scholarly journals UNMANNED AERIAL VEHICLE APPLICATIONS OF 3D MODELLING, VISUALIZATION AND PARAMETER CALCULATIONS

2018 ◽  
Vol XLII-5 ◽  
pp. 649-652 ◽  
Author(s):  
V. Lambey ◽  
A. D. Prasad
Keyword(s):  
Point Cloud ◽  
Low Cost ◽  
3D Modelling ◽  
Aerial Photogrammetry ◽  
Average Accuracy ◽  
Aerial Vehicle ◽  
High Resolution Images ◽  
Institute Of Technology ◽  
Uav Images ◽  
Economical Alternative

<p><strong>Abstract.</strong> Photogrammetric surveying with the use of Unmanned Aerial Vehicles (UAV) have gained vast popularity in short span. UAV have the potential to provide imagery at an extraordinary spatial and temporal resolution when coupled with remote sensing. Currently, UAV platforms are fastest and easiest source of data for mapping and 3D modelling. It is to be considered as a low-cost substitute to the traditional airborne photogrammetry. In the present study, UAV applications are explored in terms of 3D modelling, visualization and parameter calculations. National Institute of Technology Raipur, Raipur is chosen as study area and high resolution images are acquired from the UAV with 85% overlap. 3D model is processed through the point cloud generated for the UAV images. The results are compared with traditional methods for validation. The average accuracy obtained for elevation points and area is 97.99% and 97.75%. The study proves that UAV based surveying is an economical alternative in terms of money, time and resources, when compared to the classical aerial photogrammetry methods.</p>

scholarly journals PERFORMANCE EVALUATION OF 3D MODELING SOFTWARE FOR UAV PHOTOGRAMMETRY

2016 ◽  
Vol XLI-B5 ◽  
pp. 147-152 ◽  
Author(s):  
H. Yanagi ◽  
H. Chikatsu
Keyword(s):  
3D Modeling ◽  
Low Cost ◽  
Black Box ◽  
3D Modelling ◽  
The Internet ◽  
Aerial Photogrammetry ◽  
Check Points ◽  
Modeling Software ◽  
Aerial Vehicle ◽  
User Friendly

UAV (Unmanned Aerial Vehicle) photogrammetry, which combines UAV and freely available internet-based 3D modeling software, is widely used as a low-cost and user-friendly photogrammetry technique in the fields such as remote sensing and geosciences. In UAV photogrammetry, only the platform used in conventional aerial photogrammetry is changed. Consequently, 3D modeling software contributes significantly to its expansion. However, the algorithms of the 3D modelling software are black box algorithms. As a result, only a few studies have been able to evaluate their accuracy using 3D coordinate check points. With this motive, Smart3DCapture and Pix4Dmapper were downloaded from the Internet and commercial software PhotoScan was also employed; investigations were performed in this paper using check points and images obtained from UAV.

scholarly journals PERFORMANCE EVALUATION OF 3D MODELING SOFTWARE FOR UAV PHOTOGRAMMETRY

2016 ◽  
Vol XLI-B5 ◽  
pp. 147-152 ◽  
Author(s):  
H. Yanagi ◽  
H. Chikatsu
Keyword(s):  
3D Modeling ◽  
Low Cost ◽  
Black Box ◽  
3D Modelling ◽  
The Internet ◽  
Aerial Photogrammetry ◽  
Check Points ◽  
Modeling Software ◽  
Aerial Vehicle ◽  
User Friendly

UAV (Unmanned Aerial Vehicle) photogrammetry, which combines UAV and freely available internet-based 3D modeling software, is widely used as a low-cost and user-friendly photogrammetry technique in the fields such as remote sensing and geosciences. In UAV photogrammetry, only the platform used in conventional aerial photogrammetry is changed. Consequently, 3D modeling software contributes significantly to its expansion. However, the algorithms of the 3D modelling software are black box algorithms. As a result, only a few studies have been able to evaluate their accuracy using 3D coordinate check points. With this motive, Smart3DCapture and Pix4Dmapper were downloaded from the Internet and commercial software PhotoScan was also employed; investigations were performed in this paper using check points and images obtained from UAV.

scholarly journals Towards Amazon Forest Restoration: Automatic Detection of Species from UAV Imagery

