scholarly journals Monitoring Selective Logging in a Pine-Dominated Forest in Central Germany with Repeated Drone Flights Utilizing A Low Cost RTK Quadcopter

Drones ◽  
2020 ◽  
Vol 4 (2) ◽  
pp. 11 ◽  
Author(s):  
Christian Thiel ◽  
Marlin M. Müller ◽  
Christian Berger ◽  
Felix Cremer ◽  
Clémence Dubois ◽  
...  
Keyword(s):  
Low Cost ◽  
Three Dimensional ◽  
Point Clouds ◽  
Selective Logging ◽  
Ease Of Use ◽  
Tree Level ◽  
Unmanned Aerial Systems ◽  
3D Point Clouds ◽  
Individual Trees ◽  
New Generation

There is no doubt that unmanned aerial systems (UAS) will play an increasing role in Earth observation in the near future. The field of application is very broad and includes aspects of environmental monitoring, security, humanitarian aid, or engineering. In particular, drones with camera systems are already widely used. The capability to compute ultra-high-resolution orthomosaics and three-dimensional (3D) point clouds from UAS imagery generates a wide interest in such systems, not only in the science community, but also in industry and agencies. In particular, forestry sciences benefit from ultra-high-structural and spectral information as regular tree level-based monitoring becomes feasible. There is a great need for this kind of information as, for example, due to the spring and summer droughts in Europe in the years 2018/2019, large quantities of individual trees were damaged or even died. This study focuses on selective logging at the level of individual trees using repeated drone flights. Using the new generation of UAS, which allows for sub-decimeter-level positioning accuracies, a change detection approach based on bi-temporal UAS acquisitions was implemented. In comparison to conventional UAS, the effort of implementing repeated drone flights in the field was low, because no ground control points needed to be surveyed. As shown in this study, the geometrical offset between the two collected datasets was below 10 cm across the site, which enabled a direct comparison of both datasets without the need for post-processing (e.g., image matching). For the detection of logged trees, we utilized the spectral and height differences between both acquisitions. For their delineation, an object-based approach was employed, which was proven to be highly accurate (precision = 97.5%; recall = 91.6%). Due to the ease of use of such new generation, off-the-shelf consumer drones, their decreasing purchase costs, the quality of available workflows for data processing, and the convincing results presented here, UAS-based data can and should complement conventional forest inventory practices.

scholarly journals POINT CLOUD MAPPING METHODS FOR DOCUMENTING CULTURAL LANDSCAPE FEATURES AT THE WORMSLOE STATE HISTORIC SITE, SAVANNAH, GEORGIA, USA

2016 ◽  
Vol XLI-B5 ◽  
pp. 277-280
Author(s):  
T. R. Jordana ◽  
C. L. Goetcheus ◽  
M. Madden
Keyword(s):  
Laser Scanning ◽  
Cultural Landscape ◽  
Three Dimensional ◽  
Point Clouds ◽  
Ease Of Use ◽  
Unmanned Aerial Systems ◽  
Historic Site ◽  
Data Set ◽  
3D Point Clouds ◽  
Park Service

Documentation of the three-dimensional (3D) cultural landscape has traditionally been conducted during site visits using conventional photographs, standard ground surveys and manual measurements. In recent years, there have been rapid developments in technologies that produce highly accurate 3D point clouds, including aerial LiDAR, terrestrial laser scanning, and photogrammetric data reduction from unmanned aerial systems (UAS) images and hand held photographs using Structure from Motion (SfM) methods. These 3D point clouds can be precisely scaled and used to conduct measurements of features even after the site visit has ended. As a consequence, it is becoming increasingly possible to collect non-destructive data for a wide variety of cultural site features, including landscapes, buildings, vegetation, artefacts and gardens. As part of a project for the U.S. National Park Service, a variety of data sets have been collected for the Wormsloe State Historic Site, near Savannah, Georgia, USA. In an effort to demonstrate the utility and versatility of these methods at a range of scales, comparisons of the features mapped with different techniques will be discussed with regards to accuracy, data set completeness, cost and ease-of-use.

scholarly journals POINT CLOUD MAPPING METHODS FOR DOCUMENTING CULTURAL LANDSCAPE FEATURES AT THE WORMSLOE STATE HISTORIC SITE, SAVANNAH, GEORGIA, USA

2016 ◽  
Vol XLI-B5 ◽  
pp. 277-280 ◽  
Author(s):  
T. R. Jordana ◽  
C. L. Goetcheus ◽  
M. Madden
Keyword(s):  
Laser Scanning ◽  
Cultural Landscape ◽  
Three Dimensional ◽  
Point Clouds ◽  
Ease Of Use ◽  
Unmanned Aerial Systems ◽  
Historic Site ◽  
Data Set ◽  
3D Point Clouds ◽  
Park Service

