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Structure from Motion (SfM) Photogrammetry for Geomatics and Geoscience Applications
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Structure from Motion (SfM) Photogrammetry for Geomatics and Geoscience Applications

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing Image Processing".

Deadline for manuscript submissions: closed (31 January 2020) | Viewed by 100747

Special Issue Editors

Prof. Dr. Antonio Vettore

E-Mail Website
Guest Editor
Interdepartmental Research Center of Geomatics (CIRGEO), University of Padova, via dell’Università 16, 35020 Legnaro (PD), Italy
Interests: geomatics; mobile mapping; laser scanning; photogrammetry; remote sensing; navigation; unmanned aerial vehicles; cultural heritage; GIS
Special Issues, Collections and Topics in MDPI journals
Dr. Andrea Masiero

E-Mail Website
Guest Editor
Secretary of ISPRS WG I/7—Mobile Mapping Technology, Interdepartmental Research Center of Geomatics (CIRGEO), University of Padua, Padua, Italy
Interests: geomatics; mobile mapping; laser scanning; photogrammetry; remote sensing; navigation; data processing; machine learning; unmanned aerial vehicles; cultural heritage
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Ayman F. Habib

E-Mail Website
Guest Editor
Lyles School of Civil Engineering, Purdue University, West Lafayette, IN 47907, USA
Interests: photogrammetry; laser scanning; mobile mapping systems; system calibration; computer vision; unmanned aerial mapping systems; multisensor/multiplatform data integration
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Nowadays, a large number of applications require reliable geometric information about objects and the environment. The most commonly-used techniques for obtaining such 3D information without contact with the objects are usually LiDAR (Light Detection And Ranging) and photogrammetry. Despite both these techniques are widely used, and sometimes integrated together, two key factors are motivating the recent fast increase of photogrammetry usage: the availability of low cost cameras, which can easily mounted on UAVs (Unmanned Aerial Vehicles) and are commonly embedded in smartphones or other mobile devices, and to the recent introduction of almost automated software, typically based on the Structure from Motion approach, for easily obtaining tridimensional information from images.

The aim of this Special Issue is that of presenting new research advancements on methodological and algorithmic aspects on photogrammetry and Structure from Motion, on the integration of photogrammetric reconstruction with other systems, on the processing and analysis of image-based tridimensional data, and on the use of photogrammetry in applications related in particular to geomatics, geosciences, and related fields, such as surveying, mobile mapping, hydrology, geomorphology, civil engineering, architecture, cultural heritage, and precision farming.

Dr. Antonio Vettore

Dr. Andrea Masiero

Prof. Dr. Ayman F. Habib

Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Photogrammetry
  • Structure from Motion
  • Geoscience
  • Geomatics
  • UAV
  • 3D data processing
  • Mobile mapping
  • DTM
  • Remote Sensing
  • GIS

Published Papers (17 papers)