2021 ◽  
Vol 13 (13) ◽  
pp. 2627
Author(s):  
Marks Melo Moura ◽  
Luiz Eduardo Soares de Oliveira ◽  
Carlos Roberto Sanquetta ◽  
Alexis Bastos ◽  
Midhun Mohan ◽  
...  
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Forest Restoration ◽  
Amazon Forest ◽  
Forest Species ◽  
Accuracy And Precision ◽  
Identification Of Species ◽  
Aerial Vehicle ◽  
High Resolution Images ◽  
Uav Images

Precise assessments of forest species’ composition help analyze biodiversity patterns, estimate wood stocks, and improve carbon stock estimates. Therefore, the objective of this work was to evaluate the use of high-resolution images obtained from Unmanned Aerial Vehicle (UAV) for the identification of forest species in areas of forest regeneration in the Amazon. For this purpose, convolutional neural networks (CNN) were trained using the Keras–Tensorflow package with the faster_rcnn_inception_v2_pets model. Samples of six forest species were used to train CNN. From these, attempts were made with the number of thresholds, which is the cutoff value of the function; any value below this output is considered 0, and values above are treated as an output 1; that is, values above the value stipulated in the Threshold are considered as identified species. The results showed that the reduction in the threshold decreases the accuracy of identification, as well as the overlap of the polygons of species identification. However, in comparison with the data collected in the field, it was observed that there exists a high correlation between the trees identified by the CNN and those observed in the plots. The statistical metrics used to validate the classification results showed that CNN are able to identify species with accuracy above 90%. Based on our results, which demonstrate good accuracy and precision in the identification of species, we conclude that convolutional neural networks are an effective tool in classifying objects from UAV images.

scholarly journals Quality of Digital Elevation Models obtained from Unmanned Aerial Vehicles for Precision Viticulture

OENO One ◽  
2016 ◽  
Vol 50 (3) ◽  
Author(s):  
Léo Pichon ◽  
Arnaud Ducanchez ◽  
Hélène Fonta ◽  
Bruno Tisseyre
Keyword(s):  
Low Cost ◽  
Wine Industry ◽  
Image Capture ◽  
Digital Elevation ◽  
Elevation Data ◽  
Aerial Vehicle ◽  
Elevation Model ◽  
Uav Images ◽  
Data Acquisition And Processing

<p style="text-align: justify;"><strong>Aims:</strong> This work aims to study the quality of low cost Digital Surface Models (DSMs) obtained with Unmanned Aerial Vehicle (UAV) images and to test whether these DSMs meet common requirements of the wine industry.</p><p style="text-align: justify;"><strong>Methods and results: </strong>Experiments were carried out on a 4-ha vineyard located 10 km north of Beziers (France). The experimental site presents slope and aspect variations representative of mechanised commercial vineyards in Languedoc Roussillon. DSMs were provided by three UAV companies selected for the diversity of their solutions in terms of image capture altitude, type of UAV and image processing software. DSMs were obtained by photogrammetry and correspond to commercial products usually delivered by UAV companies. DSMs from UAV were compared to a reference Digital Elevation Model (DEM) acquired by a laser tachymeter. Four indicators were used to test the quality of DSMs: the mean error and its dispersion in the XY plane and in elevation Z. Results show a good georeferencing of the DSMs (MeanErrorXY&lt;10 cm) and a similar quality in elevation (MeanErrorZ&lt;10 cm) estimation. Results also show that the error in elevation is highly spatially structured. The spatial patterns observed did not depend on the elevation and could be related to algorithms used to compute the DSMs.</p><p style="text-align: justify;"><strong>Conclusion: </strong>Data acquisition and processing methods have an impact on the quality of the DSMs provided by the UAV companies. DSM qualities are good enough to meet commercial vineyard requirements. The tested DSMs fit the requirements to assess field characteristics (elevation, slope, aspects) which may be important for terroir characterisation purposes.</p><p style="text-align: justify;"><strong>Significance and impact of the study:</strong> This study proves that elevation data derived from UAV present an accuracy equivalent to the reference system used in this study. The rapidity, the low cost and the high spatial resolution of these data offer significant opportunities for the development of new services for the wine industry for field characterisation.</p>

scholarly journals ANALYSIS OF POSSIBILITIES OF LOW-COST PHOTOGRAMMETRY FOR INTERIOR MAPPING

