scholarly journals DEM-Based UAV Flight Planning for 3D Mapping of Geosites: The Case of Olympus Tectonic Window, Lesvos, Greece

2021 ◽  
Vol 10 (8) ◽  
pp. 535
Author(s):  
Ermioni-Eirini Papadopoulou ◽  
Christos Vasilakos ◽  
Nikolaos Zouros ◽  
Nikolaos Soulakellis
Keyword(s):  
Three Dimensional ◽  
Surface Profile ◽  
Point Clouds ◽  
Integrated System ◽  
Slope Aspect ◽  
3D Mapping ◽  
Flight Planning ◽  
Dense Point ◽  
Tectonic Window ◽  
Elevation Model

Geosites are an important part of geoheritage, thus their detailed mapping is crucial for their management, protection and promotion processes. However, there is no specific approach to three-dimensional (3D) mapping of geosites and a full investigation is required, considering the current advances in the science of Geoinformatics and the need for setting up an integrated system that will suggest a suitable way of mapping areas of geological significance. The main purpose of this study is to explore new approaches to the 3D mapping of geosites, where the unmanned aerial vehicles’ (UAVs) flight planning is based on the digital elevation model (DEM). The case study that is being examined is the tectonic window of Mount Olympus, located in the southeast of Lesvos island, Greece. In this paper, a methodology has been developed to create flight plans for geosite 3D mapping. This methodology consists of three main stages: a) flight planning based on SRTM-DEM, b) data acquisition and image-based 3D modelling, and c) comparison (flight plans and results). A semi-automated algorithm was developed for designing the flights, taking into account the topography of the mapped area (slope, aspect, elevation) and the final cartographic derivatives. The flight plans were compared with each other in levels of data collection, flight characteristics and their results. The results of this study are dense point clouds, DEMs and orthophotomaps. The algorithms that have been used for the comparison of point clouds were I) surface density, II) number of neighbours (NN), and III) roughness and surface profile. The conclusion drawn from this study is that the DEM is a valuable source of information that can be used in designing flight plans specially shaped on the topography of each geosite.

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 Visualizations of the Doblar Accumulation Basin Based on the UAV Survey

2019 ◽  
Vol 1 ◽  
pp. 1-7
Author(s):  
Klemen Kozmus Trajkovski ◽  
Gašper Štebe ◽  
Dušan Petrovič
Keyword(s):  
3D Model ◽  
Weather Conditions ◽  
Point Clouds ◽  
Water Levels ◽  
Contour Lines ◽  
Digital Elevation ◽  
Short Period ◽  
Dense Point ◽  
Aerial Vehicle ◽  
Elevation Model

<p><strong>Abstract.</strong> Our research is based on a large case study of Unmanned Aerial Vehicle (UAV) surveys, modelling and visualizations of the Doblar accumulation basin. The various approaches for UAV surveying of large, demanding terrain configurations, and the benefits of surveying products used as a basis for other interdisciplinary hydrological and environmental services were researched. The demanding mountainous terrain, the steep slopes and deep and narrow streams required detailed pre-planning of the survey, including the pre-survey terrain overview. The accumulation basin was emptied merely for a short period; thus, the survey was performed in unfavourable weather conditions, which included coldness, snowfall and wind. Point clouds were generated and georeferenced from the 4377 recorded photos. The dense point cloud contained approximately 222 million points in the medium setting and more than a billion in the high setting. A 3D model was built from the data. This became the basis for numerous further analyses and for the presentation using cartographic principles: a digital elevation model with a resolution of 10&amp;thinsp;cm, an orthophoto with a resolution of 10&amp;thinsp;cm, a 3D model draped with orthophoto, contour lines with a 1&amp;thinsp;m interval, topographic profiles, calculations of volumes at different water levels, a flythrough, augmented reality and a video simulation of the water level changes. The model can also serve as a basis for hydraulic and environmental analysis and simulations or used for analyses of the accumulation and deposition of river material compared with previous and future surveys.</p>

scholarly journals A SMARTPHONE-BASED 3D PIPELINE FOR THE CREATIVE INDUSTRY &ndash; THE REPLICATE EU PROJECT

