the voxel size is consistent with the minimum distance of the point cloud set by TLS instrument, it has a strong correlation with the measured value of canopy analyser. These results lay the foundation for conveniently and quickly obtaining structural parameters of trees, tree growth state detection, and canopy ecological benefit assessment.

Quantification of occlusions influencing the tree stem curve retrieving from single-scan terrestrial laser scanning data

Background: The stem curve of standing trees is an essential parameter for accurate estimation of stem volume.This study aims to directly quantify the occlusions within the single-scan terrestrial laser scanning(TLS) data,evaluate its correlation with the accuracy of the retrieved stem curves, and subsequently, to assess the capacity of single-scan TLS to estimate stem curves.Methods: We proposed an index, occlusion rate, to quantify the occlusion level in TLS data. We then analyzed three influencing factors for the occlusion rate: the percentage of basal area near the scanning center, the scanning distance and the source of occlusions. Finally, we evaluated the effects of occlusions on stem curve estimates from single-scan TLS data.Results: The results showed that the correlations between the occlusion rate and the stem curve estimation accuracies were strong(r = 0.60–0.83), so was the correlations between the occlusion rate and its influencing factors(r = 0.84–0.99). It also showed that the occlusions from tree stems were the main factor of the low detection rate of stems, while the non-stem components mainly influenced the completeness of the retrieved stem curves.Conclusions: Our study demonstrates that the occlusions significantly affect the accuracy of stem curve retrieval from the single-scan TLS data in a typical-size(32 m × 32 m) forest plot. However, the single-scan mode has the capacity to accurately estimate the stem curve in a small forest plot(< 10 m × 10 m) or a plot with a lower occlusion rate, such as less than 35% in our tested datasets. The findings from this study are useful for guiding the practice of retrieving forest parameters using single-scan TLS data.

Geostructural stability assessment of cave using rock surface discontinuity extracted from terrestrial laser scanning point cloud

The use of terrestrial laser scanning（TLS） in the caves has been growing drastically over the last decade.However, TLS application to cave stability assessment has not received much attention of researchers.This study attempted to utilize rock surface orientations obtained from TLS point cloud collected along cave passages to（1） investigate the influence of rock geostructure on cave passage development, and（2）assess cave stability by determining areas susceptible to different failure types. The TLS point cloud was divided into six parts（Entry hall, Chamber, Main hall, Shaft 1, Shaft 2 and Shaft 3）, each representing different segments of the cave passages. Furthermore, the surface orientation information was extracted and grouped into surface discontinuity joint sets. The computed global mean and best-fit planes of the entire cave show that the outcrop dips 290° with a major north-south strike. But at individual level, the passages with dip angle between 26° and 80° are featured with dip direction of 75°-322°. Kinematic tests reveal the potential for various failure modes of rock slope. Our findings show that toppling is the dominant failure type accounting for high-risk rockfall in the cave, with probabilities of 75.26%, 43.07%and 24.82% in the Entry hall, Main hall and Shaft 2, respectively. Unlike Shaft 2 characterized by high risk of the three failure types（32.49%, 24.82% and 50%）, the chamber and Shaft 3 passages are not suffering from slope failure. The results also show that the characteristics of rock geostructure considerably influence the development of the cave passages, and four sections of the cave are susceptible to different slope failure types, at varying degrees of risk.

Assessment of handheld mobile terrestrial laser scanning for estimating tree parameters

Sustainable forest management heavily relies on the accurate estimation of tree parameters.Among others,the diameter at breast height(DBH) is important for extracting the volume and mass of an individual tree.For systematically estimating the volume of entire plots,airborne laser scanning(ALS) data are used.The estimation model is frequently calibrated using manual DBH measurements or static terrestrial laser scans(STLS) of sample plots.Although reliable,this method is time-consuming,which greatly hampers its use.Here,a handheld mobile terrestrial laser scanning(HMTLS) was demonstrated to be a useful alternative technique to precisely and efficiently calculate DBH.Different data acquisition techniques were applied at a sample plot,then the resulting parameters were comparatively analysed.The calculated DBH values were comparable to the manual measurements for HMTLS,STLS,and ALS data sets.Given the comparability of the extracted parameters,with a reduced point density of HTMLS compared to STLS data,and the reasonable increase of performance,with a reduction of acquisition time with a factor of5 compared to conventional STLS techniques and a factor of3 compared to manual measurements,HMTLS is considered a useful alternative technique.

