scholarly journals Structure-from-Motion-Derived Digital Surface Models from Historical Aerial Photographs: A New 3D Application for Coastal Dune Monitoring

2020 ◽  
Vol 13 (1) ◽  
pp. 95
Author(s):  
Edoardo Grottoli ◽  
Mélanie Biausque ◽  
David Rogers ◽  
Derek W. T. Jackson ◽  
J. Andrew G. Cooper
Keyword(s):  
Structure From Motion ◽  
Point Cloud ◽  
Depth Map ◽  
Coastal Dune ◽  
Aerial Photographs ◽  
Dune System ◽  
Surface Models ◽  
Dense Point ◽  
Cleaning Methods ◽  
Coastal Landform

Recent advances in structure-from-motion (SfM) techniques have proliferated the use of unmanned aerial vehicles (UAVs) in the monitoring of coastal landform changes, particularly when applied in the reconstruction of 3D surface models from historical aerial photographs. Here, we explore a number of depth map filtering and point cloud cleaning methods using the commercial software Agisoft Metashape Pro to determine the optimal methodology to build reliable digital surface models (DSMs). Twelve different aerial photography-derived DSMs are validated and compared against light detection and ranging (LiDAR)- and UAV-derived DSMs of a vegetated coastal dune system that has undergone several decades of coastline retreat. The different studied methods showed an average vertical error (root mean square error, RMSE) of approximately 1 m, with the best method resulting in an error value of 0.93 m. In our case, the best method resulted from the removal of confidence values in the range of 0–3 from the dense point cloud (DPC), with no filter applied to the depth maps. Differences among the methods examined were associated with the reconstruction of the dune slipface. The application of the modern SfM methodology to the analysis of historical aerial (vertical) photography is a novel (and reliable) new approach that can be used to better quantify coastal dune volume changes. DSMs derived from suitable historical aerial photographs, therefore, represent dependable sources of 3D data that can be used to better analyse long-term geomorphic changes in coastal dune areas that have undergone retreat.

scholarly journals TERRESTRIAL PHOTOGRAMMETRY VS LASER SCANNING FOR RAPID EARTHQUAKE DAMAGE ASSESSMENT

2018 ◽  
Vol XLII-3/W4 ◽  
pp. 527-533 ◽  
Author(s):  
C. Vasilakos ◽  
S. Chatzistamatis ◽  
O. Roussou ◽  
N. Soulakellis
Keyword(s):  
Structure From Motion ◽  
Damage Assessment ◽  
Point Cloud ◽  
Laser Scanning ◽  
Point Clouds ◽  
Earthquake Damage ◽  
Map Building ◽  
Dense Point ◽  
Terrestrial Photogrammetry ◽  
Earthquake Damage Assessment

<p><strong>Abstract.</strong> Building damage assessment caused by earthquakes is essential during the response phase following a catastrophic event. Modern techniques include terrestrial and aerial photogrammetry based on Structure from Motion algorithm and Laser Scanning with the latter to prove its superiority in accuracy assessment due to the high-density point clouds. However, standardized procedures during emergency surveys often could not be followed due to restrictions of outdoor operations because of debris or decrepit buildings, the high human presence of civil protection agencies, expedited deployment of survey team and cost of operations. The aim of this paper is to evaluate whether terrestrial photogrammetry based on a handheld amateur DSLR camera can be used to map building damages, structural deformations and facade production in an accepted accuracy comparing to laser scanning technique. The study area is the Vrisa village, Lesvos, Greece where a Mw&amp;thinsp;6.3 earthquake occurred on June 12th, 2017. A dense point cloud from some digital images created based on Structure from Motion algorithm and compared with a dense point cloud acquired by a laser scanner. The distance measurement and the comparison were conducted with the Multiscale Model to Model Cloud Comparison method. According to the results, the mean of the absolute distances between the two clouds is 0.038&amp;thinsp;m while the 94.9&amp;thinsp;% of the point distances are less than 0.1&amp;thinsp;m. Terrestrial photogrammetry proved to be an accurate methodology for rapid earthquake damage assessment thus its products were used by local authorities for the calculation of the compensation for the property loss.</p>

