scholarly journals Canopy Roughness: A New Phenotypic Trait to Estimate Aboveground Biomass from Unmanned Aerial System

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Monica Herrero-Huerta ◽  
Alexander Bucksch ◽  
Eetu Puttonen ◽  
Katy M. Rainey
Keyword(s):  
Aboveground Biomass ◽  
Recombinant Inbred Lines ◽  
Digital Camera ◽  
Point Clouds ◽  
Aerial Images ◽  
Optical Data ◽  
Coefficient Of Determination ◽  
Phenotypic Trait ◽  
Unmanned Aerial Systems ◽  
3D Point Clouds

Cost-effective phenotyping methods are urgently needed to advance crop genetics in order to meet the food, fuel, and fiber demands of the coming decades. Concretely, characterizing plot level traits in fields is of particular interest. Recent developments in high-resolution imaging sensors for UAS (unmanned aerial systems) focused on collecting detailed phenotypic measurements are a potential solution. We introduce canopy roughness as a new plant plot-level trait. We tested its usability with soybean by optical data collected from UAS to estimate biomass. We validate canopy roughness on a panel of 108 soybean [Glycine max (L.) Merr.] recombinant inbred lines in a multienvironment trial during the R2 growth stage. A senseFly eBee UAS platform obtained aerial images with a senseFly S.O.D.A. compact digital camera. Using a structure from motion (SfM) technique, we reconstructed 3D point clouds of the soybean experiment. A novel pipeline for feature extraction was developed to compute canopy roughness from point clouds. We used regression analysis to correlate canopy roughness with field-measured aboveground biomass (AGB) with a leave-one-out cross-validation. Overall, our models achieved a coefficient of determination (R2) greater than 0.5 in all trials. Moreover, we found that canopy roughness has the ability to discern AGB variations among different genotypes. Our test trials demonstrate the potential of canopy roughness as a reliable trait for high-throughput phenotyping to estimate AGB. As such, canopy roughness provides practical information to breeders in order to select phenotypes on the basis of UAS data.

scholarly journals Symmetry Analysis of Oriental Polygonal Pagodas Using 3D Point Clouds for Cultural Heritage

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1228
Author(s):  
Ting On Chan ◽  
Linyuan Xia ◽  
Yimin Chen ◽  
Wei Lang ◽  
Tingting Chen ◽  
...  
Keyword(s):  
Cultural Heritage ◽  
Unmanned Aerial Vehicle ◽  
Point Cloud ◽  
Geometric Model ◽  
Digital Camera ◽  
Point Clouds ◽  
Symmetry Analysis ◽  
3D Point Clouds ◽  
Transmission Towers ◽  
Aerial Vehicle

Ancient pagodas are usually parts of hot tourist spots in many oriental countries due to their unique historical backgrounds. They are usually polygonal structures comprised by multiple floors, which are separated by eaves. In this paper, we propose a new method to investigate both the rotational and reflectional symmetry of such polygonal pagodas through developing novel geometric models to fit to the 3D point clouds obtained from photogrammetric reconstruction. The geometric model consists of multiple polygonal pyramid/prism models but has a common central axis. The method was verified by four datasets collected by an unmanned aerial vehicle (UAV) and a hand-held digital camera. The results indicate that the models fit accurately to the pagodas’ point clouds. The symmetry was realized by rotating and reflecting the pagodas’ point clouds after a complete leveling of the point cloud was achieved using the estimated central axes. The results show that there are RMSEs of 5.04 cm and 5.20 cm deviated from the perfect (theoretical) rotational and reflectional symmetries, respectively. This concludes that the examined pagodas are highly symmetric, both rotationally and reflectionally. The concept presented in the paper not only work for polygonal pagodas, but it can also be readily transformed and implemented for other applications for other pagoda-like objects such as transmission towers.

scholarly journals Mapping Forest Structure Using UAS inside Flight Capabilities

Sensors ◽  
2018 ◽  
Vol 18 (7) ◽  
pp. 2245 ◽  
Author(s):  
Karel Kuželka ◽  
Peter Surový
Keyword(s):  
Least Squares ◽  
Forest Structure ◽  
European Beech ◽  
Point Clouds ◽  
Unmanned Aerial Systems ◽  
Structure Mapping ◽  
Close Range Photogrammetry ◽  
3D Point Clouds ◽  
Ellipse Method ◽  
Close Range

