OPUS: Open Ulethbridge Scholarship
Open ULeth Scholarship (OPUS) is the University of Lethbridge's open access research repository. It contains a collection of materials related to research and teaching produced by the academic community.
Self-archiving your research in OPUS is one way to meet Open Access policies of granting agencies. It is important to retain your final, post-peer-reviewed drafts for submission to OPUS, as this is often the only version publishers will allow to be archived. Click here for information on the U of L Open Access Policy.
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Uzbek music in Western style: the influence of folk traditions in the piano works of Georgi Mushel
(Lethbridge, Alta. : University of Lethbridge, Dept. of Music, 2025) Merzaeva, Bakhora; University of Lethbridge. Faculty of Arts and Science; Parker, Bradley
This project focuses on Uzbek folk music elements in Soviet composer Georgi Mushel’s piano compositions. Through a detailed analysis of a selection of Mushel’s piano compositions, I have developed an informed interpretation of the folk elements in these works.
By working closely with native musicians and ethnomusicologists, Mushel absorbed the national music of the region. As Vaughan Williams wrote: “The great masters of music have never hesitated to build on folk-song material when they wished to” (1934, 80). Though Mushel was born in Russia and had French ancestry, he lived the majority of his life in Uzbekistan and tied himself up with Uzbek culture. He was influenced by the music of the region and felt its beauty which is expressed in his works.
Uzbek folk and traditional music is a vibrant reflection of the country’s diverse cultural history. It is characterized by modal scales, rhythmic cycles, and melodic ornamentation often performed with traditional instruments like the dutar, rubab, ghijak, doira, and nay. I found evidence of these musical elements and imitation of dutar and doira timbre in Mushel’s three piano compositions.
In this study, I explored whether the original Uzbek folk songs used by Georgi Mushel in his piano compositions are accessible today through scores or recordings. I also examined the specific musical elements from Uzbek folk traditions that Mushel incorporated into his works. Finally, I investigated how the stylistic nuances of Uzbek music mentioned above can be interpreted and expressed effectively on the piano.
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The role of online communities for Canadian immigrants: knowledge and support systems provided by Reddit
(Lethbridge, Alta. : University of Lethbridge, Dhillon School of Business, 2025) Koshuta, Makayla R.; University of Lethbridge. Dhillon School of Business; Basil, Debra Z.
This research study examined how Canadian newcomers seek and share settlement information on Reddit. Applying a transformative consumer research (TCR) lens, the research study explores motivational factors behind information sharing on social media within the context of the Canadian immigrant community on Reddit. The key hypothesized factors for immigrants’ motivations to share information regarding the Canadian immigrant settlement process on Reddit include empathy, sense of community, and advocacy and activism. The study analyzed 10 Reddit discussion threads obtained through data scraping, with a total of 691 comments after data cleaning, using qualitative content analysis as well as some quantitative analyses for hypothesis testing. The results of the study revealed a significant expression of shared experience and advocacy and activism within the Reddit conversations, as well as a small positive correlation and statistically significant relationship between empathy and shared experience. The findings also revealed that many immigrants tend to seek informal information and supports from Reddit, rather than through formal settlement support organizations such as government and non-profit organizations. Overall, this research study provides a better understanding of how settlement information is sought and shared by existing and prospective Canadian immigrants through Reddit discussion forums. These findings can benefit those engaged in transformative service research and social marketing efforts to facilitate immigrant settlement in Canada.
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The hip-hop and mental health handbook for mental health practicioners
(Lethbridge, Alta. : University of Lethbridge, Faculty of Education, 2025) Volk, Hunter J.; University of Lethbridge. Faculty of Education; Gunn, Thelma
Hip-hop culture is a dynamic, multifaceted movement with profound relevance to mental health practices, albeit one that few professionals have experience with. Practitioners can develop more creative, culturally responsive, and trauma-informed approaches by understanding hip-hop culture and realizing how it can be used to improve mental health. This project articulates a literature review of several critical areas including a brief history of hip-hop culture, hip-hop through a Canadian lens, and the application of hip-hop in mental health practices. Additionally, this project includes a handbook that translates findings from the literature review into an accessible, interdisciplinary resource for professionals seeking to better understand hip-hop culture and potentially incorporate it into their practice. By increasing visibility and facilitating a better understanding of the relationship between hip-hop culture and mental health, this project aims to improve professionals’ engagement with hip-hop as a therapeutic tool in working with diverse, relevant populations.