2017 ◽  
Vol XLII-2/W3 ◽  
pp. 535-541 ◽  
Author(s):  
E. Nocerino ◽  
F. Lago ◽  
D. Morabito ◽  
F. Remondino ◽  
L. Porzi ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Point Clouds ◽  
First Year ◽  
Automated Generation ◽  
Dense Point ◽  
Modelling Techniques ◽  
Eu Project ◽  
Selection Of ◽  
Made In

During the last two decades we have witnessed great improvements in ICT hardware and software technologies. Three-dimensional content is starting to become commonplace now in many applications. Although for many years 3D technologies have been used in the generation of assets by researchers and experts, nowadays these tools are starting to become commercially available to every citizen. This is especially the case for smartphones, that are powerful enough and sufficiently widespread to perform a huge variety of activities (e.g. paying, calling, communication, photography, navigation, localization, etc.), including just very recently the possibility of running 3D reconstruction pipelines. The REPLICATE project is tackling this particular issue, and it has an ambitious vision to enable ubiquitous 3D creativity via the development of tools for mobile 3D-assets generation on smartphones/tablets. This article presents the REPLICATE project’s concept and some of the ongoing activities, with particular attention being paid to advances made in the first year of work. Thus the article focuses on the system architecture definition, selection of optimal frames for 3D cloud reconstruction, automated generation of sparse and dense point clouds, mesh modelling techniques and post-processing actions. Experiments so far were concentrated on indoor objects and some simple heritage artefacts, however, in the long term we will be targeting a larger variety of scenarios and communities.

scholarly journals Measuring Three-Dimensional Temperature Distributions in Steel–Concrete Composite Slabs Subjected to Fire Using Distributed Fiber Optic Sensors

Sensors ◽  
2020 ◽  
Vol 20 (19) ◽  
pp. 5518
Author(s):  
Yi Bao ◽  
Matthew S. Hoehler ◽  
Christopher M. Smith ◽  
Matthew Bundy ◽  
Genda Chen
Keyword(s):  
Fiber Optic ◽  
Three Dimensional ◽  
Thermal Response ◽  
Point Clouds ◽  
Fiber Optic Sensors ◽  
Distributed Sensors ◽  
Temperature Distributions ◽  
Composite Slabs ◽  
Spatially Distributed ◽  
Dense Point

Detailed information about temperature distribution can be important to understand structural behavior in fire. This study develops a method to image three-dimensional temperature distributions in steel–concrete composite slabs using distributed fiber optic sensors. The feasibility of the method is explored using six 1.2 m × 0.9 m steel–concrete composite slabs instrumented with distributed sensors and thermocouples subjected to fire for over 3 h. Dense point clouds of temperature in the slabs were measured using the distributed sensors. The results show that the distributed sensors operated at material temperatures up to 960 °C with acceptable accuracy for many structural fire applications. The measured non-uniform temperature distributions indicate a spatially distributed thermal response in steel–concrete composite slabs, which can only be adequately captured using approaches that provide a high density of through-depth data points.

Development on Filtering Algorithms of Airborne LiDAR Point Clouds

2012 ◽  
Vol 226-228 ◽  
pp. 1892-1898
Author(s):  
Jian Qing Shi ◽  
Ting Chen Jiang ◽  
Ming Lian Jiao
Keyword(s):  
Remote Sensing ◽  
Laser Scanning ◽  
Three Dimensional ◽  
Point Clouds ◽  
Airborne Lidar ◽  
Filtering Algorithms ◽  
Filtering Algorithm ◽  
Digital Elevation ◽  
City Model ◽  
Elevation Model