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23 pages, 6048 KiB  
Article
Crop Loss Evaluation Using Digital Surface Models from Unmanned Aerial Vehicles Data
by Virginia E. Garcia Millan, Cassidy Rankine and G. Arturo Sanchez-Azofeifa
Remote Sens. 2020, 12(6), 981; https://doi.org/10.3390/rs12060981 - 18 Mar 2020
Cited by 16 | Viewed by 4588
Abstract
Precision agriculture and Unmanned Aerial Vehicles (UAV) are revolutionizing agriculture management methods. Remote sensing data, image analysis and Digital Surface Models derived from Structure from Motion and Multi-View Stereopsis offer new and fast methods to detect the needs of crops, greatly improving crops [...] Read more.
Precision agriculture and Unmanned Aerial Vehicles (UAV) are revolutionizing agriculture management methods. Remote sensing data, image analysis and Digital Surface Models derived from Structure from Motion and Multi-View Stereopsis offer new and fast methods to detect the needs of crops, greatly improving crops efficiency. In this study, we present a tool to detect and estimate crop damage after a disturbance (i.e., weather event, wildlife attacks or fires). The types of damage that are addressed in this study affect crop structure (i.e., plants are bent or gone), in the shape of depressions in the crop canopy. The aim of this study was to evaluate the performance of four unsupervised methods based on terrain analyses, for the detection of damaged crops in UAV 3D models: slope detection, variance analysis, geomorphology classification and cloth simulation filter. A full workflow was designed and described in this article that involves the postprocessing of the raw results from the terrain analyses, for a refinement in the detection of damages. Our results show that all four methods performed similarly well after postprocessing––reaching an accuracy above to 90%––in the detection of severe crop damage, without the need of training data. The results of this study suggest that the used methods are effective and independent of the crop type, crop damage and growth stage. However, only severe damages were detected with this workflow. Other factors such as data volume, processing time, number of processing steps and spatial distribution of targets and errors are discussed in this article for the selection of the most appropriate method. Among the four tested methods, slope analysis involves less processing steps, generates the smallest data volume, is the fastest of methods and resulted in best spatial distribution of matches. Thus, it was selected as the most efficient method for crop damage detection. Full article
(This article belongs to the Special Issue Structure from Motion (SfM) Photogrammetry for Geomatics and Geoscience Applications)
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23 pages, 21187 KiB  
Article
Determining the Suitable Number of Ground Control Points for UAS Images Georeferencing by Varying Number and Spatial Distribution
by Valeria-Ersilia Oniga, Ana-Ioana Breaban, Norbert Pfeifer and Constantin Chirila
Remote Sens. 2020, 12(5), 876; https://doi.org/10.3390/rs12050876 - 09 Mar 2020
Cited by 41 | Viewed by 5005
Abstract
Currently, products that are obtained by Unmanned Aerial Systems (UAS) image processing based on structure-from-motion photogrammetry (SfM) are being investigated for use in high precision projects. Independent of the georeferencing process being done directly or indirectly, Ground Control Points (GCPs) are needed to [...] Read more.
Currently, products that are obtained by Unmanned Aerial Systems (UAS) image processing based on structure-from-motion photogrammetry (SfM) are being investigated for use in high precision projects. Independent of the georeferencing process being done directly or indirectly, Ground Control Points (GCPs) are needed to increase the accuracy of the obtained products. A minimum of three GCPs is required to bring the results into a desired coordinate system through the indirect georeferencing process, but it is well known that increasing the number of GCPs will lead to a higher accuracy of the final results. The aim of this study is to find the suitable number of GCPs to derive high precision results and what is the effect of GCPs systematic or stratified random distribution on the accuracy of the georeferencing process and the final products, respectively. The case study involves an urban area of about 1 ha that was photographed with a low-cost UAS, namely, the DJI Phantom 3 Standard, at 28 m above ground. The camera was oriented in a nadiral position and 300 points were measured using a total station in a local coordinate system. The UAS images were processed using the 3DF Zephyr software performing a full BBA with a variable number of GCPs i.e., from four up to 150, while the number and the spatial location of check points (ChPs) was kept constant i.e., 150 for each independent distribution. In addition, the systematic and stratified random distribution of GCPs and ChPs spatial positions was analysed. Furthermore, the point clouds and the mesh surfaces that were automatically derived were compared with a terrestrial laser scanner (TLS) point cloud while also considering three test areas: two inside the area defined by GCPs and one outside the area. The results expressed a clear overview of the number of GCPs needed for the indirect georeferencing process with minimum influence on the final results. The RMSE can be reduced down to 50% when switching from four to 20 GCPs, whereas a higher number of GCPs only slightly improves the results. Full article
(This article belongs to the Special Issue Structure from Motion (SfM) Photogrammetry for Geomatics and Geoscience Applications)
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37 pages, 13045 KiB  
Article
GNSS/INS-Assisted Structure from Motion Strategies for UAV-Based Imagery over Mechanized Agricultural Fields
by Seyyed Meghdad Hasheminasab, Tian Zhou and Ayman Habib
Remote Sens. 2020, 12(3), 351; https://doi.org/10.3390/rs12030351 - 21 Jan 2020
Cited by 36 | Viewed by 4606
Abstract
Acquired imagery by unmanned aerial vehicles (UAVs) has been widely used for three-dimensional (3D) reconstruction/modeling in various digital agriculture applications, such as phenotyping, crop monitoring, and yield prediction. 3D reconstruction from well-textured UAV-based images has matured and the user community has access to [...] Read more.
