LiDAR Characterization of Boreal Understory

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dc.contributor.advisorMcDermid, Gregory J.
dc.contributor.authorLosada Rozo, Silvia Alejandra
dc.contributor.committeememberMcDermid, Gregory J.
dc.contributor.committeememberGoldblum, David
dc.contributor.committeememberChamer, Laura E.
dc.date2021-11
dc.date.accessioned2021-05-17T18:37:37Z
dc.date.available2021-05-17T18:37:37Z
dc.date.issued2021-05-13
dc.description.abstractThe understory vegetation layer contributes considerably to the physical structure of boreal forests. This research sought to understand the relationships between field- and LiDAR- (light detection and ranging-) derived measures of boreal understory structure. As well as how environmental factors may influence discrepancies that can arise between these derived measures. Five attributes to map and characterize the boreal understory vegetation were selected: mean understory height, percent cover, density, complexity, and volume. Percent understory cover showed limited bias in LiDAR-derived estimates of compared to field measurements, in northeastern Alberta. However, LiDAR was shown to underestimate understory mean height and volume, and to overestimate understory density and complexity. Generalized linear model regression analysis were used to understand the influence of external environmental factors on these error patterns. Explanatory variables for these models included canopy openings, bole density, canopy complexity, and ecosite type. It was found that canopy openings reduced errors in understory mean height, percent cover, and volume. Higher bole density was strongly associated with increased errors in understory mean height and volume, and had weak influence on errors in understory percent cover, complexity, and density. More complex canopies were seen to slightly increase the errors in understory volume and did not influence errors in the remaining attributes. Finally, ecosite had a strong influence on errors in understory mean height, complexity, and volume. In the final phase of this research, a series of predictive maps of understory structure were developed across a 4300-hectare study area in the central mixed-wood subregion of the boreal forest, with independent-validation coefficients of determination ranging from 0.41 - 0.59.en_US
dc.identifier.citationLosada Rozo, S. A. (2021). LiDAR Characterization of Boreal Understory (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.en_US
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/38878
dc.identifier.urihttp://hdl.handle.net/1880/113431
dc.language.isoengen_US
dc.publisher.facultyArtsen_US
dc.publisher.institutionUniversity of Calgaryen
dc.rightsUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.en_US
dc.subjectUnderstory vegetationen_US
dc.subjectLiDARen_US
dc.subjectboreal foresten_US
dc.subjectforest structureen_US
dc.subjectforestryen_US
dc.subjecterroren_US
dc.subject.classificationForestry and Wildlifeen_US
dc.subject.classificationEcologyen_US
dc.subject.classificationPhysical Geographyen_US
dc.subject.classificationRemote Sensingen_US
dc.titleLiDAR Characterization of Boreal Understoryen_US
dc.typemaster thesisen_US
thesis.degree.disciplineGeographyen_US
thesis.degree.grantorUniversity of Calgaryen_US
thesis.degree.nameMaster of Science (MSc)en_US
ucalgary.item.requestcopytrueen_US
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