scholarly journals Processing Point Clouds Using Simulated Physical Processes as Replacements of Conventional Mathematically Based Procedures: A Theoretical Virtual Measurement for Stem Volume

2021 ◽  
Vol 13 (22) ◽  
pp. 4627
Author(s):  
Zhichao Wang ◽  
Yan-Jun Shen ◽  
Xiaoyuan Zhang ◽  
Yao Zhao ◽  
Christiane Schmullius
Keyword(s):  
Data Processing ◽  
Virtual Water ◽  
Point Clouds ◽  
Stem Volume ◽  
Measurement Instruments ◽  
Physical Processes ◽  
Water Displacement ◽  
Solid Objects ◽  
Mathematical Expressions ◽  
Data Points

Conventional mathematically based procedures in forest data processing have some problems, such as deviations between the natural tree and the tree described using mathematical expressions, and manual selection of equations and parameters. These problems are rooted at the algorithmic level. Our solution for these problems was to process raw data using simulated physical processes as replacements of conventional mathematically based procedures. In this mechanism, we treated the data points as solid objects and formed virtual trees. Afterward, the tree parameters were obtained by the external physical detection, i.e., computational virtual measurement (CVM). CVM simulated the physical behavior of measurement instruments in reality to measure virtual trees. Namely, the CVM process was a pure (simulated) physical process. In order to verify our assumption of CVM, we developed the virtual water displacement (VWD) application. VWD could extract stem volume from an artificial stem (consisted of 2000 points) by simulating the physical scenario of a water displacement method. Compared to conventional mathematically based methods, VWD removed the need to predefine the shape of the stem and minimized human interference. That was because VWD utilized the natural contours of the stem through the interaction between the point cloud and the virtual water molecules. The results showed that the stem volume measured using VWD was 29,636 cm3 (overestimation at 6.0%), where the true volume was 27,946 cm3. The overall feasibility of CVM was proven by the successful development of VWD. Meanwhile, technical experiences, current limitations, and potential solutions were discussed. We considered CVM as a generic method that focuses the objectivity at the algorithmic level, which will become a noteworthy development direction in the field of forest data processing in the future.

scholarly journals Revealing Changes in the Stem Form and Volume Allocation in Diverse Boreal Forests Using Two-Date Terrestrial Laser Scanning

Forests ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 835
Author(s):  
Ville Luoma ◽  
Tuomas Yrttimaa ◽  
Ville Kankare ◽  
Ninni Saarinen ◽  
Jiri Pyörälä ◽  
...  
Keyword(s):  
Tree Growth ◽  
Point Cloud ◽  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Point Clouds ◽  
Stem Volume ◽  
Accurate Information ◽  
Stem Form ◽  
Monitoring Period ◽  
Significant Difference

Tree growth is a multidimensional process that is affected by several factors. There is a continuous demand for improved information on tree growth and the ecological traits controlling it. This study aims at providing new approaches to improve ecological understanding of tree growth by the means of terrestrial laser scanning (TLS). Changes in tree stem form and stem volume allocation were investigated during a five-year monitoring period. In total, a selection of attributes from 736 trees from 37 sample plots representing different forest structures were extracted from taper curves derived from two-date TLS point clouds. The results of this study showed the capability of point cloud-based methods in detecting changes in the stem form and volume allocation. In addition, the results showed a significant difference between different forest structures in how relative stem volume and logwood volume increased during the monitoring period. Along with contributing to providing more accurate information for monitoring purposes in general, the findings of this study showed the ability and many possibilities of point cloud-based method to characterize changes in living organisms in particular, which further promote the feasibility of using point clouds as an observation method also in ecological studies.

scholarly journals Accuracy of common stem volume formulae using terrestrial photogrammetric point clouds: a case study with savanna trees in Benin

2021 ◽  
Author(s):  
Hospice A. Akpo ◽  
Gilbert Atindogbé ◽  
Maxwell C. Obiakara ◽  
Arios B. Adjinanoukon ◽  
Madaï Gbedolo ◽  
...  
Keyword(s):  
Point Clouds ◽  
Stem Volume ◽  
Individual Tree ◽  
Volume Calculation ◽  
Tropical Regions ◽  
Solid Of Revolution ◽  
Taper Function ◽  
Geometric Solids ◽  
Traditional Approaches ◽  
Tree Stem

