STRUCTURE-FROM-MOTION PHOTOGRAMMETRY TECHNIQUES AND DIGITAL SURFACE MODEL CREATION FOR GEOSCIENCE APPLICATIONS

2017 ◽  
Author(s):  
Brian M. Webb ◽  
◽  
Jason D. McClaughry ◽  
Robert Hairston-Porter ◽  
Ian P. Madin
Keyword(s):  
Structure From Motion ◽  
Surface Model ◽  
Digital Surface Model

Combined aerial and ground-based Structure-from-Motion modelling for a vertical rock wall face to estimate volume of failure

2020 ◽  
Author(s):  
Helge Smebye
Keyword(s):  
High Resolution ◽  
Structure From Motion ◽  
Software Package ◽  
Standoff Distance ◽  
Ground Control ◽  
Surface Model ◽  
Digital Surface Model ◽  
Failure Model ◽  
Volume Estimate ◽  
Rock Wall

<p>Combined aerial and ground-based Structure-from-Motion modelling for a vertical rock wall face to estimate volume of failure</p><p> </p><p>Helge C. Smebye,<sup>a,* </sup>Sean E. Salazar,<sup>a</sup> Asgeir O. K. Lysdahl,<sup>a</sup></p><p>aNorwegian Geotechnical Institute, Sognsveien 72, 0855 Oslo, Norway</p><p> </p><p><strong>Abstract</strong>.  The A rock wall failure occurred along a major highway in south-eastern Norway, shutting down two lanes of traffic for an extended period of time while the road authority inspected and repaired the wall. It was desired to have a high-resolution digital surface model along a 215-m long section of the 34-m tall vertical rock wall that included the failure zone.</p><p>A Structure-from-Motion (SfM)-based methodology was selected to achieve the desired resolution on the rock wall face, as well as below the foot and above the head of the wall. Due to the proximity of the wall face to the remaining open lanes of traffic, it was not possible to survey the face of the wall using a remotely piloted aircraft system (RPAS). Therefore, a combined platform photogrammetric surveying technique was employed to ensure optimal photographic coverage and to generate the best possible model. Ground control points (GCP) were distributed and surveyed along the bottom and top of the wall and an RPAS was flown manually over the head of the wall to capture downward facing (nadir) images. A lift crane was also employed to capture images from elevations varying between 20–30 meters with a standoff distance of 15 meters from the wall. Finally, ground-based images were captured using a camera equipped with real-time GNSS from the top of the opposite rock wall (across the highway) with standoff distance of approximately 65 meters.</p><p>In total, over 800 images were ingested into a commercial SfM software package. The bundle adjustments were assisted by the GNSS-equipped camera locations and the surveyed GCP were imported to georeference the resulting model. The dense point cloud product was exported to a separate meshing software package for comparison with a second dense surface model that was derived from pre-existing images of the as-built condition of same rock wall face (prior to failure). By subtracting the post-failure model from the pre-failure model, a volume estimate of the material, that was mobilized during the failure, was determined.</p><p>The utility of the multi-platform survey technique was demonstrated. The combination of aerial and ground-based photographic surveying techniques provided optimal photographic coverage of the entire length of the rock wall to successfully derive high-resolution surface models and volume estimates.</p><p> </p><p><strong> </strong></p><p><strong>Keywords</strong>: Structure-from-Motion, photogrammetry, digital surface model, natural hazards, ground control.</p><p> </p><p><strong>*</strong>Helge C. Smebye, E-mail: [email protected]</p>

scholarly journals Accuracy Assessment of Post-processing Kinematic Georeferencing Based on Real-time Kinematic Unmanned Aerial Vehicle and Structure-from-motion Photogrammetry: Topographic Measurements of a Riverbed in a Small Watershed with a Check Dam

2021 ◽  
Author(s):  
Masato Hayamizu ◽  
Yasutaka Nakata
Keyword(s):  
Structure From Motion ◽  
Working Time ◽  
Surface Model ◽  
Digital Surface Model ◽  
Check Dam ◽  
Post Processing ◽  
Small Watershed ◽  
Total Station ◽  
Vertical Error ◽  
Aerial Vehicle