Acquired imagery by unmanned aerial vehicles (UAVs) has been widely used for three-dimensional (3D) reconstruction/modeling in various digital agriculture applications, such as phenotyping, crop monitoring, and yield prediction. 3D reconstruction from well-textured UAV-based images has matured and the user community has access to several commercial and opensource tools that provide accurate products at a high level of automation. However, in some applications, such as digital agriculture, due to repetitive image patterns, these approaches are not always able to produce reliable/complete products. The main limitation of these techniques is their inability to establish a sufficient number of correctly matched features among overlapping images, causing incomplete and/or inaccurate 3D reconstruction. This paper provides two structure from motion (SfM) strategies, which use trajectory information provided by an onboard survey-grade global navigation satellite system/inertial navigation system (GNSS/INS) and system calibration parameters. The main difference between the proposed strategies is that the first one—denoted as partially GNSS/INS-assisted SfM—implements the four stages of an automated triangulation procedure, namely, imaging matching, relative orientation parameters (ROPs) estimation, exterior orientation parameters (EOPs) recovery, and bundle adjustment (BA). The second strategy— denoted as fully GNSS/INS-assisted SfM—removes the EOPs estimation step while introducing a random sample consensus (RANSAC)-based strategy for removing matching outliers before the BA stage. Both strategies modify the image matching by restricting the search space for conjugate points. They also implement a linear procedure for ROPs’ refinement. Finally, they use the GNSS/INS information in modified collinearity equations for a simpler BA procedure that could be used for refining system calibration parameters. Eight datasets over six agricultural fields are used to evaluate the performance of the developed strategies. In comparison with a traditional SfM framework and Pix4D Mapper Pro, the proposed strategies are able to generate denser and more accurate 3D point clouds as well as orthophotos without any gaps. Full article
(This article belongs to the Special Issue Structure from Motion (SfM) Photogrammetry for Geomatics and Geoscience Applications)
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27 pages, 33902 KiB  
Article
Measuring Change Using Quantitative Differencing of Repeat Structure-From-Motion Photogrammetry: The Effect of Storms on Coastal Boulder Deposits
by Timothy Nagle-McNaughton and Rónadh Cox
Remote Sens. 2020, 12(1), 42; https://doi.org/10.3390/rs12010042 - 20 Dec 2019
Cited by 15 | Viewed by 5620
Abstract
Repeat photogrammetry is increasingly the go-too tool for long-term geomorphic monitoring, but quantifying the differences between structure-from-motion (SfM) models is a developing field. Volumetric differencing software (such as the open-source package CloudCompare) provides an efficient mechanism for quantifying change in landscapes. In this [...] Read more.
Repeat photogrammetry is increasingly the go-too tool for long-term geomorphic monitoring, but quantifying the differences between structure-from-motion (SfM) models is a developing field. Volumetric differencing software (such as the open-source package CloudCompare) provides an efficient mechanism for quantifying change in landscapes. In this case study, we apply this methodology to coastal boulder deposits on Inishmore, Ireland. Storm waves are known to move these rocks, but boulder transportation and evolution of the deposits are not well documented. We used two disparate SfM data sets for this analysis. The first model was built from imagery captured in 2015 using a GoPro Hero 3+ camera (fisheye lens) and the second used 2017 imagery from a DJI FC300X camera (standard digital single-lens reflex (DSLR) camera); and we used CloudCompare to measure the differences between them. This study produced two noteworthy findings: First, volumetric differencing reveals that short-term changes in boulder deposits can be larger than expected, and that frequent monitoring can reveal not only the scale but the complexities of boulder transport in this setting. This is a valuable addition to our growing understanding of coastal boulder deposits. Second, SfM models generated by different imaging hardware can be successfully compared at sub-decimeter resolution, even when one of the camera systems has substantial lens distortion. This means that older image sets, which might not otherwise be considered of appropriate quality for co-analysis with more recent data, should not be ignored as data sources in long-term monitoring studies. Full article
(This article belongs to the Special Issue Structure from Motion (SfM) Photogrammetry for Geomatics and Geoscience Applications)
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22 pages, 7514 KiB  
Article
Accurate Calibration Scheme for a Multi-Camera Mobile Mapping System
by Ehsan Khoramshahi, Mariana Batista Campos, Antonio Maria Garcia Tommaselli, Niko Vilijanen, Teemu Mielonen, Harri Kaartinen, Antero Kukko and Eija Honkavaara
Remote Sens. 2019, 11(23), 2778; https://doi.org/10.3390/rs11232778 - 25 Nov 2019
Cited by 10 | Viewed by 5372
Abstract
Mobile mapping systems (MMS) are increasingly used for many photogrammetric and computer vision applications, especially encouraged by the fast and accurate geospatial data generation. The accuracy of point position in an MMS is mainly dependent on the quality of calibration, accuracy of sensor [...] Read more.
Mobile mapping systems (MMS) are increasingly used for many photogrammetric and computer vision applications, especially encouraged by the fast and accurate geospatial data generation. The accuracy of point position in an MMS is mainly dependent on the quality of calibration, accuracy of sensor synchronization, accuracy of georeferencing and stability of geometric configuration of space intersections. In this study, we focus on multi-camera calibration (interior and relative orientation parameter estimation) and MMS calibration (mounting parameter estimation). The objective of this study was to develop a practical scheme for rigorous and accurate system calibration of a photogrammetric mapping station equipped with a multi-projective camera (MPC) and a global navigation satellite system (GNSS) and inertial measurement unit (IMU) for direct georeferencing. The proposed technique is comprised of two steps. Firstly, interior orientation parameters of each individual camera in an MPC and the relative orientation parameters of each cameras of the MPC with respect to the first camera are estimated. In the second step the offset and misalignment between MPC and GNSS/IMU are estimated. The global accuracy of the proposed method was assessed using independent check points. A correspondence map for a panorama is introduced that provides metric information. Our results highlight that the proposed calibration scheme reaches centimeter-level global accuracy for 3D point positioning. This level of global accuracy demonstrates the feasibility of the proposed technique and has the potential to fit accurate mapping purposes. Full article