Airborne LiDAR is a new kind of surveying technology of remote sensing which developed rapidly during recent years. Raw laser scanning point clouds data include terrain points, building points, vegetation points, outlier points, etc.. In order to generate digital elevation model (DEM) and three-dimensional city model,these point clouds data must be filtered. Mathematical morphology based filtering algorithm, slope based filtering algorithm, TIN based filtering algorithm, moving surface based filtering algorithm, scanning lines based filtering algorithm and so on several representative filtering algorithms for LiDAR point clouds data have been introduced and discussed and contrasted in this paper. Based on these algorithms summarize the studying progresss about the filtering algorithm of airborne LiDAR point clouds data in home and abroad. In the end, the paper gives an expectation which will provides a reference for the following relative study.

scholarly journals AUOTOMATIC CLASSIFICATION OF POINT CLOUDS EXTRACTED FROM ULTRACAM STEREO IMAGES

2015 ◽  
Vol XL-1-W5 ◽  
pp. 493-496 ◽  
Author(s):  
M. Modiri ◽  
M. Masumi ◽  
A. Eftekhari
Keyword(s):  
Image Matching ◽  
Vegetation Index ◽  
Region Growing ◽  
Point Clouds ◽  
Maximum Height ◽  
Color Characteristics ◽  
Matching Technique ◽  
Dense Point ◽  
Elevation Model

Automatic extraction of building roofs, street and vegetation are a prerequisite for many GIS (Geographic Information System) applications, such as urban planning and 3D building reconstruction. Nowadays with advances in image processing and image matching technique by using feature base and template base image matching technique together dense point clouds are available. Point clouds classification is an important step in automatic features extraction. Therefore, in this study, the classification of point clouds based on features color and shape are implemented. <br><br> We use two images by proper overlap getting by Ultracam-x camera in this study. The images are from Yasouj in IRAN. It is semi-urban area by building with different height. Our goal is classification buildings and vegetation in these points. <br><br> In this article, an algorithm is developed based on the color characteristics of the point’s cloud, using an appropriate DEM (Digital Elevation Model) and points clustering method. So that, firstly, trees and high vegetation are classified by using the point’s color characteristics and vegetation index. Then, bare earth DEM is used to separate ground and non-ground points. <br><br> Non-ground points are then divided into clusters based on height and local neighborhood. One or more clusters are initialized based on the maximum height of the points and then each cluster is extended by applying height and neighborhood constraints. Finally, planar roof segments are extracted from each cluster of points following a region-growing technique.

scholarly journals Three-dimensional discrete element modelling of rubble masonry structures from dense point clouds

2020 ◽  
Vol 119 ◽  
pp. 103365
Author(s):  
Nicko Kassotakis ◽  
Vasilis Sarhosis ◽  
Belen Riveiro ◽  
Borja Conde ◽  
Antonio Maria D'Altri ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Point Clouds ◽  
Discrete Element ◽  
Discrete Element Modelling ◽  
Masonry Structures ◽  
Element Modelling ◽  
Dense Point

scholarly journals Rail Track Detection and Projection-Based 3D Modeling from UAV Point Cloud

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5220
Author(s):  
Shima Sahebdivani ◽  
Hossein Arefi ◽  
Mehdi Maboudi
Keyword(s):  
3D Modeling ◽  
Point Cloud ◽  
3D Model ◽  
Three Dimensional ◽  
Point Clouds ◽  
Rail Track ◽  
Three Dimensional Modeling ◽  
Railway Industry ◽  
Dense Point ◽  
Uav Images

The expansion of the railway industry has increased the demand for the three-dimensional modeling of railway tracks. Due to the increasing development of UAV technology and its application advantages, in this research, the detection and 3D modeling of rail tracks are investigated using dense point clouds obtained from UAV images. Accordingly, a projection-based approach based on the overall direction of the rail track is proposed in order to generate a 3D model of the railway. In order to extract the railway lines, the height jump of points is evaluated in the neighborhood to select the candidate points of rail tracks. Then, using the RANSAC algorithm, line fitting on these candidate points is performed, and the final points related to the rail are identified. In the next step, the pre-specified rail piece model is fitted to the rail points through a projection-based process, and the orientation parameters of the model are determined. These parameters are later improved by fitting the Fourier curve, and finally a continuous 3D model for all of the rail tracks is created. The geometric distance of the final model from rail points is calculated in order to evaluate the modeling accuracy. Moreover, the performance of the proposed method is compared with another approach. A median distance of about 3 cm between the produced model and corresponding point cloud proves the high quality of the proposed 3D modeling algorithm in this study.