MDC-Net:a multi-directional constrained and prior assisted neural network for wood and leaf separation from terrestrial laser scanning

Wood-leaf separation from terrestrial laser scanning(TLS)is a crucial prerequisite for quantifying many biophysical properties and understanding ecological functions.In this study,we propose a novel multi-directional collaborative convolutional neural network(MDC-Net)that takes the original 3D coordinates and useful features from prior knowledge(prior features)as input,and outputs the semantic labels of TLS point clouds.The MDC-Net contains two key units:(1)a multi-directional neighborhood construction(MDNC)unit to obtain more representative neighbors and enable directionally aware feature encoding in the subsequent local feature extraction,to mitigate occlusion effects;(2)a collaborative feature encoding(CFE)unit is introduced to incorporate useful features from prior knowledge into the network through a collaborative cross coding to enhance the discrimination for thin structures(e.g.small branches and leaf).The MDC-Net is evaluated onfive plots from forests in Guangxi,China,with different branch architectures and leaf distributions.Experimental results showed that the MDC-Net achieved an OA of 0.973 and a mIoU of 0.821 and outperformed other related methods.We believe the MDC-Net would facilitate the usage of TLS in ecology studies for quantifying tree size and morphology and thus promote the development of relevant ecological applications.

Applications of terrestrial laser scanning for tunnels: a review

In recent years, the use of terrestrial laser scanning （TLS） technique in engineering surveys is gaining an increasing interest due to the advantages of non-contact, rapidity, high accuracy, and large scale. Millions of accurate 3D points （mm level accuracy） can be delivered by this technique with a high point density in a short time （up to 1 million points per second）, which makes it a poten- tial technique for large scale applications in engineering environments such as tunnels, bridges, and heritage buildings. Tunnels, in particular those with long lengths, create great challenges for surveyors to obtain the satisfactory scanned data. This paper presents a short history of TLS techniques used for tunnels. A general overview of TLS techniques is given, followed by a review of several applications of TLS for tunnels. These applications are classified as： detecting geological features of drilling tun- nels, monitoring the geometry of tunnels during excavation, making deformation measurements, and extracting features. The review emphasizes how TLS techniques can be used to measure various aspects of tunnels. It is clear that TLS techniques are not yet a common tool for tunnel investigations, but there is still a huge potential to excavate.

Development of a 3D modeling algorithm for tunnel deformation monitoring based on terrestrial laser scanning

Deformation monitoring is vital for tunnel engineering.Traditional monitoring techniques measure only a few data points,which is insufficient to understand the deformation of the entire tunnel.Terrestrial Laser Scanning(TLS)is a newly developed technique that can collect thousands of data points in a few minutes,with promising applications to tunnel deformation monitoring.The raw point cloud collected from TLS cannot display tunnel deformation;therefore,a new 3D modeling algorithm was developed for this purpose.The 3D modeling algorithm includes modules for preprocessing the point cloud,extracting the tunnel axis,performing coordinate transformations,performing noise reduction and generating the 3D model.Measurement results from TLS were compared to the results of total station and numerical simulation,confirming the reliability of TLS for tunnel deformation monitoring.Finally,a case study of the Shanghai West Changjiang Road tunnel is introduced,where TLS was applied to measure shield tunnel deformation over multiple sections.Settlement,segment dislocation and cross section convergence were measured and visualized using the proposed 3D modeling algorithm.

Building 3D CityGML models of mining industrial structures using integrated UAV and TLS point clouds

Mining industrial areas with anthropogenic engineering structures are one of the most distinctive features of the real world.3D models of the real world have been increasingly popular with numerous applications,such as digital twins and smart factory management.In this study,3D models of mining engineering structures were built based on the CityGML standard.For collecting spatial data,the two most popular geospatial technologies,namely UAV-SfM and TLS were employed.The accuracy of the UAV survey was at the centimeter level,and it satisfied the absolute positional accuracy requirement of creat-ing all levels of detail(LoD)according to the CityGML standard.Therefore,the UAV-SfM point cloud dataset was used to build LoD 2 models.In addition,the comparison between the UAV-SfM and TLS sub-clouds of facades and roofs indicates that the UAV-SfM and TLS point clouds of these objects are highly consistent,therefore,point clouds with a higher level of detail and accuracy provided by the integration of UAV-SfM and TLS were used to build LoD 3 models.The resulting 3D CityGML models include 39 buildings at LoD 2,and two mine shafts with hoistrooms,headframes,and sheave wheels at LoD3.