2019 ◽  
Vol XLII-5/W3 ◽  
pp. 27-31
Author(s):  
A. Dlesk ◽  
K. Vach ◽  
P. Holubec
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
3D Model ◽  
Low Cost ◽  
Digital Camera ◽  
3D Modelling ◽  
Light Conditions ◽  
Advantages And Disadvantages ◽  
Lower Light ◽  
High Level

Abstract. This paper shows the possibilities of using low-cost photogrammetry for interior mapping as a tool to gather fast and accurate data for 3D modelling and BIM. To create a 3D model of a building interior with a high level of detail requires techniques such as laser scanning and photogrammetry. In the case of photogrammetry, it is possible to use standard cameras and SfM software to create an accurate point cloud which can be used for 3D modelling and then for BIM. The images captured indoor are often captured under lower light conditions. Using different exposure during capturing of images of building interior was tested. Frequent plain walls of a building interior cause that the images are usually lack of any features and their photogrammetric processing is getting much more difficult. In some cases, results of photogrammetric processing are poor and inaccurate. In this paper, an experiment of creating a 3D model of a building interior using photogrammetric processing of images was carried out. For this experiment digital camera with two different lenses (16 mm lens and fisheye lens) was used. For photogrammetric processing were chosen different software. All the results were compared to each other and to the laser scanning data of the interior. At the end of the paper, the discussion of the advantages and disadvantages of the shown method has been made.

scholarly journals Non-Rigid Vehicle-Borne LiDAR-Assisted Aerotriangulation

2019 ◽  
Vol 11 (10) ◽  
pp. 1188
Author(s):  
Li Zheng ◽  
Yuhao Li ◽  
Meng Sun ◽  
Zheng Ji ◽  
Manzhu Yu ◽  
...  
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Point Clouds ◽  
Necessary Condition ◽  
Control Points ◽  
The Road ◽  
Aerial Vehicle ◽  
Joint Mapping ◽  
Close Range ◽  
Uav Images

VLS (Vehicle-borne Laser Scanning) can easily scan the road surface in the close range with high density. UAV (Unmanned Aerial Vehicle) can capture a wider range of ground images. Due to the complementary features of platforms of VLS and UAV, combining the two methods becomes a more effective method of data acquisition. In this paper, a non-rigid method for the aerotriangulation of UAV images assisted by a vehicle-borne light detection and ranging (LiDAR) point cloud is proposed, which greatly reduces the number of control points and improves the automation. We convert the LiDAR point cloud-assisted aerotriangulation into a registration problem between two point clouds, which does not require complicated feature extraction and match between point cloud and images. Compared with the iterative closest point (ICP) algorithm, this method can address the non-rigid image distortion with a more rigorous adjustment model and a higher accuracy of aerotriangulation. The experimental results show that the constraint of the LiDAR point cloud ensures the high accuracy of the aerotriangulation, even in the absence of control points. The root-mean-square error (RMSE) of the checkpoints on the x, y, and z axes are 0.118 m, 0.163 m, and 0.084m, respectively, which verifies the reliability of the proposed method. As a necessary condition for joint mapping, the research based on VLS and UAV images in uncontrolled circumstances will greatly improve the efficiency of joint mapping and reduce its cost.

Extraction of geometrical information used in photovoltaic and rainwater harvesting potential estimation from UAV optical images

2020 ◽  
Vol 25 (3) ◽  
Author(s):  
Caisse Amisse ◽  
Alvaro Muriel Lima Machado ◽  
Jorge Antonio Silva Centeno
Keyword(s):  
Point Cloud ◽  
Rainwater Harvesting ◽  
State Of The Art ◽  
Low Cost ◽  
Geometrical Parameters ◽  
Optical Images ◽  
Aerial Vehicle ◽  
Geometrical Information ◽  
Reference Measurements ◽  
Data Acquisition And Processing

