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

Author(s):  
Helge Smebye

<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>

UKaRsT ◽  
2021 ◽  
Vol 5 (1) ◽  
pp. 49
Author(s):  
Dian Wahyu Khaulan ◽  
Entin Hidayah ◽  
Gusfan Halik

The Digital Surface Model (DSM) is commonly used in studies on flood map modeling. The lack of accurate, high-resolution topography data has hindered flood modeling. The use of the Unmanned Aerial Vehicle (UAV) can help data acquisition with sufficient accuracy. This research aims to provide high-resolution DSM-generated maps by Ground Control Points (GCPs) settings. Improvement of the model's accuracy was pursued by distributing 20 GCPs along the edges of the study area. Agrisoft software was used to generate the DSM. The generated DSM can be used for various planning purposes. The model's accuracy is measured in Root Mean Square Error (RMSE) based on the generated DSM. The RMSE values are 0.488 m for x-coordinates and y-coordinates (horizontal direction) and 0.161 m for z-coordinates (vertical direction).


2020 ◽  
Author(s):  
Sean Salazar ◽  
Helge Smebye ◽  
Regula Frauenfelder ◽  
Frank Miller ◽  
Emil Solbakken ◽  
...  

<p>The availability of consumer remotely piloted aircraft systems (RPAS) has enabled rapidly deployable airborne surveys for civilian applications. Combined with photogrammetric reconstruction techniques, such as Structure-from-Motion (SfM), it has become increasingly feasible to survey large areas with very high resolution, especially when compared with other airborne or spaceborne surveying techniques. A pair of case studies, using an RPAS-based field surveying technique for establishing baseline surface models in steep terrain, are presented for two different natural hazard applications.</p><p>The first case study involved a survey over the entire 1000-m length of a snow-free avalanche path on Sætreskarsfjellet in Stryn municipality in Norway. A terrain-aware, multi-battery flight plan was designed to ensure good photographic coverage over the entire avalanche path and 21 ground control points (GCP) were distributed evenly across the path and subsequently surveyed. More than 400 images were collected over a 0.5 km<sup>2</sup> area, which were processed using a commercial SfM software package. Two digital surface models were reconstructed, each utilizing a different ground control scenario: the first one with the full count of GCP, while the second used only a limited count of GCP, which is more feasible for a repeat survey when avalanche hazard is high. Comparison with data from a pre-existing, airborne LiDAR survey over the avalanche path revealed that the SfM-derived model that utilized only a limited number of GCP diverged significantly from the model that utilized all available GCP. Further differences between the SfM- and LiDAR-derived surface models were observed in areas with very steep slopes and vegetative cover. The same methodology can subsequently be applied during the winter season, after extensive snowfall and/or avalanche events, to deduce relevant avalanche parameters such as snow height, snow distribution and drift, opening of cracks in the snow surface (e.g. for glide avalanches), and avalanche outlines.</p><p>The second case study involved a survey over the entire 1000-m length of a debris flow path at Årnes in Jølster, Norway. The Årnes flow, which caused one fatality, was one of the largest of several tens of debris flows that occurred on July 30, 2019. The flows were triggered by an extreme precipitation event around the Jølstravatnet area. Like with the Sætreskarsfjellet avalanche path case study, a terrain-aware flight plan was established and 24 GCP were distributed and surveyed along the debris flow path. Over 400 images were collected over a 0.3 km<sup>2</sup> area, which were used to reconstruct a high-resolution surface model. Like with the avalanche case study, the SfM-derived model was compared with a pre-existing LiDAR survey-derived digital terrain model. Altitude and volume changes, due to the debris flow event, were calculated using GIS analysis tools.</p><p>The utility of the RPAS survey technique was demonstrated in both case studies, despite difficult accessibility for ground control. It is suggested that a real-time-kinematic (RTK)-enabled workflow may significantly reduce survey time and increase personnel safety by minimizing the number of required GCP.</p><p><strong>Keywords</strong>: Structure-from-Motion, photogrammetry, digital surface model, natural hazards, ground control.</p>


Drones ◽  
2022 ◽  
Vol 6 (1) ◽  
pp. 24
Author(s):  
Taleatha Pell ◽  
Joan Y. Q. Li ◽  
Karen E. Joyce

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.


2018 ◽  
Vol 2 ◽  
pp. 535
Author(s):  
Maundri Prihanggo

<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>


Author(s):  
J. Fagir ◽  
A. Schubert ◽  
M. Frioud ◽  
D. Henke

The fusion of synthetic aperture radar (SAR) and optical data is a dynamic research area, but image segmentation is rarely treated. While a few studies use low-resolution nadir-view optical images, we approached the segmentation of SAR and optical images acquired from the same airborne platform – leading to an oblique view with high resolution and thus increased complexity. To overcome the geometric differences, we generated a digital surface model (DSM) from adjacent optical images and used it to project both the DSM and SAR data into the optical camera frame, followed by segmentation with each channel. The fused segmentation algorithm was found to out-perform the single-channel version.


Author(s):  
K. M. Kim

Traditional field methods for measuring tree heights are often too costly and time consuming. An alternative remote sensing approach is to measure tree heights from digital stereo photographs which is more practical for forest managers and less expensive than LiDAR or synthetic aperture radar. This work proposes an estimation of stand height and forest volume(m<sup>3</sup>/ha) using normalized digital surface model (nDSM) from high resolution stereo photography (25cm resolution) and forest type map. The study area was located in Mt. Maehwa model forest in Hong Chun-Gun, South Korea. The forest type map has four attributes such as major species, age class, DBH class and crown density class by stand. Overlapping aerial photos were taken in September 2013 and digital surface model (DSM) was created by photogrammetric methods(aerial triangulation, digital image matching). Then, digital terrain model (DTM) was created by filtering DSM and subtracted DTM from DSM pixel by pixel, resulting in nDSM which represents object heights (buildings, trees, etc.). Two independent variables from nDSM were used to estimate forest stand volume: crown density (%) and stand height (m). First, crown density was calculated using canopy segmentation method considering live crown ratio. Next, stand height was produced by averaging individual tree heights in a stand using Esri’s ArcGIS and the USDA Forest Service’s FUSION software. Finally, stand volume was estimated and mapped using aerial photo stand volume equations by species which have two independent variables, crown density and stand height. South Korea has a historical imagery archive which can show forest change in 40 years of successful forest rehabilitation. For a future study, forest volume change map (1970s&ndash;present) will be produced using this stand volume estimation method and a historical imagery archive.


2017 ◽  
Author(s):  
Brian M. Webb ◽  
◽  
Jason D. McClaughry ◽  
Robert Hairston-Porter ◽  
Ian P. Madin

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