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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Thaw Slump Activity Via Close-range ‘Structure from Motion’ in Time-lapse Using Ground-based Autonomous Cameras

Armstrong, Lindsay Faye January 2017 (has links)
Northwestern Arctic Canada is one of the most rapidly warming regions in the Arctic (Serreze et al., 2009). Retrogressive thaw slumps (RTS) are one of the most dramatic thermokarst features in permafrost terrain (Kokelj et al., 2013). Many studies have focused on describing the distribution of thermokarst landscapes (i.e., Olefeldt et al., 2016), as well as change in thermokarst terrain over the historical record (i.e., Kokelj and Jorgenson, 2013). However, improved high temporal and spatial resolution monitoring of thaw slump activity is required to enhance our understanding of factors governing their growth. Recent advances in aerial and ground-based Structure from Motion (SfM), a photogrammetry application, allow for temporal and spatial high-resolution characterization of landscape changes. This thesis explores two methods in SfM photogrammetry: 1) aerial imaging using an unmanned aerial vehicle (UAV) and 2) ground-based imaging using stationary multi-camera time-lapse installations, to derive high-resolution temporal and spatial data for change detection. A trend in mean elevation change was produced, and agrees with the RTS behaviour over the study period, which supports the viability of the proposed capture method. The lack of congruency in data range suggests need for further development in terms of analyses and differencing algorithms employed. The proposed method may be feasible for employment in other fields of science in which high temporal resolution change detection is desired. This proof of concept study was conducted at a small slump on the Peel Plateau, NWT, Canada, and aims to enhance understanding of the development and perpetuation of thaw slumps, to better anticipate landscape and ecosystem responses to future climate change.
2

Visualization and Interaction with 3D Data

Trollsfjord, Dennis January 2023 (has links)
This paper presents Triangle-To-Cloud (T2C), a new approach for point cloud change detection. The method is compared to the established method Multiscale Model to Model Cloud Comparison (M3C2) on the accuracy to detect changes, from a point cloud to another. The comparison is performed on Light Detection and Ranging (LiDAR) mappings from an Ouster OS0-128 LiDAR sensor. Both T2C and M3C2 are tested with different parameters in all of the experiments conducted for evaluation. This work demonstrates in the experiments that T2C can outperform M3C2 in its ability to detect changes.
3

Jämförelse av punktmoln genererade med terrester laserskanner och drönar-baserad Structure-from-Motion fotogrammetri : En studie om osäkerhet och kvalitet vid detaljmätning och 3D-modellering / Comparison of Point Clouds Generated by Terrestrial Laser Scanning and Structure-from-Motion Photogrammetry with UAVs : A study on uncertainty and quality in detailed measurement and 3D modeling