Trunk volume estimation of irregular shaped Populus euphratica riparian forest using TLS point cloud data and multivariate prediction models

Background: Trunk volume(Vt) is an essential parameter for estimating forest stand volume, biomass, and carbon sequestration potential. As the dominant tree species in desert riparian forests, Euphrates poplar(Populus euphratica) has a high proportion of irregularly shaped tree trunks along the Tarim River, NW China, where the habitat is very fragile owing to long-term water stress. This causes uncertainty in estimation accuracy as well as technical challenges for forest surveys. Our study aimed to acquire P. euphratica Vtusing terrestrial laser scanning(TLS) and to establish a species-specific Vtprediction model.Methods: A total of 240 individual trees were measured by TLS multiple-station in 12 sampling plots in three sections along the lower reaches of the Tarim River. Vtwas calculated by a definite integration method using trunk diameters(Di) at every 0.1-m tree height obtained from TLS, and all data were split randomly into two sets:70% of data were used to estimate the model parameter calibration, and the remaining 30% were used for model validation. Sixteen widely used candidate tree Vtestimation models were fitted to the TLS-measured Vtand tree structural parameter data, including tree height(H), diameter at breast height(DBH), and basal diameter(BD). All model performances were evaluated and compared by the statistical parameters of determination coefficient(R^(2)),root mean square error(RMSE), Bayesian information criterion(BIC), mean prediction error(ME), mean absolute error(MAE), and modeling efficiency(EF), and accordingly the best model was selected.Results: TLS point cloud reflection intensity(RI) has advantageous in the extraction of data from irregular tree trunk structures. The P. euphratica tree Vtvalues showed obvious differences at the same tree height(H). There was no significant correlation between Vtand H(R^(2)=0.11, P < 0.01), which reflected the irregularity of P. euphratica trunk shape in the study area. Among all the models, model(14): Vt=0.909DBH1.184H0.487BD0.836(R^(2)=0.97, RMSE=0.14) had the best prediction capability for irregularly shaped Vtwith the highest R^(2), BIC(-37.96), and EF(0.96), and produced a smaller ME(0.006) and MAE(1.177) compared to other models. The prediction accuracy was 93.18%.Conclusions: TLS point cloud RI has a potential for nondestructively measuring irregularly shaped trunk structures of P. euphratica and developed Vtprediction models. The multivariate models more effectively predicted Vtfor irregularly shaped trees compared to one-way and general volume models.

Natural forest ALS-TLS point cloud data registration without control points

Airborne laser scanning(ALS)and terrestrial laser scanning(TLS)has attracted attention due to their forest parameter investigation and research applications.ALS is limited to obtaining fi ne structure information below the forest canopy due to the occlusion of trees in natural forests.In contrast,TLS is unable to gather fi ne structure information about the upper canopy.To address the problem of incomplete acquisition of natural forest point cloud data by ALS and TLS on a single platform,this study proposes data registration without control points.The ALS and TLS original data were cropped according to sample plot size,and the ALS point cloud data was converted into relative coordinates with the center of the cropped data as the origin.The same feature point pairs of the ALS and TLS point cloud data were then selected to register the point cloud data.The initial registered point cloud data was fi nely and optimally registered via the iterative closest point(ICP)algorithm.The results show that the proposed method achieved highprecision registration of ALS and TLS point cloud data from two natural forest plots of Pinus yunnanensis Franch.and Picea asperata Mast.which included diff erent species and environments.An average registration accuracy of 0.06 m and 0.09 m were obtained for P.yunnanensis and P.asperata,respectively.