<p><a>To obtain an accurate digital surface model of the small watershed topography of a forested area while reducing time and labor costs, we used a consumer-grade unmanned aerial vehicle (UAV) with a build-in real-time kinematic global navigation satellite system. The applicability of structure-from-motion (SfM) multi-view stereo processing with post-processing kinematic (PPK) correction of the positional coordinate data (the UAV-PPK-SfM method) was tested. Nine verification points were set up in a small (0.5 km<sup>2</sup>) watershed, based on a check dam in the headwaters of a forest area. The location information of the verification points extracted from the digital surface model acquired by UAV-PPK-SfM and the overall working time were compared with the corresponding location information and working time of a traditional field survey using a total station. The results showed that the vertical error between the total station and each verification point at an altitude of 150 m ranged from 0.006 to 0.181 m. The working time of the UAV-PK-SfM survey was 10 % of that of the total station survey (30 min). The UAV-PPK-SfM workflow proposed in this study shows that wide-area, non-destructive topographic surveying, including fluvial geomorphological mapping, is possible with a vertical error of ±0.2 m in small watersheds (<0.5 km<sup>2</sup>). This method will be useful for rapid topographic surveying in inaccessible areas during disasters, such as monitoring debris flow at check dam sites, and for efficient topographic mapping of steep valleys in forested areas where the positioning of ground control points is a laborious task.</a></p>

scholarly journals Demystifying the Differences between Structure-from-Motion Software Packages for Pre-Processing Drone Data

Drones ◽  
2022 ◽  
Vol 6 (1) ◽  
pp. 24
Author(s):  
Taleatha Pell ◽  
Joan Y. Q. Li ◽  
Karen E. Joyce
Keyword(s):  
Structure From Motion ◽  
Software Package ◽  
Low Cost ◽  
Surface Model ◽  
Digital Surface Model ◽  
Output File ◽  
Environmental Assessments ◽  
Processing Times ◽  
Software Packages ◽  
Digital Elevation

With the increased availability of low-cost, off-the-shelf drone platforms, drone data become easy to capture and are now a key component of environmental assessments and monitoring. Once the data are collected, there are many structure-from-motion (SfM) photogrammetry software options available to pre-process the data into digital elevation models (DEMs) and orthomosaics for further environmental analysis. However, not all software packages are created equal, nor are their outputs. Here, we evaluated the workflows and output products of four desktop SfM packages (AgiSoft Metashape, Correlator3D, Pix4Dmapper, WebODM), across five input datasets representing various ecosystems. We considered the processing times, output file characteristics, colour representation of orthomosaics, geographic shift, visual artefacts, and digital surface model (DSM) elevation values. No single software package was determined the “winner” across all metrics, but we hope our results help others demystify the differences between the options, allowing users to make an informed decision about which software and parameters to select for their specific application. Our comparisons highlight some of the challenges that may arise when comparing datasets that have been processed using different parameters and different software packages, thus demonstrating a need to provide metadata associated with processing workflows.

scholarly journals Accuracy Assessment of Post-processing Kinematic Georeferencing Based on Real-time Kinematic Unmanned Aerial Vehicle and Structure-from-motion Photogrammetry: Topographic Measurements of a Riverbed in a Small Watershed with a Check Dam

2021 ◽  
Author(s):  
Masato Hayamizu ◽  
Yasutaka Nakata
Keyword(s):  
Structure From Motion ◽  
Working Time ◽  
Surface Model ◽  
Digital Surface Model ◽  
Check Dam ◽  
Post Processing ◽  
Small Watershed ◽  
Total Station ◽  
Vertical Error ◽  
Aerial Vehicle

<p><a>To obtain an accurate digital surface model of the small watershed topography of a forested area while reducing time and labor costs, we used a consumer-grade unmanned aerial vehicle (UAV) with a build-in real-time kinematic global navigation satellite system. The applicability of structure-from-motion (SfM) multi-view stereo processing with post-processing kinematic (PPK) correction of the positional coordinate data (the UAV-PPK-SfM method) was tested. Nine verification points were set up in a small (0.5 km<sup>2</sup>) watershed, based on a check dam in the headwaters of a forest area. The location information of the verification points extracted from the digital surface model acquired by UAV-PPK-SfM and the overall working time were compared with the corresponding location information and working time of a traditional field survey using a total station. The results showed that the vertical error between the total station and each verification point at an altitude of 150 m ranged from 0.006 to 0.181 m. The working time of the UAV-PK-SfM survey was 10 % of that of the total station survey (30 min). The UAV-PPK-SfM workflow proposed in this study shows that wide-area, non-destructive topographic surveying, including fluvial geomorphological mapping, is possible with a vertical error of ±0.2 m in small watersheds (<0.5 km<sup>2</sup>). This method will be useful for rapid topographic surveying in inaccessible areas during disasters, such as monitoring debris flow at check dam sites, and for efficient topographic mapping of steep valleys in forested areas where the positioning of ground control points is a laborious task.</a></p>

EVALUASI KETELITIAN HORIZONTAL DARI CITRA TEGAK SATELIT RESOLUSI SANGAT TINGGI MENGGUNAKAN SRTM DAN TERRASAR-X UNTUK PEMETAAN SKALA BESAR