We evaluated two unmanned aerial systems (UASs), namely the DJI Phantom 4 Pro and DJI Mavic Pro, for 3D forest structure mapping of the forest stand interior with the use of close-range photogrammetry techniques. Assisted flights were performed within two research plots established in mature pure Norway spruce (Picea abies (L.) H. Karst.) and European beech (Fagus sylvatica L.) forest stands. Geotagged images were used to produce georeferenced 3D point clouds representing tree stem surfaces. With a flight height of 8 m above the ground, the stems were precisely modeled up to a height of 10 m, which represents a considerably larger portion of the stem when compared with terrestrial close-range photogrammetry. Accuracy of the point clouds was evaluated by comparing field-measured tree diameters at breast height (DBH) with diameter estimates derived from the point cloud using four different fitting methods, including the bounding circle, convex hull, least squares circle, and least squares ellipse methods. The accuracy of DBH estimation varied with the UAS model and the diameter fitting method utilized. With the Phantom 4 Pro and the least squares ellipse method to estimate diameter, the mean error of diameter estimates was −1.17 cm (−3.14%) and 0.27 cm (0.69%) for spruce and beech stands, respectively.

Robust external calibration of terrestrial laser scanner and digital camera for structural monitoring

2019 ◽  
Vol 13 (2) ◽  
pp. 105-134 ◽  
Author(s):  
Mohammad Omidalizarandi ◽  
Boris Kargoll ◽  
Jens-André Paffenholz ◽  
Ingo Neumann
Keyword(s):  
Em Algorithm ◽  
Laser Scanner ◽  
Digital Camera ◽  
Point Clouds ◽  
Deformation Monitoring ◽  
Deformation Analysis ◽  
Terrestrial Laser Scanner ◽  
External Calibration ◽  
3D Point Clouds ◽  
Calibration Parameters

Abstract In the last two decades, the integration of a terrestrial laser scanner (TLS) and digital photogrammetry, besides other sensors integration, has received considerable attention for deformation monitoring of natural or man-made structures. Typically, a TLS is used for an area-based deformation analysis. A high-resolution digital camera may be attached on top of the TLS to increase the accuracy and completeness of deformation analysis by optimally combining points or line features extracted both from three-dimensional (3D) point clouds and captured images at different epochs of time. For this purpose, the external calibration parameters between the TLS and digital camera needs to be determined precisely. The camera calibration and internal TLS calibration are commonly carried out in advance in the laboratory environments. The focus of this research is to highly accurately and robustly estimate the external calibration parameters between the fused sensors using signalised target points. The observables are the image measurements, the 3D point clouds, and the horizontal angle reading of a TLS. In addition, laser tracker observations are used for the purpose of validation. The functional models are determined based on the space resection in photogrammetry using the collinearity condition equations, the 3D Helmert transformation and the constraint equation, which are solved in a rigorous bundle adjustment procedure. Three different adjustment procedures are developed and implemented: (1) an expectation maximization (EM) algorithm to solve a Gauss-Helmert model (GHM) with grouped t-distributed random deviations, (2) a novel EM algorithm to solve a corresponding quasi-Gauss-Markov model (qGMM) with t-distributed pseudo-misclosures, and (3) a classical least-squares procedure to solve the GHM with variance components and outlier removal. The comparison of the results demonstrates the precise, reliable, accurate and robust estimation of the parameters in particular by the second and third procedures in comparison to the first one. In addition, the results show that the second procedure is computationally more efficient than the other two.

scholarly journals Measuring Height Characteristics of Sagebrush (Artemisia sp.) Using Imagery Derived from Small Unmanned Aerial Systems (sUAS)

Drones ◽  
2020 ◽  
Vol 4 (1) ◽  
pp. 6 ◽  
Author(s):  
Ryan G. Howell ◽  
Ryan R. Jensen ◽  
Steven L. Petersen ◽  
Randy T. Larsen
Keyword(s):  
Data Storage ◽  
Accuracy Assessment ◽  
Point Clouds ◽  
Unmanned Aerial Systems ◽  
Surface Model ◽  
Sage Grouse ◽  
Double Pass ◽  
Single Pass ◽  
3D Point Clouds ◽  
Aerial Systems