(This article belongs to the Special Issue Structure from Motion (SfM) Photogrammetry for Geomatics and Geoscience Applications)
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16 pages, 2286 KiB  
Article
Relative Importance of Binocular Disparity and Motion Parallax for Depth Estimation: A Computer Vision Approach
by Mostafa Mansour, Pavel Davidson, Oleg Stepanov and Robert Piché
Remote Sens. 2019, 11(17), 1990; https://doi.org/10.3390/rs11171990 - 23 Aug 2019
Cited by 19 | Viewed by 5885
Abstract
Binocular disparity and motion parallax are the most important cues for depth estimation in human and computer vision. Here, we present an experimental study to evaluate the accuracy of these two cues in depth estimation to stationary objects in a static environment. Depth [...] Read more.
Binocular disparity and motion parallax are the most important cues for depth estimation in human and computer vision. Here, we present an experimental study to evaluate the accuracy of these two cues in depth estimation to stationary objects in a static environment. Depth estimation via binocular disparity is most commonly implemented using stereo vision, which uses images from two or more cameras to triangulate and estimate distances. We use a commercial stereo camera mounted on a wheeled robot to create a depth map of the environment. The sequence of images obtained by one of these two cameras as well as the camera motion parameters serve as the input to our motion parallax-based depth estimation algorithm. The measured camera motion parameters include translational and angular velocities. Reference distance to the tracked features is provided by a LiDAR. Overall, our results show that at short distances stereo vision is more accurate, but at large distances the combination of parallax and camera motion provide better depth estimation. Therefore, by combining the two cues, one obtains depth estimation with greater range than is possible using either cue individually. Full article
(This article belongs to the Special Issue Structure from Motion (SfM) Photogrammetry for Geomatics and Geoscience Applications)
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36 pages, 10574 KiB  
Article
New Strategies for Time Delay Estimation during System Calibration for UAV-Based GNSS/INS-Assisted Imaging Systems
by Lisa LaForest, Seyyed Meghdad Hasheminasab, Tian Zhou, John Evan Flatt and Ayman Habib
Remote Sens. 2019, 11(15), 1811; https://doi.org/10.3390/rs11151811 - 01 Aug 2019
Cited by 18 | Viewed by 4101
Abstract
The need for accurate 3D spatial information is growing rapidly in many of today’s key industries, such as precision agriculture, emergency management, infrastructure monitoring, and defense. Unmanned aerial vehicles (UAVs) equipped with global navigation satellite systems/inertial navigation systems (GNSS/INS) and consumer-grade digital imaging [...] Read more.
The need for accurate 3D spatial information is growing rapidly in many of today’s key industries, such as precision agriculture, emergency management, infrastructure monitoring, and defense. Unmanned aerial vehicles (UAVs) equipped with global navigation satellite systems/inertial navigation systems (GNSS/INS) and consumer-grade digital imaging sensors are capable of providing accurate 3D spatial information at a relatively low cost. However, with the use of consumer-grade sensors, system calibration is critical for accurate 3D reconstruction. In this study, ‘consumer-grade’ refers to cameras that require system calibration by the user instead of by the manufacturer or other high-end laboratory settings, as well as relatively low-cost GNSS/INS units. In addition to classical spatial system calibration, many consumer-grade sensors also need temporal calibration for accurate 3D reconstruction. This study examines the accuracy impact of time delay in the synchronization between the GNSS/INS unit and cameras on-board UAV-based mapping systems. After reviewing existing strategies, this study presents two approaches (direct and indirect) to correct for time delay between GNSS/INS recorded event markers and actual time of image exposure. Our results show that both approaches are capable of handling and correcting this time delay, with the direct approach being more rigorous. When a time delay exists and the direct or indirect approach is applied, horizontal accuracy of 1–3 times the ground sampling distance (GSD) can be achieved without either the use of any ground control points (GCPs) or adjusting the original GNSS/INS trajectory information. Full article
(This article belongs to the Special Issue Structure from Motion (SfM) Photogrammetry for Geomatics and Geoscience Applications)
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20 pages, 3821 KiB  
Article
Indirect UAV Strip Georeferencing by On-Board GNSS Data under Poor Satellite Coverage
by Gianfranco Forlani, Fabrizio Diotri, Umberto Morra di Cella and Riccardo Roncella
Remote Sens. 2019, 11(15), 1765; https://doi.org/10.3390/rs11151765 - 26 Jul 2019
Cited by 39 | Viewed by 3949
Abstract
The so-called Real Time Kinematic (RTK) option, which allows one to determine with cm-level accuracy the Unmanned Aerial Vehicles (UAV) camera position at shooting time, is also being made available on medium- or low-cost drones. It can be foreseen that a sizeable amount [...] Read more.