scholarly journals Super Edge 4-Points Congruent Sets-Based Point Cloud Global Registration

2021 ◽  
Vol 13 (16) ◽  
pp. 3210
Author(s):  
Shikun Li ◽  
Ruodan Lu ◽  
Jianya Liu ◽  
Liang Guo
Keyword(s):  
Three Dimensional ◽  
Initial Point ◽  
Point Clouds ◽  
Search Space ◽  
Frame Rate ◽  
Registration Method ◽  
Dense Point ◽  
Coarse Registration ◽  
Fine Registration ◽  
Original Point

With the acceleration in three-dimensional (3D) high-frame-rate sensing technologies, dense point clouds collected from multiple standpoints pose a great challenge for the accuracy and efficiency of registration. The combination of coarse registration and fine registration has been extensively promoted. Unlike the requirement of small movements between scan pairs in fine registration, coarse registration can match scans with arbitrary initial poses. The state-of-the-art coarse methods, Super 4-Points Congruent Sets algorithm based on the 4-Points Congruent Sets, improves the speed of registration to a linear order via smart indexing. However, the lack of reduction in the scale of original point clouds limits the application. Besides, the coplanarity of registration bases prevents further reduction of search space. This paper proposes a novel registration method called the Super Edge 4-Points Congruent Sets to address the above problems. The proposed algorithm follows a three-step procedure, including boundary segmentation, overlapping regions extraction, and bases selection. Firstly, an improved method based on vector angle is used to segment the original point clouds aiming to thin out the scale of the initial point clouds. Furthermore, overlapping regions extraction is executed to find out the overlapping regions on the contour. Finally, the proposed method selects registration bases conforming to the distance constraints from the candidate set without consideration about coplanarity. Experiments on various datasets with different characteristics have demonstrated that the average time complexity of the proposed algorithm is improved by 89.76%, and the accuracy is improved by 5 mm on average than the Super 4-Points Congruent Sets algorithm. More encouragingly, the experimental results show that the proposed algorithm can be applied to various restrictive cases, such as few overlapping regions and massive noise. Therefore, the algorithm proposed in this paper is a faster and more robust method than Super 4-Points Congruent Sets under the guarantee of the promised quality.

scholarly journals THE ARCHITECTURE OF A STEREO IMAGE BASED SYSTEM TO MEASURE TREE GEOMETRIC PARAMETERS

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 183-189
Author(s):  
M. Bayat ◽  
H. Latifi ◽  
A. Hosseininaveh
Keyword(s):  
Real Time ◽  
Data Transfer ◽  
Imaging System ◽  
Three Dimensional ◽  
Point Clouds ◽  
Urban Trees ◽  
Stereo Image ◽  
Raspberry Pi ◽  
Remote Measurement ◽  
Dense Point

Abstract. Stereo photogrammetry enables collecting precise and detailed three-dimensional data of terrestrial objects. The estimation of qualitative and quantitative tree attributes, in particular those related to geometric measures, is crucial for forest management. In this study, a stereo imaging system is designed in order to measure a set of geometric attributes of urban trees such as crown dimensions, height and diameter at multiple height levels. The system consists of two hardware and software components. The hardware comprises two cameras with a specified baseline, two raspberry pi 3 model B+ boards, a GPS, an IMU and a power bank, all embedded in a box. The software includes a connection between the camera and the raspberry pi 3 in each side as well as data transfer to a laptop. The calibration is conducted in laboratory prior to applying the system and leads to achieve a disparity image from a pair of stereo imagery, which is then processed to extract dense point clouds. The system enables measuring basic, yet crucial tree attributes such as height and diameter in near real-time basis. The entire process is conducted by means of drastic libraries in Robot Operating System (ROS). Apart from being convenient and real-time, the system is associated with the potential for timely and precise measurements, which enable comparative analysis against other existing remote measurement systems as well as reference field data.

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