Documentation of the three-dimensional (3D) cultural landscape has traditionally been conducted during site visits using conventional photographs, standard ground surveys and manual measurements. In recent years, there have been rapid developments in technologies that produce highly accurate 3D point clouds, including aerial LiDAR, terrestrial laser scanning, and photogrammetric data reduction from unmanned aerial systems (UAS) images and hand held photographs using Structure from Motion (SfM) methods. These 3D point clouds can be precisely scaled and used to conduct measurements of features even after the site visit has ended. As a consequence, it is becoming increasingly possible to collect non-destructive data for a wide variety of cultural site features, including landscapes, buildings, vegetation, artefacts and gardens. As part of a project for the U.S. National Park Service, a variety of data sets have been collected for the Wormsloe State Historic Site, near Savannah, Georgia, USA. In an effort to demonstrate the utility and versatility of these methods at a range of scales, comparisons of the features mapped with different techniques will be discussed with regards to accuracy, data set completeness, cost and ease-of-use.

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 ACCURACY ASSESSMENT OF UNDERWATER PHOTOGRAMMETRIC THREE DIMENSIONAL MODELLING FOR CORAL REEFS

2016 ◽  
Vol XLI-B5 ◽  
pp. 821-828 ◽  
Author(s):  
T. Guo ◽  
A. Capra ◽  
M. Troyer ◽  
A. Gruen ◽  
A. J. Brooks ◽  
...  
Keyword(s):  
Coral Cover ◽  
Accuracy Assessment ◽  
Low Cost ◽  
Three Dimensional ◽  
Point Clouds ◽  
3D Modelling ◽  
Relative Accuracy ◽  
3D Point Clouds ◽  
The Individual ◽  
Working Distance

Recent advances in automation of photogrammetric 3D modelling software packages have stimulated interest in reconstructing highly accurate 3D object geometry in unconventional environments such as underwater utilizing simple and low-cost camera systems. The accuracy of underwater 3D modelling is affected by more parameters than in single media cases. This study is part of a larger project on 3D measurements of temporal change of coral cover in tropical waters. It compares the accuracies of 3D point clouds generated by using images acquired from a system camera mounted in an underwater housing and the popular GoPro cameras respectively. A precisely measured calibration frame was placed in the target scene in order to provide accurate control information and also quantify the errors of the modelling procedure. In addition, several objects (cinder blocks) with various shapes were arranged in the air and underwater and 3D point clouds were generated by automated image matching. These were further used to examine the relative accuracy of the point cloud generation by comparing the point clouds of the individual objects with the objects measured by the system camera in air (the best possible values). Given a working distance of about 1.5 m, the GoPro camera can achieve a relative accuracy of 1.3 mm in air and 2.0 mm in water. The system camera achieved an accuracy of 1.8 mm in water, which meets our requirements for coral measurement in this system.

scholarly journals A Self-Assembly Portable Mobile Mapping System for Archeological Reconstruction Based on VSLAM-Photogrammetric Algorithm

Sensors ◽  
2019 ◽  
Vol 19 (18) ◽  
pp. 3952 ◽  
Author(s):  
* ◽  
*
Keyword(s):  
Self Assembly ◽  
Average Distance ◽  
Low Cost ◽  
Three Dimensional ◽  
Point Clouds ◽  
3D Models ◽  
Data Capture ◽  
Information Modeling ◽  
3D Point Clouds ◽  
Mean Square Errors

Three Dimensional (3D) models are widely used in clinical applications, geosciences, cultural heritage preservation, and engineering; this, together with new emerging needs such as building information modeling (BIM) develop new data capture techniques and devices with a low cost and reduced learning curve that allow for non-specialized users to employ it. This paper presents a simple, self-assembly device for 3D point clouds data capture with an estimated base price under €2500; furthermore, a workflow for the calculations is described that includes a Visual SLAM-photogrammetric threaded algorithm that has been implemented in C++. Another purpose of this work is to validate the proposed system in BIM working environments. To achieve it, in outdoor tests, several 3D point clouds were obtained and the coordinates of 40 points were obtained by means of this device, with data capture distances ranging between 5 to 20 m. Subsequently, those were compared to the coordinates of the same targets measured by a total station. The Euclidean average distance errors and root mean square errors (RMSEs) ranging between 12–46 mm and 8–33 mm respectively, depending on the data capture distance (5–20 m). Furthermore, the proposed system was compared with a commonly used photogrammetric methodology based on Agisoft Metashape software. The results obtained demonstrate that the proposed system satisfies (in each case) the tolerances of ‘level 1’ (51 mm) and ‘level 2’ (13 mm) for point cloud acquisition in urban design and historic documentation, according to the BIM Guide for 3D Imaging (U.S. General Services).