The so-called Real Time Kinematic (RTK) option, which allows one to determine with cm-level accuracy the Unmanned Aerial Vehicles (UAV) camera position at shooting time, is also being made available on medium- or low-cost drones. It can be foreseen that a sizeable amount of UAV surveys will be soon performed (almost) without Ground Control Points (GCP). However, obstacles to Global Navigation Satellite Systems (GNSS) signal at the optimal flight altitude might prevent accurate retrieval of camera station positions, e.g., in narrow gorges. In such cases, the master block can be georeferenced by tying it to an (auxiliary) block flown at higher altitude, where the GNSS signal is not impeded. To prove the point in a worst case scenario, but under controlled conditions, an experiment was devised. A single strip about 700 m long, surveyed by a multi-copter at 30 m relative flight height, was referenced with cm-level accuracy by joint adjustment with a block flown at 100 m relative flight height, acquired by a fixed-wing UAV provided with RTK option. The joint block orientation was repeated with or without GCP and with pre-calibrated or self-calibrated camera parameters. Accuracy on ground was assessed on a fair number of Check Points (CP). The results show that, even without GCP, the precision is effectively transferred from the auxiliary block projection centres to the object point horizontal coordinates and, with a pre-calibrated camera, also to the elevations. Full article
(This article belongs to the Special Issue Structure from Motion (SfM) Photogrammetry for Geomatics and Geoscience Applications)
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19 pages, 10167 KiB  
Article
Modelling the Surface of Racing Vessel’s Hull by Laser Scanning and Digital Photogrammetry
by Karol Bartoš, Katarína Pukanská, Peter Repáň, Ľubomír Kseňak and Janka Sabová
Remote Sens. 2019, 11(13), 1526; https://doi.org/10.3390/rs11131526 - 27 Jun 2019
Cited by 12 | Viewed by 3797
Abstract
The knowledge of the hull shape and geometry of a racing vessel is one of the most important factors for predicting boat performance. The Offshore Racing Congress (ORC) rating system specifies the calculation parameters of the hydrodynamic forces of boat lift and drag [...] Read more.
The knowledge of the hull shape and geometry of a racing vessel is one of the most important factors for predicting boat performance. The Offshore Racing Congress (ORC) rating system specifies the calculation parameters of the hydrodynamic forces of boat lift and drag on the basis of input data as the length of waterline while sailing, displacement, wetted surface and the volume distribution along the hull. It is represented by sophisticated calculations for national as well as international events and races. Measurement using a reflectorless total station in a coordinate system defined by the sailboat hull is the most established method approved by the ORC organisation. The determination of these geometric parameters by new, unconventional technologies, which should provide a quicker and more detailed measurement while preserving the quality and accuracy of results necessary for the handicap calculations was our main objective. Geometrical shapes of a cabin sailboat hull were determined by the technology of terrestrial laser scanning and two methods of digital close-range photogrammetry—convergence case of photogrammetry and Structure-from-Motion (SfM) method. High-Definition Surveying (HDS) targets for laser scanning and coded targets for digital photogrammetry were used throughout all methods in order to transform the resulting data into a single local coordinate system. The resulting models were mutually compared by visual, geometrical and statistical comparison. In conclusion, both technologies were considered suitable, however, with various advantages and disadvantages. Nevertheless, although labour intensive, the SfM photogrammetry can be considered the most suitable method if the correct procedures are followed. Full article
(This article belongs to the Special Issue Structure from Motion (SfM) Photogrammetry for Geomatics and Geoscience Applications)
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27 pages, 11934 KiB  
Article
Monitoring and Computation of the Volumes of Stockpiles of Bulk Material by Means of UAV Photogrammetric Surveying
by Grazia Tucci, Antonio Gebbia, Alessandro Conti, Lidia Fiorini and Claudio Lubello
Remote Sens. 2019, 11(12), 1471; https://doi.org/10.3390/rs11121471 - 21 Jun 2019
Cited by 43 | Viewed by 5396
Abstract
The monitoring and metric assessment of piles of natural or man-made materials plays a fundamental role in the production and management processes of multiple activities. Over time, the monitoring techniques have undergone an evolution linked to the progress of measure and data processing [...] Read more.
The monitoring and metric assessment of piles of natural or man-made materials plays a fundamental role in the production and management processes of multiple activities. Over time, the monitoring techniques have undergone an evolution linked to the progress of measure and data processing techniques; starting from classic topography to global navigation satellite system (GNSS) technologies up to the current survey systems like laser scanner and close-range photogrammetry. Last-generation 3D data management software allow for the processing of increasingly truer high-resolution 3D models. This study shows the results of a test for the monitoring and computing of stockpile volumes of material coming from the differentiated waste collection inserted in the recycling chain, performed by means of an unmanned aerial vehicle (UAV) photogrammetric survey and the generation of 3D models starting from point clouds. The test was carried out with two UAV flight sessions, with vertical and oblique camera configurations, and using a terrestrial laser scanner for measuring the ground control points and as ground truth for testing the two survey configurations. The computations of the volumes were carried out using two software and comparisons were made both with reference to the different survey configurations and to the computation software. Full article
(This article belongs to the Special Issue Structure from Motion (SfM) Photogrammetry for Geomatics and Geoscience Applications)
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18 pages, 7916 KiB  
Article
A Fisheye Image Matching Method Boosted by Recursive Search Space for Close Range Photogrammetry
by Mariana Batista Campos, Antonio Maria Garcia Tommaselli, Letícia Ferrari Castanheiro, Raquel Alves Oliveira and Eija Honkavaara
Remote Sens. 2019, 11(12), 1404; https://doi.org/10.3390/rs11121404 - 13 Jun 2019
Cited by 8 | Viewed by 4435
Abstract
Close range photogrammetry (CRP) with large field-of-view images has become widespread in recent years, especially in terrestrial mobile mapping systems (TMMS). However, feature-based matching (FBM) with omnidirectional images (e.g., fisheye) is challenging even for state-of-the-art methods, such as the scale-invariant feature transform (SIFT), [...] Read more.
