Rock glacier catalogue and predictive modeling in the Mackenzie Mountains: predicting rock glacier likelihood with a generalized additive model

Simple item page
dc.contributor.authorThiessen, Rabecca R.
dc.contributor.authorUniversity of Lethbridge. Faculty of Arts and Science
dc.contributor.supervisorBonnaventure, Philip
dc.date.accessioned2024-02-01T18:03:29Z
dc.date.available2024-02-01T18:03:29Z
dc.date.issued2023
dc.degree.levelMasters
dc.description.abstractRock glaciers are important features of periglacial landscapes and have potentially significant hydrological, ecological, and geological impacts on alpine environments. The purpose of this study is to catalog rock glaciers in three regions of the Mackenzie Mountains, northwest Canada, and to develop a predictive model for rock glacier probability mapping. Identification of rock glaciers follows guidelines set by the International Permafrost Association (IPA) Rock Glacier Action Group, incorporating geomorphological approaches for identification. Of the 530 rock glaciers mapped within three regions of the Mackenzie Mountains, ̴90% were classified as active, with primarily northern orientations. The model utilizes variables such as potential incoming solar radiation (PISR), elevation, slope, aspect, lithology, and topographic position index (TPI) to understand rock glacier distribution. Modeling methods include a Generalized Additive Model (GAM), Random Forest (RF) and Forest-based Classification and Regression (FBCR). The comparison of models revealed that the GAM was the best model, with selected variables. The performance of the GAM was assessed using training (70%) and testing (30%) datasets. The confusion matrix for the training data indicated a total of 321 true negatives (0) and 322 true positives (1), with 50 false negatives and 49 false positives. The training accuracy was calculated to be 0.87, reflecting the proportion of correctly classified instances. An additional test site revealed that the GAM can be generalized to new regions within the Mackenzie Mountains, limiting the time needed for manual identification of rock glaciers in large regions. This research contributes to the existing knowledge on rock glacier formation and persistence and emphasizes the importance of comprehensive inventories for future research and monitoring.
dc.identifier.urihttps://hdl.handle.net/10133/6678
dc.language.isoen
dc.proquestyesNo
dc.publisherLethbridge, Alta. : University of Lethbridge, Dept. of Geography and Environment
dc.publisher.departmentDepartment of Geography and Environment
dc.publisher.facultyArts and Science
dc.relation.ispartofseriesThesis (University of Lethbridge. Faculty of Arts and Science)
dc.subjectrock glacier
dc.subjectpermafrost
dc.subjectMackenzie Mountains
dc.subjectgeneralized additive model
dc.subject.lcshRock glaciers--Research--Mackenzie Mountains (N.W.T. and Yukon)
dc.subject.lcshRock glaciers--Mackenzie Mountains (N.W.T. and Yukon)--Mathematical models
dc.subject.lcshPermafrost--Research--Mackenzie Mountains (N.W.T. and Yukon)
dc.subject.lcshMackenzie Mountains (N.W.T. and Yukon)
dc.subject.lcshGeological modeling
dc.subject.lcshSpatial data mining--Mackenzie Mountains (N.W.T. and Yukon)
dc.subject.lcshLinear models (Statistics)
dc.subject.lcshDissertations, Academic
dc.titleRock glacier catalogue and predictive modeling in the Mackenzie Mountains: predicting rock glacier likelihood with a generalized additive model
dc.typeThesis
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
THIESSEN_RABECCA_MSC_202303.pdf
Size:
2.24 MB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
license.txt
Size:
3.25 KB
Format:
Item-specific license agreed upon to submission
Description:
Download
Collections
Arts and Science, Faculty of
University of Lethbridge Theses