In situ measurements of sagebrush have traditionally been expensive and time consuming. Currently, improvements in small Unmanned Aerial Systems (sUAS) technology can be used to quantify sagebrush morphology and community structure with high resolution imagery on western rangelands, especially in sensitive habitat of the Greater sage-grouse (Centrocercus urophasianus). The emergence of photogrammetry algorithms to generate 3D point clouds from true color imagery can potentially increase the efficiency and accuracy of measuring shrub height in sage-grouse habitat. Our objective was to determine optimal parameters for measuring sagebrush height including flight altitude, single- vs. double- pass, and continuous vs. pause features. We acquired imagery using a DJI Mavic Pro 2 multi-rotor Unmanned Aerial Vehicle (UAV) equipped with an RGB camera, flown at 30.5, 45, 75, and 120 m and implementing single-pass and double-pass methods, using continuous flight and paused flight for each photo method. We generated a Digital Surface Model (DSM) from which we derived plant height, and then performed an accuracy assessment using on the ground measurements taken at the time of flight. We found high correlation between field measured heights and estimated heights, with a mean difference of approximately 10 cm (SE = 0.4 cm) and little variability in accuracy between flights with different heights and other parameters after statistical correction using linear regression. We conclude that higher altitude flights using a single-pass method are optimal to measure sagebrush height due to lower requirements in data storage and processing time.

scholarly journals Urban Feature Extraction from Merged Airborne LiDAR Data and Digital Camera Data

2021 ◽  
Vol 7 (2) ◽  
pp. 57-74
Author(s):  
Lamyaa Gamal EL-Deen Taha ◽  
A. I. Ramzi ◽  
A. Syarawi ◽  
A. Bekheet
Keyword(s):  
Neural Network ◽  
Digital Camera ◽  
Point Clouds ◽  
Airborne Lidar ◽  
Surface Model ◽  
Digital Surface Model ◽  
3D Point Clouds ◽  
Digital Elevation ◽  
Surface Models ◽  
Elevation Model

Until recently, the most highly accurate digital surface models were obtained from airborne lidar. With the development of a new generation of large format digital photogrammetric aerial camera, a fully digital photogrammetric workflow became possible. Digital airborne images are sources for elevation extraction and orthophoto generation. This research concerned with the generation of digital surface models and orthophotos as applications from high-resolution images.  In this research, the following steps were performed. A Benchmark data of LIDAR and digital aerial camera have been used.  Firstly, image orientation, AT have been performed. Then the automatic digital surface model DSM generation has been produced from the digital aerial camera. Thirdly true digital ortho has been generated from the digital aerial camera also orthoimage will be generated using LIDAR digital elevation model (DSM). Leica Photogrammetric Suite (LPS) module of Erdsa Imagine 2014 software was utilized for processing. Then the resulted orthoimages from both techniques were mosaicked. The results show that automatic digital surface model DSM that been produced from digital aerial camera method has very high dense photogrammetric 3D point clouds compared to the LIDAR 3D point clouds. It was found that the true orthoimage produced from the second approach is better than the true orthoimage produced from the first approach. The five approaches were tested for classification of the best-orthorectified image mosaic using subpixel based (neural network) and pixel-based ( minimum distance and maximum likelihood).Multicues were extracted such as texture(entropy-mean),Digital elevation model, Digital surface model ,normalized digital surface model (nDSM) and intensity image. The contributions of the individual cues used in the classification have been evaluated. It was found that the best cue integration is intensity (pan) +nDSM+ entropy followed by intensity (pan) +nDSM+mean then intensity image +mean+ entropy after that DSM )image and two texture measures (mean and entropy) followed by the colour image. The integration with height data increases the accuracy. Also, it was found that the integration with entropy texture increases the accuracy. Resulted in fifteen cases of classification it was found that maximum likelihood classifier is the best followed by minimum distance then neural network classifier. We attribute this to the fine resolution of the digital camera image. Subpixel classifier (neural network) is not suitable for classifying aerial digital camera images. 