Close range photogrammetry (CRP) with large field-of-view images has become widespread in recent years, especially in terrestrial mobile mapping systems (TMMS). However, feature-based matching (FBM) with omnidirectional images (e.g., fisheye) is challenging even for state-of-the-art methods, such as the scale-invariant feature transform (SIFT), because of the strong scale change from image to image. This paper proposes an approach to boost FBM techniques on fisheye images with recursive reduction of the search space based on epipolar geometry. The epipolar restriction is calculated with the equidistant mathematical model and the initial exterior orientation parameters (EOPs) determined with navigation sensors from TMMS. The proposed method was assessed with data sets acquired by a low-cost TMMS. The TMMS is composed of a calibrated poly-dioptric system (Ricoh Theta S) and navigation sensors aimed at outdoor applications. The assessments show that Ricoh Theta S position and attitude were estimated in a global bundle adjustment with a precision (standard deviation) of 4 cm and 0.3°, respectively, using as observations the detected matches from the proposed method. Compared with other methods based on SIFT extended to the omnidirectional geometry, our approach achieved compatible results for outdoor applications. Full article
(This article belongs to the Special Issue Structure from Motion (SfM) Photogrammetry for Geomatics and Geoscience Applications)
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14 pages, 7238 KiB  
Article
Corridor Mapping of Sandy Coastal Foredunes with UAS Photogrammetry and Mobile Laser Scanning
by Alphonse Nahon, Pere Molina, Marta Blázquez, Jennifer Simeon, Sylvain Capo and Cédrik Ferrero
Remote Sens. 2019, 11(11), 1352; https://doi.org/10.3390/rs11111352 - 05 Jun 2019
Cited by 24 | Viewed by 4536
Abstract
Recurrent monitoring of sandy beaches and of the dunes behind them is needed to improve the scientific knowledge on their dynamics as well as to develop sustainable management practices of those valuable landforms. Unmanned Aircraft Systems (UAS) are sought as a means to [...] Read more.
Recurrent monitoring of sandy beaches and of the dunes behind them is needed to improve the scientific knowledge on their dynamics as well as to develop sustainable management practices of those valuable landforms. Unmanned Aircraft Systems (UAS) are sought as a means to fulfill this need, especially leveraged by photogrammetric and LiDAR-based mapping methods and technology. The present study compares different strategies to carry UAS photogrammetric corridor mapping over linear extensions of sandy shores. In particular, we present results on the coupling of a UAS with a mobile laser scanning system, operating simultaneously in Cap Ferret, SW France. This aerial-terrestrial tandem enables terrain reconstruction with kinematic ground control points, thus largely avoiding the deployment of surveyed ground control points on the non-stable sandy ground. Results show how these three techniques—mobile laser scanning, photogrammetry based on ground control points, and photogrammetry based on kinematic ground control points—deliver accurate (i.e., root mean square errors < 15 cm) 3D reconstruction of beach-to-dune transition areas, the latter being performed at lower survey and logistic costs, and with enhanced spatial coverage capabilities. This study opens the gate for exploring longer (hundreds of kilometers) shoreline dynamics with ground-control-point-free air and ground mapping techniques. Full article
(This article belongs to the Special Issue Structure from Motion (SfM) Photogrammetry for Geomatics and Geoscience Applications)
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16 pages, 9609 KiB  
Article
Mapping of River Terraces with Low-Cost UAS Based Structure-from-Motion Photogrammetry in a Complex Terrain Setting
by Hui Li, Lin Chen, Zhaoyang Wang and Zhongdi Yu
Remote Sens. 2019, 11(4), 464; https://doi.org/10.3390/rs11040464 - 24 Feb 2019
Cited by 14 | Viewed by 6265
Abstract
River terraces are the principal geomorphic features for unraveling tectonics, sea level, and climate conditions during the evolutionary history of a river. The increasing availability of high-resolution topography data generated by low-cost Unmanned Aerial Systems (UAS) and modern photogrammetry offer an opportunity to [...] Read more.
River terraces are the principal geomorphic features for unraveling tectonics, sea level, and climate conditions during the evolutionary history of a river. The increasing availability of high-resolution topography data generated by low-cost Unmanned Aerial Systems (UAS) and modern photogrammetry offer an opportunity to identify and characterize these features. In this paper, we assessed the capabilities of UAS-based Structure-from-Motion (SfM) photogrammetry, coupled with a river terrace detection algorithm for mapping of river terraces over a 1.9 km2 valley of complex terrain setting, with a focus on the performance of this latest technology over such complex terrains. With the proposed image acquisition approach and SfM photogrammetry, we constructed a 3.8 cm resolution orthomosaic and digital surface model (DSM). The vertical accuracy of DSM was assessed against 196 independent checkpoints measured with a real-time kinematic (RTK) GPS. The results indicated that the root mean square error (RMSE) and mean absolute error (MAE) were 3.1 cm and 2.9 cm, respectively. These encouraging results suggest that this low-cost, logistically simple method can deliver high-quality terrain datasets even in the complex terrain, competitive with those obtained using more expensive laser scanning. A simple algorithm was then employed to detect river terraces from the generated DSM. The results showed that three levels of river terraces and a high-level floodplain were identified. Most of the detected river terraces were confirmed by field observations. Despite the highly erosive nature of fluvial systems, this work obtained good results, allowing fast analysis of fluvial valleys and their comparison. Overall, our results demonstrated that the low-cost UAS-based SfM technique could yield highly accurate ultrahigh-resolution topography data over complex terrain settings, making it particularly suitable for quick and cost-effective mapping of micro to medium-sized geomorphic features under such terrains in remote or poorly accessible areas. Methods discussed in this paper can also be applied to produce highly accurate digital terrain data over large spatial extents for some other places of complex terrains. Full article