Point-cloud segmentation of individual trees in complex natural forest scenes based on a trunk-growth method

Forest resource management and ecological assessment have been recently supported by emerging technologies.Terrestrial laser scanning(TLS)is one that can be quickly and accurately used to obtain three-dimensional forest information,and create good representations of forest vertical structure.TLS data can be exploited for highly significant tasks,particularly the segmentation and information extraction for individual trees.However,the existing single-tree segmentation methods suffer from low segmentation accuracy and poor robustness,and hence do not lead to satisfactory results for natural forests in complex environments.In this paper,we propose a trunk-growth(TG)method for single-tree point-cloud segmentation,and apply this method to the natural forest scenes of Shangri-La City in Northwest Yunnan,China.First,the point normal vector and its Z-axis component are used as trunk-growth constraints.Then,the points surrounding the trunk are searched to account for regrowth.Finally,the nearest distributed branch and leaf points are used to complete the individual tree segmentation.The results show that the TG method can effectively segment individual trees with an average F-score of 0.96.The proposed method applies to many types of trees with various growth shapes,and can effectively identify shrubs and herbs in complex scenes of natural forests.The promising outcomes of the TG method demonstrate the key advantages of combining plant morphology theory and LiDAR technology for advancing and optimizing forestry systems.

Multiple forest structural elements are needed to promote beetle biomass, diversity and abundance

Background:Retention forestry is a management strategy aiming to mitigate biodiversity loss by retaining structural elements such as dead trees that would otherwise be removed.Here we analyze the biomass,diversity and abundance among forest beetles collected using window traps on 1281-ha forest sites reflecting gradients in the amount of structural elements in southwestern Germany.Results:We found that beetle biomass increased with mean diameter at breast height(a measure of tree size),and decreased with stand structural complexity.Biomass of individual feeding guilds responded differently to forest structural elements,namely lying deadwood,understory complexity,tree basal area and stand structural complexity.Beetle family diversity increased with the effective number of layers,i.e.1-m forest strata occupied by vegetation assessed via terrestrial laser scanning.Abundance of feeding guilds responded to only elevation and share of deciduous trees.Community composition in terms of biomass was structured by forest elements similar to biomass of individual feeding guilds,with the addition of lying deadwood.This differed from community composition in terms of abundance of feeding guilds,which was structured by primarily standing deadwood volume and share of deciduous trees.Conclusions:Our results show that biomass,diversity and abundance respond differently to forest structural elements.This suggests that the concurrent prioritization of multiple forest elements is needed to promote forest beetles,with more focus placed on the differing resource needs among feeding guilds.In addition,retention strategies should also consider the varying responses of beetle biodiversity metrics when assessing the importance of forest structural elements.

Fast registration of forest terrestrial laser scans using key points detected from crowns and stems

Registration of TLS data is an important prerequisite to overcome the limitations of occlusion.Most existing registration methods rely on stems to determine the transformation parameters.However,the complexity of the registration problem increases dramatically as the number of stems grows.It is tricky to reduce the stems and determine the valid ones that can provide reliable registration transformation without a knowledge of the two scans.This paper presents an automatic and fast registration of TLS point clouds in forest areas.It reduces stems by selecting from the overlap areas,which are recovered from the mode-based key points that are detected from crowns.The proposed method was tested in a managed forest in Finland,and was compared with the stem-based registration method without reducing stems.The experiments demonstrated that the mean rotation error was 2.09′,and the mean errors in horizontal and vertical translation were 1.13 and 7.21 cm,respectively.Compared with the stem-based method,the proposed method improves the registration efficiency significantly(818 s vs 96 s)and achieves similar results in terms of the mean registration errors(1.94′for rotation error,0.83 and 7.38 cm for horizontal and vertical translation error,respectively).

Automated registration of wide-baseline point clouds in forests using discrete overlap search