scholarly journals Automatic Reconstruction of Building-Scale Indoor 3D Environment with a Deep-Reinforcement-Learning-Based Mobile Robot

2021 ◽  
Vol 6 ◽  
pp. 11-23
Author(s):  
Menglong Yang ◽  
Katashi Nagao
Keyword(s):  
Reinforcement Learning ◽  
Mobile Robot ◽  
Real World ◽  
Low Cost ◽  
Three Dimensional ◽  
Point Clouds ◽  
Autonomous Agent ◽  
Entire Area ◽  
The Real ◽  
3D Point Clouds

The aim of this paper is to digitize the environments in which humans live, at low cost, and reconstruct highly accurate three-dimensional environments that are based on those in the real world. This three-dimensional content can be used such as for virtual reality environments and three-dimensional maps for automatic driving systems. In general, however, a three-dimensional environment must be carefully reconstructed by manually moving the sensors used to first scan the real environment on which the three-dimensional one is based. This is done so that every corner of an entire area can be measured, but time and costs increase as the area expands. Therefore, a system that creates three-dimensional content that is based on real-world large-scale buildings at low cost is proposed. This involves automatically scanning the indoors with a mobile robot that uses low-cost sensors and generating 3D point clouds. When the robot reaches an appropriate measurement position, it collects the three-dimensional data of shapes observable from that position by using a 3D sensor and 360-degree panoramic camera. The problem of determining an appropriate measurement position is called the “next best view problem,” and it is difficult to solve in a complicated indoor environment. To deal with this problem, a deep reinforcement learning method is employed. It combines reinforcement learning, with which an autonomous agent learns strategies for selecting behavior, and deep learning done using a neural network. As a result, 3D point cloud data can be generated with better quality than the conventional rule-based approach.

scholarly journals Enhancing Image-Based Multiscale Heritage Recording with Near-Infrared Data

2020 ◽  
Vol 9 (4) ◽  
pp. 269 ◽  
Author(s):  
Efstathios Adamopoulos ◽  
Fulvio Rinaudo
Keyword(s):  
Near Infrared ◽  
Low Cost ◽  
Three Dimensional ◽  
Point Clouds ◽  
Archaeological Site ◽  
Short Review ◽  
Additional Information ◽  
3D Point Clouds ◽  
Heritage Science ◽  
Imaging Sensors

Passive sensors, operating in the visible (VIS) spectrum, have widely been used towards the trans-disciplinary documentation, understanding, and protection of tangible cultural heritage (CH). Although, many heritage science fields benefit significantly from additional information that can be acquired in the near-infrared (NIR) spectrum. NIR imagery, captured for heritage applications, has been mostly investigated with two-dimensional (2D) approaches or by 2D-to-three-dimensional (3D) integrations following complicated techniques, including expensive imaging sensors and setups. The availability of high-resolution digital modified cameras and software implementations of Structure-from-Motion (SfM) and Multiple-View-Stereo (MVS) algorithms, has made the production of models with spectral textures more feasible than ever. In this research, a short review of image-based 3D modeling with NIR data is attempted. The authors aim to investigate the use of near-infrared imagery from relatively low-cost modified sensors for heritage digitization, alongside the usefulness of spectral textures produced, oriented towards heritage science. Therefore, thorough experimentation and assessment with different software are conducted and presented, utilizing NIR imagery and SfM/MVS methods. Dense 3D point clouds and textured meshes have been produced and evaluated for their metric validity and radiometric quality, comparing to results produced from VIS imagery. The datasets employed come from heritage assets of different dimensions, from an archaeological site to a medium-sized artwork, to evaluate implementation on different levels of accuracy and specifications of texture resolution.

scholarly journals ACCURACY ASSESSMENT OF UNDERWATER PHOTOGRAMMETRIC THREE DIMENSIONAL MODELLING FOR CORAL REEFS

2016 ◽  
Vol XLI-B5 ◽  
pp. 821-828 ◽  
Author(s):  
T. Guo ◽  
A. Capra ◽  
M. Troyer ◽  
A. Gruen ◽  
A. J. Brooks ◽  
...  
Keyword(s):  
Coral Cover ◽  
Accuracy Assessment ◽  
Low Cost ◽  
Three Dimensional ◽  
Point Clouds ◽  
3D Modelling ◽  
Relative Accuracy ◽  
3D Point Clouds ◽  
The Individual ◽  
Working Distance