(This article belongs to the Special Issue Structure from Motion (SfM) Photogrammetry for Geomatics and Geoscience Applications)
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34 pages, 9292 KiB  
Article
Automated Aerial Triangulation for UAV-Based Mapping
by Fangning He, Tian Zhou, Weifeng Xiong, Seyyed Meghdad Hasheminnasab and Ayman Habib
Remote Sens. 2018, 10(12), 1952; https://doi.org/10.3390/rs10121952 - 04 Dec 2018
Cited by 57 | Viewed by 8682
Abstract
Accurate 3D reconstruction/modelling from unmanned aerial vehicle (UAV)-based imagery has become the key prerequisite in various applications. Although current commercial software has automated the process of image-based reconstruction, a transparent system, which can be incorporated with different user-defined constraints, is still preferred by [...] Read more.
Accurate 3D reconstruction/modelling from unmanned aerial vehicle (UAV)-based imagery has become the key prerequisite in various applications. Although current commercial software has automated the process of image-based reconstruction, a transparent system, which can be incorporated with different user-defined constraints, is still preferred by the photogrammetric research community. In this regard, this paper presents a transparent framework for the automated aerial triangulation of UAV images. The proposed framework is conducted in three steps. In the first step, two approaches, which take advantage of prior information regarding the flight trajectory, are implemented for reliable relative orientation recovery. Then, initial recovery of image exterior orientation parameters (EOPs) is achieved through either an incremental or global approach. Finally, a global bundle adjustment involving Ground Control Points (GCPs) and check points is carried out to refine all estimated parameters in the defined mapping coordinate system. Four real image datasets, which are acquired by two different UAV platforms, have been utilized to evaluate the feasibility of the proposed framework. In addition, a comparative analysis between the proposed framework and the existing commercial software is performed. The derived experimental results demonstrate the superior performance of the proposed framework in providing an accurate 3D model, especially when dealing with acquired UAV images containing repetitive pattern and significant image distortions. Full article
(This article belongs to the Special Issue Structure from Motion (SfM) Photogrammetry for Geomatics and Geoscience Applications)
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19 pages, 7311 KiB  
Article
Accuracy of Unmanned Aerial Vehicle (UAV) and SfM Photogrammetry Survey as a Function of the Number and Location of Ground Control Points Used
by Enoc Sanz-Ablanedo, Jim H. Chandler, José Ramón Rodríguez-Pérez and Celestino Ordóñez
Remote Sens. 2018, 10(10), 1606; https://doi.org/10.3390/rs10101606 - 09 Oct 2018
Cited by 263 | Viewed by 14407
Abstract
The geometrical accuracy of georeferenced digital surface models (DTM) obtained from images captured by micro-UAVs and processed by using structure from motion (SfM) photogrammetry depends on several factors, including flight design, camera quality, camera calibration, SfM algorithms and georeferencing strategy. This paper focusses [...] Read more.
The geometrical accuracy of georeferenced digital surface models (DTM) obtained from images captured by micro-UAVs and processed by using structure from motion (SfM) photogrammetry depends on several factors, including flight design, camera quality, camera calibration, SfM algorithms and georeferencing strategy. This paper focusses on the critical role of the number and location of ground control points (GCP) used during the georeferencing stage. A challenging case study involving an area of 1200+ ha, 100+ GCP and 2500+ photos was used. Three thousand, four hundred and sixty-five different combinations of control points were introduced in the bundle adjustment, whilst the accuracy of the model was evaluated using both control points and independent check points. The analysis demonstrates how much the accuracy improves as the number of GCP points increases, as well as the importance of an even distribution, how much the accuracy is overestimated when it is quantified only using control points rather than independent check points, and how the ground sample distance (GSD) of a project relates to the maximum accuracy that can be achieved. Full article
(This article belongs to the Special Issue Structure from Motion (SfM) Photogrammetry for Geomatics and Geoscience Applications)
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22 pages, 16672 KiB  
Article
Efficient SfM for Oblique UAV Images: From Match Pair Selection to Geometrical Verification
by San Jiang and Wanshou Jiang
Remote Sens. 2018, 10(8), 1246; https://doi.org/10.3390/rs10081246 - 08 Aug 2018
Cited by 30 | Viewed by 5255
Abstract
Accurate orientation is required for the applications of UAV (Unmanned Aerial Vehicle) images. In this study, an integrated Structure from Motion (SfM) solution is proposed, which aims to address three issues to ensure the efficient and reliable orientation of oblique UAV images, including [...] Read more.
Accurate orientation is required for the applications of UAV (Unmanned Aerial Vehicle) images. In this study, an integrated Structure from Motion (SfM) solution is proposed, which aims to address three issues to ensure the efficient and reliable orientation of oblique UAV images, including match pair selection for large-volume images with large overlap degree, reliable feature matching of images captured from varying directions, and efficient geometrical verification of initial matches. By using four datasets captured with different oblique imaging systems, the proposed SfM solution is comprehensively compared and analyzed. The results demonstrate that linear computational costs can be achieved in feature extraction and matching; although high decrease ratios occur in image pairs, reliable orientation results are still obtained from both the relative and absolute bundle adjustment (BA) tests when compared with other software packages. For the orientation of oblique UAV images, the proposed method can be an efficient and reliable solution. Full article
(This article belongs to the Special Issue Structure from Motion (SfM) Photogrammetry for Geomatics and Geoscience Applications)
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Other