High-Resolution Structure-From-Motion Models and Orthophotos of the Southern Sections of the 2019 Mw 7.1 and 6.4 Ridgecrest Earthquakes Surface Ruptures

2020 ◽  
Vol 91 (4) ◽  
pp. 2124-2126 ◽  
Author(s):  
Ian Pierce ◽  
Alana Williams ◽  
Richard D. Koehler ◽  
Colin Chupik
Keyword(s):  
High Resolution ◽  
Structure From Motion ◽  
Point Cloud ◽  
Earthquake Sequence ◽  
Aerial Photographs ◽  
Motion Models ◽  
Cloud Models ◽  
High Resolution Structure ◽  
Surface Ruptures ◽  
Resolution Structure

Abstract Aerial photographs were collected in the days immediately following the 4–5 July 2019 Ridgecrest earthquake sequence (e.g., Barnhart et al., 2019) along the publically accessible sections of the surface ruptures south of California 178. These photos were then used to produce structure-from-motion point cloud models and orthophotos with resolutions varying from ∼1 to 20  cm/pixel. Here, the models are released and initial observations of the nature of the surface ruptures are presented.

scholarly journals LONG LINE CLIFF TOPOGRAPHY MEASUREMENT BY USING STRUCTURE FROM MOTION ALGORITHM IN PHOTOGRAMMETRY

2019 ◽  
Vol XLII-2/W13 ◽  
pp. 5-12
Author(s):  
C. Altuntas
Keyword(s):  
Structure From Motion ◽  
Point Cloud ◽  
Laser Scanning ◽  
3D Model ◽  
Measurement Techniques ◽  
High Accuracy ◽  
Aerial Laser Scanning ◽  
The Earth ◽  
Long Line ◽  
Dense Point

<p><strong>Abstract.</strong> The topography of cliffs and steep slopes must be measured to acquire additional information for landscaping, visualizing changes and taking precautions against natural hazards. The Earth topography has been measured predominantly with photogrammetry, terrestrial/aerial laser scanning or other traditional measurement techniques. The stereo photogrammetry necessitates greater effort to obtain a three-dimensional (3D) model of the imaged surface. Meanwhile, terrestrial or aerial laser scanning can collect high-density measurements of spatial data in a short time. However, the costs of implementing laser scanning instruments are very high. Furthermore, conventional measurement techniques that use total stations require immense effort to collect complete 3D measurements of cliffs. On the other hand, dense image based point cloud using multi-view photogrammetry based on structure from motion (SfM) algorithm is much more effective than the others for measuring the Earth topography. In this study, the cliff topography of an old quarry located in the state of Selcuklu of Konya Province in Turkey was measured by multi-view photogrammetry. The cliff has a continuous length of approximately 600 metres and a height of 25 metres in some places. The 3D model of the cliff was generated with the image based dense point cloud of multi-view photogrammetry. Then 3D dense point cloud model was registered into a local georeference system by using control points (CPs). Because of the long line measurement area, number and localization of the CPs is very important for achieving a high-accuracy to registration into georeferenced system. The registration accuracies were evaluated for different number and distribution of the CPs with the residuals on the check points (ChPs). The high accuracy registration was acquired with uniform distributed 3 and 8 CPs as the residuals of 24.08&amp;thinsp;cm and 23.03&amp;thinsp;cm on the ChPs respectively. The results indicated that 3D measurement of long line cliffs can be performed using multi-view photogrammetry, and the registration should be made with the uniform distributed CPs. In addition, a texture-mapped 3D model and orthophoto images of the cliff surfaces were created for detailed visualization.</p>

scholarly journals PHOTOGRAMMETRIC 3D RECONSTRUCTION IN MATLAB: DEVELOPMENT OF A FREE TOOL

2017 ◽  
Vol XLII-2/W8 ◽  
pp. 141-145 ◽  
Author(s):  
A. Masiero
Keyword(s):  
3D Reconstruction ◽  
Structure From Motion ◽  
Point Cloud ◽  
Feature Matching ◽  
Computational Burden ◽  
Matching Process ◽  
Current State ◽  
Dense Point ◽  
The University