Forest is one of the most challenging environments to be recorded in a three-dimensional(3D)digitized geometrical representation,because of the size and the complexity of the environment and the data-acquisition constraints brought by on-site conditions.Previous studies have indicated that the data-acquisition pattern can have more influence on the registration results than other factors.In practice,the ideal short-baseline observations,i.e.,the dense collection mode,is rarely feasible,considering the low accessibility in forest environments and the commonly limited labor and time resources.The wide-baseline observations that cover a forest site using a few folds less observations than short-baseline observations,are therefore more preferable and commonly applied.Nevertheless,the wide-baseline approach is more challenging for data registration since it typically lacks the required sufficient overlaps between datasets.Until now,a robust automated registration solution that is independent of special hardware requirements has still been missing.That is,the registration accuracy is still far from the required level,and the information extractable from the merged point cloud using automated registration could not match that from the merged point cloud using manual registration.This paper proposes a discrete overlap search(DOS)method to find correspondences in the point clouds to solve the low-overlap problem in the wide-baseline point clouds.The proposed automatic method uses potential correspondences from both original data and selected feature points to reconstruct rough observation geometries without external knowledge and to retrieve precise registration parameters at data-level.An extensive experiment was carried out with 24 forest datasets of different conditions categorized in three difficulty levels.The performance of the proposed method was evaluated using various accuracy criteria,as well as based on data acquired from different hardware,platforms,viewing perspectives,and at different points of time.The proposed method achieved a 3D registration accuracy at a 0.50-cm level in all difficulty categories using static terrestrial acquisitions.In the terrestrial-aerial registration,data sets were collected from different sensors and at different points of time with scene changes,and a registration accuracy at the raw data geometric accuracy level was achieved.These results represent the highest automated registration accuracy and the strictest evaluation so far.The proposed method is applicable in multiple scenarios,such as 1)the global positioning of individual under-canopy observations,which is one of the main challenges in applying terrestrial observations lacking a global context,2)the fusion of point clouds acquired from terrestrial and aerial perspectives,which is required in order to achieve a complete forest observation,3)mobile mapping using a new stop-and-go approach,which solves the problems of lacking mobility and slow data collection in static terrestrial measurements as well as the data-quality issue in the continuous mobile approach.Furthermore,this work proposes a new error estimate that units all parameter-level errors into a single quantity and compensates for the downsides of the widely used parameter-and object-level error estimates;it also proposes a new deterministic point sets registration method as an alternative to the popular sampling methods.

Effects of local neighbourhood diversity on crown structure and productivity of individual trees in mature mixed-species forests

Background:Species-specific genotypic features,local neighbourhood interactions and resource supply strongly influence the tree stature and growth rate.In mixed-species forests,diversity-mediated biomass allocation has been suggested to be a fundamental mechanism underlying the positive biodiversity-productivity relationships.Empirical evidence,however,is rare about the impact of local neighbourhood diversity on tree characteristics analysed at a very high level of detail.To address this issue we analysed these effects on the individual-tree crown architecture and tree productivity in a mature mixed forest in northern Germany.Methods:Our analysis considers multiple target tree species across a local neighbourhood species richness gradient ranging from 1 to 4.We applied terrestrial laser scanning to quantify a large number of individual mature trees(N=920)at very high accuracy.We evaluated two different neighbour inclusion approaches by analysing both a fixed radius selection procedure and a selection based on overlapping crowns.Results and conclusions:We show that local neighbourhood species diversity significantly increases crown dimension and wood volume of target trees.Moreover,we found a size-dependency of diversity effects on tree productivity(basal area and wood volume increment)with positive effects for large-sized trees(diameter at breast height(DBH)>40 cm)and negative effects for small-sized(DBH<40 cm)trees.In our analysis,the neighbour inclusion approach has a significant impact on the outcome.For scientific studies and the validation of growth models we recommend a neighbour selection by overlapping crowns,because this seems to be the relevant scale at which local neighbourhood interactions occur.Because local neighbourhood diversity promotes individual-tree productivity in mature European mixed-species forests,we conclude that a small-scale species mixture should be considered in management plans.

Analysis of the displacements of pipeline overpasses based on geodetic monitoring results

There are many approaches to address geospatial monitoring of pipeline overpasses,among which the most widespread methods are terrestrial laser scanning and total station measurements.However,there is a problem in comparing the geospatial monitoring data collected by different methods in different epochs.The main task of this work is to find the correspondence between points in different epochs.The total station measurements are carried out in specific discrete points of the pipeline overpass.In contrast,terrestrial laser scanning allows the collection of the whole data set without fixing specific point co-ordinates.In order to compare different data in different epochs,it is necessary to select a relevant presentation of the monitoring results(reference model)and specify appropriate criteria for quality inspection.In general,a pipeline can be presented as a spatial curve.In this study,two types of reference models are considered:cubic splines and Bezier curves.These models are examined for the monitoring of two gas pipeline overpasses.The first measurement epoch is accomplished by the terrestrial laser scanning,and the second measurement epoch is completed by the total station.The reference models are simulated by Matlab coding.The preliminary accuracy of ground laser scanning and total station mea-surement is selected as the criterion of quality inspection.The simulation and comparison results provide the evidence that the correct selection of reference model is a crucial component of successful geospatial monitoring.The results show that the Hermite splines are effective in the comparison of different data sets.These splines present the interpolation accuracy compatible with measurement accuracy,i.e.,15-20 mm for spatial displacement determination.