AbstractRecent applications of digital photogrammetry in forestry have highlighted its utility as a viable mensuration technique. However, in tropical regions little research has been done on the accuracy of this approach for stem volume calculation. In this study, the performance of Structure from Motion photogrammetry for estimating individual tree stem volume in relation to traditional approaches was evaluated. We selected 30 trees from five savanna species growing at the periphery of the W National Park in northern Benin and measured their circumferences at different heights using traditional tape and clinometer. Stem volumes of sample trees were estimated from the measured circumferences using nine volumetric formulae for solids of revolution, including cylinder, cone, paraboloid, neiloid and their respective fustrums. Each tree was photographed and stem volume determined using a taper function derived from tri-dimensional stem models. This reference volume was compared with the results of formulaic estimations. Tree stem profiles were further decomposed into different portions, approximately corresponding to the stump, butt logs and logs, and the suitability of each solid of revolution was assessed for simulating the resulting shapes. Stem volumes calculated using the fustrums of paraboloid and neiloid formulae were the closest to reference volumes with a bias and root mean square error of 8.0% and 24.4%, respectively. Stems closely resembled fustrums of a paraboloid and a neiloid. Individual stem portions assumed different solids as follows: fustrums of paraboloid and neiloid were more prevalent from the stump to breast height, while a paraboloid closely matched stem shapes beyond this point. Therefore, a more accurate stem volumetric estimate was attained when stems were considered as a composite of at least three geometric solids.

scholarly journals Estimating tree stem diameters and volume from smartphone photogrammetric point clouds

2019 ◽  
Vol 93 (3) ◽  
pp. 411-429 ◽  
Author(s):  
Maria Immacolata Marzulli ◽  
Pasi Raumonen ◽  
Roberto Greco ◽  
Manuela Persia ◽  
Patrizia Tartarino
Keyword(s):  
Low Cost ◽  
Three Dimensional ◽  
Laser Scanner ◽  
Point Clouds ◽  
Stem Volume ◽  
Forest Plot ◽  
3D Point Clouds ◽  
Dense Point ◽  
Minimum Number ◽  
Scale Point

Abstract Methods for the three-dimensional (3D) reconstruction of forest trees have been suggested for data from active and passive sensors. Laser scanner technologies have become popular in the last few years, despite their high costs. Since the improvements in photogrammetric algorithms (e.g. structure from motion—SfM), photographs have become a new low-cost source of 3D point clouds. In this study, we use images captured by a smartphone camera to calculate dense point clouds of a forest plot using SfM. Eighteen point clouds were produced by changing the densification parameters (Image scale, Point density, Minimum number of matches) in order to investigate their influence on the quality of the point clouds produced. In order to estimate diameter at breast height (d.b.h.) and stem volumes, we developed an automatic method that extracts the stems from the point cloud and then models them with cylinders. The results show that Image scale is the most influential parameter in terms of identifying and extracting trees from the point clouds. The best performance with cylinder modelling from point clouds compared to field data had an RMSE of 1.9 cm and 0.094 m3, for d.b.h. and volume, respectively. Thus, for forest management and planning purposes, it is possible to use our photogrammetric and modelling methods to measure d.b.h., stem volume and possibly other forest inventory metrics, rapidly and without felling trees. The proposed methodology significantly reduces working time in the field, using ‘non-professional’ instruments and automating estimates of dendrometric parameters.

scholarly journals RECONSTRUCTION OF INDOOR MODELS USING POINT CLOUDS GENERATED FROM SINGLE-LENS REFLEX CAMERAS AND DEPTH IMAGES

2015 ◽  
Vol XL-4/W5 ◽  
pp. 99-102
Author(s):  
F. Tsai ◽  
T.-S. Wu ◽  
I.-C. Lee ◽  
H. Chang ◽  
A. Y. S. Su
Keyword(s):  
Data Processing ◽  
Data Acquisition ◽  
Three Dimensional ◽  
Point Clouds ◽  
Data Acquisition System ◽  
Acquisition System ◽  
Indoor Environments ◽  
Single Lens ◽  
Processing Procedure ◽  
Data Processing Procedure