This paper presents the current state of development of a free Matlab tool for photogrammetric reconstruction developed at the University of Padova, Italy. The goal of this software is mostly educational, i.e. allowing students to have a close look to the specific steps which lead to the computation of a dense point cloud. As most of recently developed photogrammetric softwares, it is based on a Structure from Motion approach. Despite being mainly motivated by educational purposes, certain implementation details are clearly inspired by recent research works, e.g. limiting the computational burden of the feature matching by determining a suboptimal set of features to be considered, using information provided by external sensors to ease the matching process.

scholarly journals Evaluating the Structure from Motion Technique for Measurement of Bed Morphology in Physical Model Studies

Water ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 998
Author(s):  
Sanat Kumar Karmacharya ◽  
Nils Ruther ◽  
Ujjwal Shrestha ◽  
Meg Bahadur Bishwakarma
Keyword(s):  
Physical Model ◽  
Structure From Motion ◽  
Point Cloud ◽  
Three Dimensional ◽  
Time Frame ◽  
Model Studies ◽  
Model Study ◽  
Skilled Personnel ◽  
Dense Point ◽  
Point Data

The selection of instrumentation for data acquisition in physical model studies depends on type and resolution of data to be recorded, time frame of the model study, available instrumentation alternatives, availability of skilled personnel and overall budget of the model study. The available instrumentation for recording bed levels or three-dimensional information on geometry of a physical model range from simple manual gauges to sophisticated laser or acoustic sensors. In this study, Structure from Motion (SfM) technique was applied, on three physical model studies of different scales and study objectives, as a cheap, quicker, easy to use and satisfactorily precise alternative for recording 3D point data in form of colour coded dense point cloud representing the model geometry especially the river bed levels in the model. The accuracy of 3D point cloud generated with SfM technique were also assessed by comparing with data obtained from manual measurement using conventional surveying technique in the models and the results were found to be very promising.

Data post processing

2018 ◽  
Author(s):  
Serge A. Wich ◽  
Lian Pin Koh
Keyword(s):  
Land Cover ◽  
Structure From Motion ◽  
Land Cover Classification ◽  
Post Processing ◽  
Surface Models

This chapter discusses how data that have been collected with drones can be used to derive orthomosaics and digital surface models through structure-from-motion software and how these can be processed further for land-cover classification or into vegetation metrics. Some examples of the various programs are provided as well. The chapter ends with a discussion on the approaches that have been used to automate counts of animals in drone images.

scholarly journals Influence of Agisoft Metashape Parameters on UAS Structure from Motion Individual Tree Detection from Canopy Height Models

Forests ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 250
Author(s):  
Wade T. Tinkham ◽  
Neal C. Swayze
Keyword(s):  
Structure From Motion ◽  
Ponderosa Pine ◽  
Point Cloud ◽  
Image Resolution ◽  
Canopy Height ◽  
Computer Hardware ◽  
Forest Monitoring ◽  
Individual Tree ◽  
Ponderosa Pine Forests ◽  
Tree Detection

Applications of unmanned aerial systems for forest monitoring are increasing and drive a need to understand how image processing workflows impact end-user products’ accuracy from tree detection methods. Increasing image overlap and making acquisitions at lower altitudes improve how structure from motion point clouds represents forest canopies. However, only limited testing has evaluated how image resolution and point cloud filtering impact the detection of individual tree locations and heights. We evaluate how Agisoft Metashape’s build dense cloud Quality (image resolution) and depth map filter settings influence tree detection from canopy height models in ponderosa pine forests. Finer resolution imagery with minimal filtering provided the best visual representation of vegetation detail for trees of all sizes. These same settings maximized tree detection F-score at >0.72 for overstory (>7 m tall) and >0.60 for understory trees. Additionally, overstory tree height bias and precision improve as image resolution becomes finer. Overstory and understory tree detection in open-canopy conifer systems might be optimized using the finest resolution imagery that computer hardware enables, while applying minimal point cloud filtering. The extended processing time and data storage demands of high-resolution imagery must be balanced against small reductions in tree detection performance when down-scaling image resolution to allow the processing of greater data extents.

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