Nyberg, Emil, Wolski, Alexander January 2024 (has links)
Fotogrammetri är en viktig metod för att skapa 3D-representationer av terräng och strukturer, men utmaningar kvarstår när det gäller noggrannheten på grund av faktorer som bildkvalitet, kamerakalibrering och positionsdata. Användningen av drönare för byggnadsdetaljmätning möjliggör snabb och kostnadseffektiv datainsamling, men noggrannheten kan påverkas av bildkvalitet och skuggning. Avhandlingen syftar till att jämföra noggrannheten och kvaliteten hos punktmoln genererade med två olika tekniker: terrester laserskanning (TLS) och struktur-från-rörelse (SfM) fotogrammetri med drönare. För att testa båda metodernas osäkerhet och noggrannhet vid detaljmätning av bostäder. Genom att utföra mätningar på en villa har data samlats in med både TLS och drönare utrustade med 48 MP kamera, samt georeferering med markstöd (GCP). SfM-punktmoln bearbetades med Agisoft Metashape. Jämförelser gjordes mellan SfM- och TLS-punktmoln avseende täckning, lägesskillnad och lägesosäkerhet. Genom att följa riktlinjer från HMK - Terrester Laserskanning och tillämpa HMK Standardnivå 3 säkerställs hög noggrannhet i mätningarna. Kontroll av lägesosäkerhet av båda punktmolnen resulterade i en lägesosäkerhet som understeg toleranser satta enligt HMK - Terrester laserskanner Standardnivå 3.  Kontrollen av lägesosäkerheten visade att kvadratiska medelfelet(RMSE) i plan och höjd var 0.011m respektive 0.007m för TLS-punktmolnet, och 0.02m respektive 0.015m för drönar-SfM-punktmolnet, vilket låg under toleransen enligt HMK- Terrester Detaljmätning 2021. Resultaten tyder på att Structure-from-Motion fotogrammetri med drönare kan generera punktmoln med god detaljrikedom, inte lika noggrann som med terrester laserskanner på sin lägsta inställning. TLS uppvisade mindre osäkerhet enligt kontrollen av lägesosäkerhet, ungefär en halvering av RMSE i både plan och höjd. I studien framgick det att TLS presterar sämre vid svåråtkomliga ytor med skymd sikt och ogynnsamma infallsvinklar, där effekten blir en lägre punkttäthet för punktmolnet. Vid gynnsamma förhållanden erbjuder TLS en högre noggrannhet och detaljnivå jämfört med SfM punktmoln. Enligt M3C2 punktmoln analys, med TLS punktmolnet som referens, antydde det att SfM punktmolnet genererade största felen vid takfot samt vid buskage. De större felen vid takfot tyder på att SfM presterar sämre gällande detaljnivå och fel vid buskageområdet varierar inte från det som dokumenterats om fotogrammetriska fel vid mappning av vegetation. SfM kan utföra en effektiv datainsamling för större samt svåråtkomliga ytor men kräver lång bearbetningstid med diverse hjälpmedel för att uppnå hög noggrannhet. TLS kräver istället en lång datainsamlingsprocess men kan generera ett detaljerat och noggrant punktmoln direkt utan långa bearbetningsprocesser. Val av metod styrs därmed baserat på specifika projektkrav. Långsiktiga implikationer inkluderar förbättrad effektivitet och säkerhet inom bygg- och anläggningsprojekt, samt potentialen för kostnadsbesparingar och mer detaljerade inspektioner. / Photogrammetry is a crucial method for creating 3D representations of terrain and structures, yet challenges remain regarding accuracy due to factors such as image quality, camera calibration, and positional data. The use of drones for building detail measurements enables rapid and cost-effective data collection, but accuracy can be affected by image quality and shading. This thesis aims to compare the accuracy and quality of point clouds generated using two different techniques: terrestrial laser scanning (TLS) and Structure-from-Motion (SfM) photogrammetry with drones. The objective is to test the uncertainty and accuracy of both methods in residential surveying. Data collection was performed on a villa using both TLS and a drone equipped with a 48 MP camera, along with georeferencing with ground control points (GCP). SfM point clouds were processed with Agisoft Metashape. Comparisons were made between SfM and TLS point clouds in terms of coverage, positional difference, and positional uncertainty. By following guidelines from HMK - Terrester laserskanning 2021 and applying HMK Standard Level 3, high measurement accuracy was ensured. Positional uncertainty checks of both point clouds resulted in positional uncertainty within tolerances set by HMK - Terrestrial Laser Scanning Standard Level 3. The positional uncertainty, with a sample of 41 points showed that the root mean square error (RMSE) in plane and height was 0.011m and 0.007m respectively for the TLS point cloud, and 0.02m and 0.015m for the drone-SfM point cloud, both within the tolerance according to HMK - Terrestrial Detail Measurement 2021. The results suggest that Structure-from-Motion photogrammetry with drones can generate point clouds with good detail, although not as accurate as terrestrial laser scanning at its lowest setting. TLS showed less uncertainty according to the positional uncertainty check, with approximately half the RMSE in both plan and height. The study found that TLS performs worse on difficult-to-access surfaces with obstructed views and unfavorable angles, resulting in lower point cloud density. Under favorable conditions, TLS offers higher accuracy and detail compared to SfM point clouds. According to M3C2 point cloud analysis, using the TLS point cloud as a reference, SfM point clouds showed the largest errors at eaves and shrubbery. The larger errors at eaves indicate that SfM performs worse in terms of detail level, and errors in the shrubbery area are consistent with documented photogrammetric errors in vegetation mapping. SfM can effectively collect data for larger and difficult-to-access areas but requires extensive processing time with various aids to achieve high accuracy. Conversely, TLS requires a long data collection process but can generate a detailed and accurate point cloud directly without lengthy processing. The choice of method thus depends on specific project requirements. Long-term implications include improved efficiency and safety in construction and infrastructure projects, as well as potential cost savings and more detailed inspections.

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