This paper presents a data acquisition system consisting of multiple RGB-D sensors and digital single-lens reflex (DSLR) cameras. A systematic data processing procedure for integrating these two kinds of devices to generate three-dimensional point clouds of indoor environments is also developed and described. In the developed system, DSLR cameras are used to bridge the Kinects and provide a more accurate ray intersection condition, which takes advantage of the higher resolution and image quality of the DSLR cameras. Structure from Motion (SFM) reconstruction is used to link and merge multiple Kinect point clouds and dense point clouds (from DSLR color images) to generate initial integrated point clouds. Then, bundle adjustment is used to resolve the exterior orientation (EO) of all images. Those exterior orientations are used as the initial values to combine these point clouds at each frame into the same coordinate system using Helmert (seven-parameter) transformation. Experimental results demonstrate that the design of the data acquisition system and the data processing procedure can generate dense and fully colored point clouds of indoor environments successfully even in featureless areas. The accuracy of the generated point clouds were evaluated by comparing the widths and heights of identified objects as well as coordinates of pre-set independent check points against in situ measurements. Based on the generated point clouds, complete and accurate three-dimensional models of indoor environments can be constructed effectively.

scholarly journals Susceptibility of surface texture parameters to acquisition point clouds with digital data processing of data from optical measuring systems

2019 ◽  
Vol 252 ◽  
pp. 03020 ◽  
Author(s):  
Emilia Bachtiak-Radka ◽  
Sara Dudzińska ◽  
Daniel Grochała ◽  
Stefan Berczyński
Keyword(s):  
Data Processing ◽  
Surface Texture ◽  
Surface Characteristics ◽  
Point Clouds ◽  
Digital Processing ◽  
Digital Data ◽  
Measuring Systems ◽  
Optical Measuring ◽  
Digital Data Processing ◽  
The Impact

Digital processing of the recorded point clouds on innovative surfaces could facilitate the operator’s planning of the metrological process and give more freedom in the assessment of the surface texture. The current state of knowledge about surface characteristics, precision and quality of measurements and especially the repeatability of measurements – not only in the laboratory environment but also in the industry pose a big challenge. The paper presents research works related to the identification of the impact of the method of acquisition point clouds using digital data processing on surface texture. The main assumption of the paper was to carry out, according to the prepared plan of the experiment, the series of sample measurements with the use of the optical measuring systems AltiSurf A520 in the Laboratory of Surface Topography at the West Pomeranian University of Technology in Szczecin. The next task was to determine the impact of the digital data processing strategy in order to identify the significance of the impact (conditions and methods of filtration), which in practice largely determines the repeatability and reproducibility of the parameter values of the geometry surface structure.

Data Processing of Point Clouds for Object Detection for Structural Engineering Applications

2013 ◽  
Vol 28 (7) ◽  
pp. 495-508 ◽  
Author(s):  
Sara B. Walsh ◽  
Daniel J. Borello ◽  
Burcu Guldur ◽  
Jerome F. Hajjar
Keyword(s):  
Data Processing ◽  
Object Detection ◽  
Structural Engineering ◽  
Point Clouds ◽  
Engineering Applications

A New Method of Data Processing Based on Geomagic Studio and Imageware in Reverse Modeling of Equipment Parts

2011 ◽  
Vol 120 ◽  
pp. 89-93
Author(s):  
Qun Zhang Tu ◽  
Jian Xun Zhao ◽  
Da Zhen Su ◽  
Jun Yan
Keyword(s):  
Data Processing ◽  
Point Clouds ◽  
New Method ◽  
Practical Application ◽  
Processing Flow

The processing flow of data clouds is analyzed concretely. Based on software Geomagic Studio and Imageware, a new method of data processing for point clouds is put forward, and the scheme of data processing is designed. Taking a mechanism part for example, the practical application is performed, and proves the feasibility and practicality of the method.

scholarly journals Data processing workflows from low-cost digital survey to various applications: three case studies of Chinese historic architecture

2015 ◽  
Vol XL-5/W7 ◽  
pp. 409-416 ◽  
Author(s):  
Z. Sun ◽  
Y. K. Cao
Keyword(s):  
Structural Analysis ◽  
Data Processing ◽  
Case Studies ◽  
Laser Scanning ◽  
Low Cost ◽  
Point Clouds ◽  
Element Analysis ◽  
Prime Concern ◽  
Architectural Preservation ◽  
Digital Survey