High-precision measurements of the inter-annual evolution for Urumqi Glacier No.1 in eastern Tien Shan,China

High-precision measuring of glacier evolution remains a challenge as the available global and regional remote sensing techniques cannot satisfactorily capture the local-scale processes of most small-and medium-sized mountain glaciers.In this study,we use a high-precision local remote sensing technique,long-range terrestrial laser scanning(TLS),to measure the evolution of Urumqi Glacier No.1 at an annual scale.We found that the dense point clouds derived from the TLS survey can be used to reconstruct glacier surface terrain,with certain details,such as depressions,debris-covered areas,and supra-glacial drainages can be distinguished.The glacier experienced pronounced thickness thinning and continuous retreat over the last four mass-balance years(2015−2019).The mean surface slope of Urumqi Glacier No.1 gradually steepened,which may increase the removal of glacier mass.The glacier was deeply incised by two very prominent primary supra-glacial rivers,and those rivers presented a widening trend.Extensive networks of supra-glacial channels had a significant impact on accelerated glacier mass loss.High-precision measuring is of vital importance to understanding the annual evolution of this type of glacier.

Methodology for Extraction of Tunnel Cross-Sections Using Dense Point Cloud Data

Tunnel deformation monitoring is a crucial task to evaluate tunnel stability during the metro operation period.Terrestrial Laser Scanning(TLS)can collect high density and high accuracy point cloud data in a few minutes as an innovation technique,which provides promising applications in tunnel deformation monitoring.Here,an efficient method for extracting tunnel cross-sections and convergence analysis using dense TLS point cloud data is proposed.First,the tunnel orientation is determined using principal component analysis(PCA)in the Euclidean plane.Two control points are introduced to detect and remove the unsuitable points by using point cloud division and then the ground points are removed by defining an elevation value width of 0.5 m.Next,a z-score method is introduced to detect and remove the outlies.Because the tunnel cross-section’s standard shape is round,the circle fitting is implemented using the least-squares method.Afterward,the convergence analysis is made at the angles of 0°,30°and 150°.The proposed approach’s feasibility is tested on a TLS point cloud of a Nanjing subway tunnel acquired using a FARO X330 laser scanner.The results indicate that the proposed methodology achieves an overall accuracy of 1.34 mm,which is also in agreement with the measurements acquired by a total station instrument.The proposed methodology provides new insights and references for the applications of TLS in tunnel deformation monitoring,which can also be extended to other engineering applications.

Co-developing an international TLS network for the 3D ecological understanding of global trees:System architecture,remote sensing models,and functional prospects

Trees are spread worldwide,as the watchmen that experience the intricate ecological effects caused by various environmental factors.In order to better understand such effects,it is preferential to achieve finely and fully mapped global trees and their environments.For this task,aerial and satellite-based remote sensing(RS)methods have been developed.However,a critical branch regarding the apparent forms of trees has significantly fallen behind due to the technical deficiency found within their globalscale surveying methods.Now,terrestrial laser scanning(TLS),a state-of-the-art RS technology,is useful for the in situ three-dimensional(3D)mapping of trees and their environments.Thus,we proposed co-developing an international TLS network as a macroscale ecotechnology to increase the 3D ecological understanding of global trees.First,we generated the system architecture and tested the available RS models to deepen its ground stakes.Then,we verified the ecotechnology regarding the identification of its theoretical feasibility,a review of its technical preparations,and a case testification based on a prototype we designed.Next,we conducted its functional prospects by previewing its scientific and technical potentials and its functional extensibility.Finally,we summarized its technical and scientific challenges,which can be used as the cutting points to promote the improvement of this technology in future studies.Overall,with the implication of establishing a novel cornerstone-sense ecotechnology,the co-development of an international TLS network can revolutionize the 3D ecological understanding of global trees and create new fields of research from 3D global tree structural ecology to 3D macroecology.