Jump to: Research

21 pages, 24690 KiB  
Technical Note
Digital Drill Core Models: Structure-from-Motion as a Tool for the Characterisation, Orientation, and Digital Archiving of Drill Core Samples
by Peter Betlem, Thomas Birchall, Kei Ogata, Joonsang Park, Elin Skurtveit and Kim Senger
Remote Sens. 2020, 12(2), 330; https://doi.org/10.3390/rs12020330 - 19 Jan 2020
Cited by 12 | Viewed by 6136
Abstract
Structure-from-motion (SfM) photogrammetry enables the cost-effective digital characterisation of seismic- to sub-decimetre-scale geoscientific samples. The technique is commonly used for the characterisation of outcrops, fracture mapping, and increasingly so for the quantification of deformation during geotechnical stress tests. We here apply SfM photogrammetry [...] Read more.
Structure-from-motion (SfM) photogrammetry enables the cost-effective digital characterisation of seismic- to sub-decimetre-scale geoscientific samples. The technique is commonly used for the characterisation of outcrops, fracture mapping, and increasingly so for the quantification of deformation during geotechnical stress tests. We here apply SfM photogrammetry using off-the-shelf components and software, to generate 25 digital drill core models of drill cores. The selected samples originate from the Longyearbyen CO2 Lab project’s borehole DH4, covering the lowermost cap rock and uppermost reservoir sequences proposed for CO2 sequestration onshore Svalbard. We have come up with a procedure that enables the determination of bulk volumes and densities with precisions and accuracies similar to those of such conventional methods as the immersion in fluid method. We use 3D printed replicas to qualitatively assure the volumes, and show that, with a mean deviation (based on eight samples) of 0.059% compared to proven geotechnical methods, the photogrammetric output is found to be equivalent. We furthermore splice together broken and fragmented core pieces to reconstruct larger core intervals. We unwrap these to generate and characterise 2D orthographic projections of the core edge using analytical workflows developed for the structure-sedimentological characterisation of virtual outcrop models. Drill core orthoprojections can be treated as directly correlatable to optical borehole-wall imagery data, enabling a direct and cost-effective elucidation of in situ drill core orientation and depth, as long as any form of borehole imagery is available. Digital drill core models are thus complementary to existing physical and photographic sample archives, and we foresee that the presented workflow can be adopted for the digitisation and digital storage of other types of geological samples, including degradable and dangerous ice and sediment cores and samples. Full article
(This article belongs to the Special Issue Structure from Motion (SfM) Photogrammetry for Geomatics and Geoscience Applications)
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