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Benchmarking tree species classification from proximally sensed laser scanning data: introducing the FOR-species20K dataset
(Wiley, 2025) Pulti, Stefano; Lines, Emily R.; Mullerova, Jana; Frey, Julian; Schindler, Zoe; Straker, Adrian; Allen, Matthew J.; Winiwarter, Lukas; Rehush, Nataliia; Hristova, Hristina; Murray, Brent; Calders, Kim; Coops, Nicholas; Hofle, Bernhard; Irwin, Liam; Junttila, Samuli; Krucek, Martin; Krok, Grzegorz; Kral, Kamil; Levick, Shaun R.; Luck, Linda; Missarov, Azim; Mokros, Martin; Owen, Harry J. F.; Sterenczak, Krzysztof; Pitkanen, Timo P.; Puletti, Nicola; Saarinen, Ninni; Hopkinson, Christopher; Terryn, Louise; Torresan, Chiara; Tomelleri, Enrico; Weiser, Hannah; Astrup, Rasmus
1. Proximally sensed laser scanning presents new opportunities for automated forest ecosystem data capture. However, a gap remains in deriving ecologically pertinent information, such as tree species, without additional ground data. Artificial intelligence approaches, particularly deep learning (DL), have shown promise towards automation. Progress has been limited by the lack of large, diverse, and, most importantly, openly available labelled single-tree point cloud datasets. This has hindered both (1) the robustness of the DL models across varying data types (platforms and sensors) and (2) the ability to effectively track progress, thereby slowing the convergence towards best practice for species classification.
2. To address the above limitations, we compiled the FOR-species20K benchmark dataset, consisting of individual tree point clouds captured using proximally sensed laser scanning data from terrestrial (TLS), mobile (MLS) and drone laser scanning (ULS). Compiled collaboratively, the dataset includes data collected in forests mainly across Europe, covering Mediterranean, temperate and boreal biogeographic regions. It includes scattered tree data from other continents, totaling over 20,000 trees of 33 species and covering a wide range of tree sizes and forms. Alongside the release of FOR-species20K, we benchmarked seven leading DL models for individual tree species classification, including both point cloud (PointNet++, MinkNet, MLP-Mixer, DGCNNs) and multi-view 2D-based methods (SimpleView, DetailView, YOLOv5).
3. 2D Image-based models had, on average, higher overall accuracy (0.77) than 3D point cloud-based models (0.72). Notably, the performance was consistently >0.8 across scanning platforms and sensors, offering versatility in deployment. The top-scoring model, DetailView, demonstrated robustness to training data imbalances and effectively generalized across tree sizes.
4. The FOR-species20K dataset represents an important asset for developing and benchmarking DL models for individual tree species classification using proximally sensed laser scanning data. As such, it serves as a crucial foundation for future efforts to classify accurately and map tree species at various scales using laser scanning technology, as it provides the complete code base, dataset, and an initial baseline representative of the current state-of-the-art of point cloud tree species classification methods.
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Applying remote sensing for large-landscape problems: inventorying and tracking habitat recovery for a broadly distributed Species At Risk
(Wiley, 2023) Dickie, Melanie; Hricko, Branislav; Hopkinson, Christopher; Tran, Victor; Kohler, Monica; Toni, Sydney; Serrouya, Robert; Kariyeva, Johan
1. Anthropogenic habitat alteration is leading to the reduction of global biodiversity. Consequently, there is an imminent need to understand the state and trend of habitat alteration across broad areas. In North America, habitat alteration has been linked to the decline of threatened woodland caribou. As such, habitat protection and restoration are critical measures to support recovery of self-sustaining caribou populations. Broad estimates of habitat change through time have set the stage for understanding the status of caribou habitat. However, the lack of updated and detailed data on post-disturbance vegetation recovery is an impediment to recovery planning and monitoring restoration effectiveness. Advances in remote sensing tools to collect high-resolution data at large spatial scales are beginning to enable ecological studies in new ways to support ecosystem-based and species-based management.
2. We used semi-automated and manual methodologies to fuse photogrammetry point clouds (PPC) from high-resolution aerial imagery with wide-area light detection and ranging (LiDAR) data to quantify vegetation structure (height, density, class) on disturbances associated with caribou declines. We also compared vegetation heights estimated from the semi-automated PPC-LiDAR fusion to heights estimated in the field, using stereoscopic interpretation, and using multi-channel TiTAN LiDAR.
3. Vegetation regrowth was occurring on many of the disturbance types, though there was local variability in the type, height and density of vegetation. Heights estimated using PPC-LiDAR fusion were highly correlated (r ≥ 0.87 in all cases) with heights estimated using stereomodels, TiTAN multi-channel LiDAR and field measurements.
4. We demonstrated that PPC-LiDAR fusion can be operationalized over large areas to collect comprehensive and consistent vegetation data across landscape levels, providing opportunities to link fine-resolution remote sensing to landscape-scale ecological studies. Crucially, these data can be used to estimate rates of habitat recovery at resolutions that are not feasible using more commonly used satellite-based sensors, bridging the gap between resolution and extent. Such data are needed to achieve effective and efficient habitat monitoring to support caribou recovery efforts, as well as a myriad of additional forest management needs.