UAV Low Altitude Photogrammetry for Power Line Inspection

2016 ◽  
Author(s):  
Yong Zhang ◽  
Xiuxiao Yuan ◽  
Yi Fang ◽  
Shiyu Chen
Keyword(s):  
Transmission Lines ◽  
Three Dimensional ◽  
Digital Camera ◽  
Point Clouds ◽  
Power Line ◽  
Epipolar Line ◽  
3D Point Clouds ◽  
Low Altitude ◽  
Power Line Corridor ◽  
Safety Inspections

When the distance between an obstacle and a power line is less than the discharge distance, a discharge arc can be generated, resulting in interruption of power supplies. Therefore, regular safety inspections are necessary to ensure safe operations of power grids. Tall vegetation and buildings are the key factors threatening the safe operation of extra high voltage transmission lines within a power line corridor. Manual or LiDAR based-inspections are time consuming and expensive. To make safety inspections more efficient and flexible, a low-altitude unmanned aerial vehicle remote-sensing platform equipped with optical digital camera was used to inspect power line corridors. We propose a semi-patch matching algorithm based on epipolar constraints using both correlation coefficient and the shape of its curve to extract three dimensional (3D) point clouds for a power line corridor. Virtual photography was used to transform the power line direction from approximately parallel to the epipolar line to approximately perpendicular to epipolar line to improve power line measurement accuracy. The distance between the power lines and the 3D point cloud is taken as a criterion for locating obstacles within the power line corridor automatically. Experimental results show that our proposed method is a reliable, cost effective and applicable way for practical power line inspection, and can locate obstacles within the power line corridor with measurement accuracies better than ±0.5 m.

scholarly journals INTEGRATED USE OF REMOTE SENSED DATA AND NUMERICAL CARTOGRAPHY FOR THE GENERATION OF 3D CITY MODELS

2018 ◽  
Vol XLII-2 ◽  
pp. 97-102 ◽  
Author(s):  
G. Bitelli ◽  
V. A. Girelli ◽  
A. Lambertini
Keyword(s):  
Large Scale ◽  
Point Clouds ◽  
3D Models ◽  
Geospatial Data ◽  
Aerial Images ◽  
Public Authorities ◽  
3D City Models ◽  
3D Point Clouds ◽  
Emilia Romagna Region ◽  
City Models

3D city models are becoming increasingly popular and important, because they constitute the base for all the visualization, planning, management operations regarding the urban infrastructure. These data are however not available in the majority of cities: in this paper, the possibility to use geospatial data of various kinds with the aim to generate 3D models in urban environment is investigated.<br> In 3D modelling works, the starting data are frequently the 3D point clouds, which are nowadays possible to collect by different sensors mounted on different platforms: LiDAR, imagery from satellite, airborne or unmanned aerial vehicles, mobile mapping systems that integrate several sensors. The processing of the acquired data and consequently the obtainability of models able to provide geometric accuracy and a good visual impact is limited by time, costs and logistic constraints.<br> Nowadays more and more innovative hardware and software solutions can offer to the municipalities and the public authorities the possibility to use available geospatial data, acquired for diverse aims, for the generation of 3D models of buildings and cities, characterized by different level of detail.<br> In the paper two cases of study are presented, both regarding surveys carried out in Emilia Romagna region, Italy, where 2D or 2.5D numerical maps are available. The first one is about the use of oblique aerial images realized by the Municipality for a systematic documentation of the built environment, the second concerns the use of LiDAR data acquired for other purposes; in the two tests, these data were used in conjunction with large scale numerical maps to produce 3D city models.

scholarly journals Analysis of Point Cloud Generation from UAS Images

2014 ◽  
Vol II-1 ◽  
pp. 45-51 ◽  
Author(s):  
S. Ostrowski ◽  
G. Jóźków ◽  
C. Toth ◽  
B. Vander Jagt
Keyword(s):  
Local Coordinate System ◽  
Field Tests ◽  
Point Clouds ◽  
Aerial Images ◽  
Unmanned Aerial Systems ◽  
Surface Model ◽  
Geospatial Information ◽  
Software Packages ◽  
The Ohio State University ◽  
Aerial Systems