2018 ◽  
Vol 2 ◽  
pp. 535
Author(s):  
Maundri Prihanggo
Keyword(s):  
Control Point ◽  
Ground Control ◽  
Surface Model ◽  
Digital Surface Model ◽  
Check Point ◽  
Ground Control Point

<p>Saat ini, citra satelit resolusi sangat tinggi digunakan dalam berbagai macam aplikasi, terutama pemetaan skala besar. Sebelum dapat digunakan, citra satelit tersebut harus diorthorektifikasi terlebih dahulu. Data <em>Digital Surface Model </em>(DSM) dan <em>Ground Control Point</em> (GCP) adalah dua data utama yang diperlukan saat melakukan orthorektifikasi. Perbedaan data DSM yang digunakan akan menghasilkan perbedaan nilai ketelitian horizontal pada kedua citra tegak hasil orthorektifikasi. Pada penelitian ini digunakan dua jenis DSM yaitu SRTM dan Terrasar-X. Ketelitian vertikal dari SRTM adalah 90 m sedangkan ketelitian vertikal dari Terrasar-X adalah 12,5 m. Penelitian ini berlokasi di Wilayah Buli, Kabupaten Halmahera Timur, Provinsi Maluku. Terdapat tiga sensor citra satelit yang digunakan yaitu Pleiades, Quickbird dan Worldview-2 yang digunakan pada lokasi penelitian. Total GCP yang digunakan adalah 33 titik, tiap titiknya diukur dengan melakukan pengamatan geodetik dan memiliki ketelitian horizontal ≤15 cm dan ketelitian vertikal ≤30 cm. Ketelitian horizontal dari citra tegak satelit resolusi sangat tinggi diperoleh dengan melakukan uji terhadap Independent Check Point (ICP). Total ICP yang digunakan adalah 12 titik, tiap titik ICP diukur dengan metode dan standar yang sama dengan titik GCP. Ketelitian horizontal dengan Circular Error (CE 90) dari citra tegak satelit menggunakan data SRTM adalah 18,856 m sedangkan ketelitian horizontal dengan Circular Error (CE 90) dari citra tegak satelit menggunakan data Terrasar-X adalah 2.168 m . Hasil dari penelitian ini membuktikan bahwa ketelitian vertikal data DSM yang digunakan memberikan pengaruh pada citra tegak satelit hasil orthorektifikasi tersebut. Mengacu pada Peraturan Kepala BIG nomor 15 tahun 2014, citra tegak satelit hasil orthorektifikasi menggunakan data Terrasar-X sebagai DSM memenuhi ketelitian horizontal peta dasar kelas 3 skala 1:5.000 sedangkan citra tegak satelit hasil orthorektifikasi menggunakan data SRTM sebagai DSM tidak dapat memenuhi ketelitian horizontal peta dasar skala besar.</p><p><strong>Kata kunci:</strong> orthorektifikasi, DSM, ketelitian horizontal</p>

Measuring historical flooding and erosion in Goodnews Bay using datasets commonly available to Alaska communities

Shore & Beach ◽  
2020 ◽  
pp. 3-13
Author(s):  
Richard Buzard ◽  
Christopher Maio ◽  
David Verbyla ◽  
Nicole Kinsman ◽  
Jacquelyn Overbeck
Keyword(s):  
Rural Communities ◽  
Coastal Communities ◽  
Aerial Imagery ◽  
Coastal Hazards ◽  
Surface Model ◽  
Digital Surface Model ◽  
Wave Impact ◽  
Information Gap ◽  
Quantitative Analyses ◽  
Gnss Measurements

Coastal hazards are of increasing concern to many of Alaska’s rural communities, yet quantitative assessments remain absent over much of the coast. To demonstrate how to fill this critical information gap, an erosion and flood analysis was conducted for Goodnews Bay using an assortment of datasets that are commonly available to Alaska coastal communities. Measurements made from orthorectified aerial imagery from 1957 to 2016 show the shoreline eroded 0 to 15.6 m at a rate that posed no immediate risk to current infrastructure. Storm surge flood risk was assessed using a combination of written accounts, photographs of storm impacts, GNSS measurements, hindcast weather models, and a digital surface model. Eight past storms caused minor to major flooding. Wave impact hour calculations showed that the record storm in 2011 doubled the typical annual wave impact hours. Areas at risk of erosion and flooding in Goodnews Bay were identified using publicly available datasets common to Alaska coastal communities; this work demonstrates that the data and tools exist to perform quantitative analyses of coastal hazards across Alaska.

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