Photovoltaic and rainwater harvesting assessment on rooftop has been studied extensively. Detailed methodologies are available over large study areas and designed to use data that are usually difficult and expensive to acquire. However, much less attention has been paid to the use of low-cost data for the estimation of photovoltaic parameters and rainwater collection in individual buildings. In this study, a workflow for extraction of geometrical information used in Photovoltaic and rainwater harvesting potential estimation from UAV optical images used to estimate photovoltaic and rainwater harvesting potential is presented. The optical images captured by the DJI Phantom 4 Unmanned Aerial Vehicle (UAV) were used to compute a point cloud, using state of the art Structure from Motion (SfM) algorithms. The modeling of the roof planes was made based on the spatial relationships between points using a Delaunay triangulation. From the generated model, roof geometrical parameters such as area, slope, and orientation were extracted and compared with reference measurements of Light Detection And Ranging (LiDAR) of the same scene. Statistical results from the experiments show that the SfM and LiDAR extracted parameters are very similar. The geometric parameters derived from UAV optical images can be used to support the analysis of the photovoltaic and rainwater harvesting potential in individual buildings. This method has the advantage to achieve results through the combination of low-cost technologies for data acquisition and processing, resulting in an easily reproducible methodology.

scholarly journals Assessment of DSM Based on Radiometric Transformation of UAV Data

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1649
Author(s):  
Muhammad Hamid Chaudhry ◽  
Anuar Ahmad ◽  
Qudsia Gulzar ◽  
Muhammad Shahid Farid ◽  
Himan Shahabi ◽  
...  
Keyword(s):  
Point Cloud ◽  
Accuracy Assessment ◽  
Low Cost ◽  
Image Data ◽  
Flying Height ◽  
Surface Model ◽  
Lidar Data ◽  
Local Accuracy ◽  
Uav Images ◽  
Uav Image

Unmanned Aerial Vehicle (UAV) is one of the latest technologies for high spatial resolution 3D modeling of the Earth. The objectives of this study are to assess low-cost UAV data using image radiometric transformation techniques and investigate its effects on global and local accuracy of the Digital Surface Model (DSM). This research uses UAV Light Detection and Ranging (LIDAR) data from 80 meters and UAV Drone data from 300 and 500 meters flying height. RAW UAV images acquired from 500 meters flying height are radiometrically transformed in Matrix Laboratory (MATLAB). UAV images from 300 meters flying height are processed for the generation of 3D point cloud and DSM in Pix4D Mapper. UAV LIDAR data are used for the acquisition of Ground Control Points (GCP) and accuracy assessment of UAV Image data products. Accuracy of enhanced DSM with DSM generated from 300 meters flight height were analyzed for point cloud number, density and distribution. Root Mean Square Error (RMSE) value of Z is enhanced from ±2.15 meters to 0.11 meters. For local accuracy assessment of DSM, four different types of land covers are statistically compared with UAV LIDAR resulting in compatibility of enhancement technique with UAV LIDAR accuracy.

scholarly journals Accuracy Analysis of a 3D Model of Excavation, Created from Images Acquired with an Action Camera from Low Altitudes

2019 ◽  
Vol 8 (2) ◽  
pp. 83 ◽  
Author(s):  
Damian Wierzbicki ◽  
Marcin Nienaltowski
Keyword(s):  
Point Cloud ◽  
3D Model ◽  
Reference Model ◽  
Low Cost ◽  
Satellite System ◽  
Practical Aspect ◽  
Average Height ◽  
Digital Cameras ◽  
Aerial Photogrammetry ◽  
Dense Point

In the last few years, Unmanned Aerial Vehicles (UAVs) equipped with compact digital cameras, have become a cheap and efficient alternative to classic aerial photogrammetry and close-range photogrammetry. Low-altitude photogrammetry has great potential not only in the development of orthophoto maps but is also increasingly used in surveying and rapid mapping. This paper presents a practical aspect of the application of the custom homemade low-cost UAV, equipped with an action camera, to obtain images from low altitudes and develop a digital elevation model of the excavation. The conducted analyses examine the possibilities of using low-cost UAVs to deliver useful photogrammetric products. The experiments were carried out on a closed excavation in the town of Mince (north-eastern Poland). The flight over the examined area was carried out autonomously. A photogrammetric network was designed, and the reference areas in the mine were measured using the Global Navigation Satellite System-Real Time Kinematic (GNSS-RTK) method to perform accuracy analyses of the excavation 3D model. Representation of the created numerical terrain model was a dense point cloud. The average height difference between the generated dense point cloud and the reference model was within the range of 0.01–0.13 m. The difference between the volume of the excavation measured by the GNSS kinematic method and the volume measured on the basis of a dense point cloud was less than 1%. The obtained results show that the application of the low-cost UAV equipped with an action camera with a wide-angle lens, allows for obtaining high-accuracy images comparable to classic, compact digital cameras.

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