The paper focuses on the versatility of data processing workflows ranging from BIM-based survey to structural analysis and reverse modeling. In China nowadays, a large number of historic architecture are in need of restoration, reinforcement and renovation. But the architects are not prepared for the conversion from the booming AEC industry to architectural preservation. As surveyors working with architects in such projects, we have to develop efficient low-cost digital survey workflow robust to various types of architecture, and to process the captured data for architects. Although laser scanning yields high accuracy in architectural heritage documentation and the workflow is quite straightforward, the cost and portability hinder it from being used in projects where budget and efficiency are of prime concern. We integrate Structure from Motion techniques with UAV and total station in data acquisition. The captured data is processed for various purposes illustrated with three case studies: the first one is as-built BIM for a historic building based on registered point clouds according to Ground Control Points; The second one concerns structural analysis for a damaged bridge using Finite Element Analysis software; The last one relates to parametric automated feature extraction from captured point clouds for reverse modeling and fabrication.

scholarly journals A Novel Recursive Non-Parametric DBSCAN Algorithm for 3D Data Analysis with an Application in Rockfall Detection

2021 ◽  
Vol 16 (4) ◽  
pp. 579-587
Author(s):  
Pitisit Dillon ◽  
Pakinee Aimmanee ◽  
Akihiko Wakai ◽  
Go Sato ◽  
Hoang Viet Hung ◽  
...  
Keyword(s):  
Point Cloud ◽  
Crack Detection ◽  
Spatial Clustering ◽  
Point Clouds ◽  
Divide And Conquer ◽  
Dbscan Algorithm ◽  
3D Data ◽  
Data Points ◽  
Clustering Data ◽  
Better Than

The density-based spatial clustering of applications with noise (DBSCAN) algorithm is a well-known algorithm for spatial-clustering data point clouds. It can be applied to many applications, such as crack detection, rockfall detection, and glacier movement detection. Traditional DBSCAN requires two predefined parameters. Suitable values of these parameters depend upon the distribution of the input point cloud. Therefore, estimating these parameters is challenging. This paper proposed a new version of DBSCAN that can automatically customize the parameters. The proposed method consists of two processes: initial parameter estimation based on grid analysis and DBSCAN based on the divide-and-conquer (DC-DBSCAN) approach, which repeatedly performs DBSCAN on each cluster separately and recursively. To verify the proposed method, we applied it to a 3D point cloud dataset that was used to analyze rockfall events at the Puiggcercos cliff, Spain. The total number of data points used in this study was 15,567. The experimental results show that the proposed method is better than the traditional DBSCAN in terms of purity and NMI scores. The purity scores of the proposed method and the traditional DBSCAN method were 96.22% and 91.09%, respectively. The NMI scores of the proposed method and the traditional DBSCAN method are 0.78 and 0.49, respectively. Also, it can detect events that traditional DBSCAN cannot detect.

Study on 3D Point Clouds Accuracy of Elongated Object Reconstruction in Close Range – Comparison of Different Software

2017 ◽  
Author(s):  
Grzegorz Gabara ◽  
Piotr Sawicki
Keyword(s):  
Data Processing ◽  
Test Object ◽  
Point Clouds ◽  
Geometric Parameters ◽  
Digital Data ◽  
Railway Track ◽  
Object Reconstruction ◽  
3D Point Clouds ◽  
Dense Point ◽  
Close Range

The image based point clouds generated from multiple different oriented photos enable 3D object reconstruction in a variety spectrum of close range applications. The paper presents the results of testing the accuracy the image based point clouds generated in disadvantageous conditions of digital photogrammetric data processing. The subject of the study was a long shaped object, i.e. the horizontal and rectilinear section of the railway track. DSLR Nikon D5100 camera, 16MP, equipped with the zoom lens (f = 18 ÷ 55mm), was used to acquire the block of terrestrial convergent and very oblique photos at different scales, with the full longitudinal overlap. The point clouds generated from digital images, automatic determination of the interior orientation parameters, the spatial orientation of photos and 3D distribution of discrete points were obtained using the successively tested software: RealityCapture, Photoscan, VisualSFM+SURE and iWitness+SURE. The dense point clouds of the test object generated with the use of RealityCapture and PhotoScan applications were filtered using MeshLab application. The geometric parameters of test object were determined by means of CloudCompare software. The image based dense point clouds allow, in the case of disadvantageous conditions of photogrammetric digital data processing, to determine the geometric parameters of a close range elongated object with the high accuracy (mXYZ < 1 mm).

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