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Development and assessment of spatially heterogeneous scaling methods for multiscale topographic characterization

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Title: Development and assessment of spatially heterogeneous scaling methods for multiscale topographic characterization
Author: Newman, Daniel
Department: Department of Geography, Environment and Geomatics
Program: Geography
Advisor: Lindsay, John
Abstract: Topography is an important interface influencing many natural environmental systems. As topographic sampling technology has improved, data sets increasingly cover broader areas at finer spatial resolutions. The unprecedented detail and coverage of topographic surveys has introduced new challenges for topographic analysis. As a result, a significant number of research studies have been undertaken over several decades to understand scale, develop methodologies to manipulate and analyze scale, and to incorporate scaled topographic information into applied domains. This thesis continues this effort by expanding upon and assessing recent developments in spatially heterogeneous scale representation. Spatially heterogeneous scale representation allows the scale at which topography is characterized to vary spatially. This addresses several theoretical issues regarding the semantics of topography, process, and scale. However, existing spatially heterogeneous methods are limited, and the idea as a whole remains untested. The purpose of this thesis is to expand the methodological approach by developing a generalizable framework for implementing topographic characterization, and assessing the theoretical and practical implications of the approach. This was accomplished by evaluating existing scaling frameworks and developing an algorithm to implement spatially heterogeneous scale representation for a wide variety of local terrain attributes. The outputs of this algorithm were compared to other scaling methods in a digital soil mapping application. The results found Gaussian smoothing had favourable properties when coupled with a content time implementation. Scale-standardization was introduced to compare measurements across scales, such that a maximization function could identify and measure locally dominant topographic features. Further testing revealed that in general, spatially heterogeneous scaling performed equally with cutting edge homogeneous scale selection techniques. However, using multiple ranges of heterogeneously scaled data proved significantly beneficial. It was concluded that spatially heterogeneous scale representation offers an efficient method for representing multiscale topographic information, and more importantly, is better able to characterize complex topography.
URI: https://hdl.handle.net/10214/27070
Date: 2022-07-15
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Related Publications: Newman, D. R., Cockburn, J. M. H., Drǎguţ, L., & Lindsay, J. B. (2022). Evaluating Scaling Frameworks for Multiscale Geomorphometric Analysis. Geomatics, 2(1), 36–51. https://doi.org/10.3390/geomatics2010003Newman, D. R., Cockburn, J. M. H., Drǎguţ, L., & Lindsay, J. B. (2022). Local scale optimization of geomorphometric land surface parameters using scale-standardized Gaussian scale-space. Computers & Geosciences, 165. https://doi.org/10.1016/j.cageo.2022.105144


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