Recent advances in automation of photogrammetric 3D modelling software packages have stimulated interest in reconstructing highly accurate 3D object geometry in unconventional environments such as underwater utilizing simple and low-cost camera systems. The accuracy of underwater 3D modelling is affected by more parameters than in single media cases. This study is part of a larger project on 3D measurements of temporal change of coral cover in tropical waters. It compares the accuracies of 3D point clouds generated by using images acquired from a system camera mounted in an underwater housing and the popular GoPro cameras respectively. A precisely measured calibration frame was placed in the target scene in order to provide accurate control information and also quantify the errors of the modelling procedure. In addition, several objects (cinder blocks) with various shapes were arranged in the air and underwater and 3D point clouds were generated by automated image matching. These were further used to examine the relative accuracy of the point cloud generation by comparing the point clouds of the individual objects with the objects measured by the system camera in air (the best possible values). Given a working distance of about 1.5 m, the GoPro camera can achieve a relative accuracy of 1.3 mm in air and 2.0 mm in water. The system camera achieved an accuracy of 1.8 mm in water, which meets our requirements for coral measurement in this system.

scholarly journals Metrics of Growth Habit Derived from the 3D Tree Point Cloud Used for Species Determination—A New Approach in Botanical Taxonomy Tested on Dragon Tree Group Example

Forests ◽  
2020 ◽  
Vol 11 (3) ◽  
pp. 272 ◽  
Author(s):  
Petr Vahalík ◽  
Karel Drápela ◽  
Andrea Procházková ◽  
Zdeněk Patočka ◽  
Marie Balková ◽  
...  
Keyword(s):  
Growth Habit ◽  
Three Dimensional ◽  
Point Clouds ◽  
Species Determination ◽  
New Approach ◽  
Three Dimensional Modeling ◽  
3D Point Clouds ◽  
Dimensional Modeling ◽  
Morphological Differences ◽  
Individual Trees

Detailed, three-dimensional modeling of trees is a new approach in botanical taxonomy. Representations of individual trees are a prerequisite for accurate assessments of tree growth and morphological metronomy. This study tests the abilities of 3D modeling of trees to determine the various metrics of growth habit and compare morphological differences. The study included four species of the genus Dracaena: D. draco, D. cinnabari, D. ombet, and D. serrulata. Forty-nine 3D tree point clouds were created, and their morphological metrics were derived and compared. Our results indicate the possible application of 3D tree point clouds to dendrological taxonomy. Basic metrics of growth habit and coefficients derived from the 3D point clouds developed in the present study enable the statistical evaluation of differences among dragon tree species.

scholarly journals Imaging in Propeller Flap Surgery

2020 ◽  
Vol 34 (03) ◽  
pp. 145-151
Author(s):  
Shimpei Ono ◽  
Hiroyuki Ohi ◽  
Rei Ogawa
Keyword(s):  
Low Cost ◽  
Three Dimensional ◽  
Duplex Sonography ◽  
Computed Tomographic Angiography ◽  
Ease Of Use ◽  
Computed Tomographic ◽  
Imaging Tool ◽  
Preoperative Mapping ◽  
Flap Design ◽  
Tomographic Angiography

AbstractSince propeller flaps are elevated as island flaps and most often nourished by a single perforator nearby the defect, it is challenging to change the flap design intraoperatively when a reliable perforator cannot be found where expected to exist. Thus, accurate preoperative mapping of perforators is essential in the safe planning of propeller flaps. Various methods have been reported so far: (1) handheld acoustic Doppler sonography (ADS), (2) color duplex sonography (CDS), (3) perforator computed tomographic angiography (P-CTA), and (4) magnetic resonance angiography (MRA). To facilitate the preoperative perforator assessment, P-CTA is currently considered as the gold standard imaging tool in revealing the three-dimensional anatomical details of perforators precisely. Nevertheless, ADS remains the most widely used tool due to its low cost, faster learning, and ease of use despite an undesirable number of false-positive results. CDS can provide hemodynamic characteristics of the perforator and is a valid and safer alternative particularly in patients in whom ionizing radiation and/or contrast exposure should be limited. Although MRA is less accurate in detecting smaller perforators of caliber less than 1.0 mm and the intramuscular course of perforators at the present time, MRA is expected to improve in the future due to the recent developments in technology, making it as accurate as P-CTA. Moreover, it provides the advantage of being radiation-free with fewer contrast reactions.

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