Unmanned Aerial Systems (UAS) allow for the collection of low altitude aerial images, along with other geospatial information from a variety of companion sensors. The images can then be processed using sophisticated algorithms from the Computer Vision (CV) field, guided by the traditional and established procedures from photogrammetry. Based on highly overlapped images, new software packages which were specifically developed for UAS technology can easily create ground models, such as Point Clouds (PC), Digital Surface Model (DSM), orthoimages, etc. The goal of this study is to compare the performance of three different software packages, focusing on the accuracy of the 3D products they produce. Using a Nikon D800 camera installed on an ocotocopter UAS platform, images were collected during subsequent field tests conducted over the Olentangy River, north from the Ohio State University campus. Two areas around bike bridges on the Olentangy River Trail were selected because of the challenge the packages would have in creating accurate products; matching pixels over the river and dense canopy on the shore presents difficult scenarios to model. Ground Control Points (GCP) were gathered at each site to tie the models to a local coordinate system and help assess the absolute accuracy for each package. In addition, the models were also relatively compared to each other using their PCs.

scholarly journals Structure from motion (SfM) photogrammetry as alternative to laser scanning for 3D modelling of historical monuments

2020 ◽  
Vol 5 (2) ◽  
Author(s):  
Omar Al Khalil
Keyword(s):  
Structure From Motion ◽  
Laser Scanning ◽  
Low Cost ◽  
Laser Scanner ◽  
Digital Camera ◽  
Point Clouds ◽  
3D Modelling ◽  
3D Point Clouds ◽  
Historical Monuments ◽  
Culture Heritage

During the past few years, new developments have occurred in the field of 3D photogrammetric modeling of culture heritage. One of these developments is the expansion of 3D photogrammetric modeling open-source software, such as VisualSfM, and cost-effective licensed software, such as Agisoft Metashape into the practical and affordable world. This type of SfM (Structure from Motion) software offers the world of 3D modelling of culture heritage a powerful tool for documentation and visualization. On the other hand, low-cost cameras are now available on the market. These cameras are characterized by high resolution and good quality lens, which makes them suitable for photogrammetric modelling. This paper reports on the results of the application of a SfM photogrammetry system in the 3D modelling of Safita Tower, a medieval structure in Safita, north-western Syria. The applied photogrammetric system consists of the Nikon Coolpix P100 10 MP digital camera and the commercial software Agisoft Metashape. The resulted 3D point clouds were compared with an available dense point cloud acquired by a laser scanner. This comparison proved that the low-cost SfM photogrammetry is an accurate methodology to 3D modeling historical monuments. 

scholarly journals USE OF VERTICAL AERIAL IMAGES FOR SEMI-OBLIQUE MAPPING

2017 ◽  
Vol XLII-1/W1 ◽  
pp. 493-498 ◽  
Author(s):  
D. Poli ◽  
K. Moe ◽  
K. Legat ◽  
I. Toschi ◽  
F. Lago ◽  
...  
Keyword(s):  
Focal Length ◽  
Point Clouds ◽  
Aerial Images ◽  
Perspective Geometry ◽  
Mesh Model ◽  
3D Point Clouds ◽  
Original Plan ◽  
3D Mesh Model ◽  
Historic Centre ◽  
Oblique Images

The paper proposes a methodology for the use of the oblique sections of images from large-format photogrammetric cameras, by exploiting the effect of the central perspective geometry in the lateral parts of the nadir images (“semi-oblique” images). The point of origin of the investigation was the execution of a photogrammetric flight over Norcia (Italy), which was seriously damaged after the earthquake of 30/10/2016. Contrary to the original plan of oblique acquisitions, the flight was executed on 15/11/2017 using an UltraCam Eagle camera with focal length 80 mm, and combining two flight plans, rotated by 90º (“crisscross” flight). The images (GSD 5 cm) were used to extract a 2.5D DSM cloud, sampled to a XY-grid size of 2 GSD, a 3D point clouds with a mean spatial resolution of 1 GSD and a 3D mesh model at a resolution of 10 cm of the historic centre of Norcia for a quantitative assessment of the damages. From the acquired nadir images the “semi-oblique” images (forward, backward, left and right views) could be extracted and processed in a modified version of GEOBLY software for measurements and restitution purposes. The potential of such semi-oblique image acquisitions from nadir-view cameras is hereafter shown and commented.

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