Elsevier

Geomorphology

Volume 387, 15 August 2021, 107778
Geomorphology

An intelligent swath tool to characterize complex topographic features: Theory and application in the Teton Range, Licking River, and Olympus Mons

https://doi.org/10.1016/j.geomorph.2021.107778Get rights and content

Highlights

  • An intelligent swath tool can objectively characterize complex geomorphic boundaries.

  • Post-processing functionalities include, but not limit to, cross-swath, data reclassification, slice, histogram.

  • The utility of the tool is demonstrated through applications: a mountainous area, a river system, and a volcano topography.

  • The full library code, tutorials and documentation is open-source under the Apache 2.0 license.

Abstract

Swath analysis has been useful for linking topography to geomorphic and tectonic processes in a variety of landscapes. Established swath methods have been limited to rectangular or simplified curvilinear sampling blocks despite most geologic structures having complex boundaries and orientations. Moreover, swath boundaries and intervals are commonly defined by arbitrary boundaries and without defined corner points, which makes reproducibility difficult. To address these shortcomings we developed PyOSP (Python Library for Object-oriented Swath Profile), an open-source library that can objectively characterize complex geomorphic boundaries using elevation, slope angle, topographic position index, or other raster calculations by intelligently assimilating geoprocessing information into swath analysis. In addition, PyOSP has post-processing tools (cross-swath, data reclassification, slice, histogram analysis, etc.) and the ability to communicate easily with other GIS software. To evaluate the utility of PyOSP, we used it in three case studies (Teton Range in Wyoming, Licking River in Kentucky, and Olympus Mons on Mars) that illustrate the library's robustness, from objective quantitative description of the topography to improved insights with post-processing capabilities.

Introduction

Swath analysis has been frequently employed to quantitatively summarize elevation trends over large-scale landforms such as plateaus or mountains (Fielding et al., 1994; Bishop et al., 2003; Molin et al., 2004; Scotti et al., 2014) in an effort to elucidate patterns of erosion, deposition, alluviation, precipitation, and their driving forces (Kühni and Pfiffner, 2001; Musumeci et al., 2003; Bookhagen et al., 2005; Hoke and Garzione, 2008; Foster et al., 2010). Swath analysis is the integration of areas within an inclusive rectangular, curvilinear, or circular region into an analysis window with the purpose of reducing complex topographic data into a simpler statistical summary (Telbisz et al., 2013). The typical statistics employed in swath analysis are minimum, mean, maximum, or various quantiles of the study area's elevation. The results of swath analysis results are considered more convincing than a traditional cross-section evaluation. Complex interactions among climate, topography, and tectonics can result in diagnostic patterns such as asymmetry, dramatic changes in relief, and correlation between erosion (glaciers, landslides, etc.) and maximum or average topography (Munroe, 2006; van der Beek and Bourbon, 2008; Champagnac et al., 2009; Dortch et al., 2011). Moreover, swath analysis has been integral to understanding the spatial-temporal evolution of river incision (Grohmann, 2004; Godard et al., 2010) and dynamic processes such as tectonic uplift, denudation, and alluviation (Pratt-Sitaula et al., 2004; Korup et al., 2005; Robl et al., 2008; Stüwe et al., 2009; Wegmann and Pazzaglia, 2009).

Advances in geographic information system software (e.g., ArcGIS, QGIS, GRASS) and availability of high-resolution elevation data have made it possible to extract topographic features quickly and easily. However, the arbitrary nature of drawn polyline or polygon shapes used to define topographic analyses hampers the reproducibility of geomorphologic characteristics. For example, the simple traditional elevation profile across a feature can change dramatically because of segment length and orientation. Typical fixed-width swath analysis addresses these issues because it contains summary statistics of the full range of values (mean, minimum, maximum, and quartiles). Sensitivity analysis by Telbisz et al. (2013) demonstrates that swath width, orientation, and horizontal bin size can tolerate a wide range in selections; however, it also shows that the optimal values still depend on manual tuning and subjective judgment.

The solution of incorporating a larger area within the swath analysis to account for the variable nature of topography creates new issues because available swath methods are generally limited to rectangular, curvilinear, or circular shapes (Telbisz et al., 2013). The requirement of using contiguous rectangular chunks of data inevitably leads to inclusion of extraneous data, which can hinder the pattern of nuances in the best case and dramatically skew summary swath statistics in the worst case. Moreover, when rectangular swath profiles are applied to intricate features, such as mountain ranges or river valleys, systematic error caused by incorporating nonessential data or missing essential data is inevitable. An important step toward addressing data capture was the development of curvilinear swath profiles (Lin and Oguchi, 2006; Hergarten et al., 2014), which enabled the topographic data to be captured along a curvilinear path. Nevertheless, swath width and orientation along the longitudinal direction are still subjective and require manual tuning throughout the profile, which can be time-intensive, requires expert knowledge, and increases accuracy (correctness) at the expense of precision (reproducibility).

In an effort to resolve outstanding issues around reproducibility and swath boundaries, we developed an open-source library PyOSP (Python Library for Object-oriented Swath Profile) that combines geoprocessing with swath profile analysis to assimilate landform information and boundary conditions into the evaluation process. Disparate topographic features will be best characterized by different value ranges or data parameters, or both (e.g., elevation, slope, local relief, topographic position index, etc.). Thus, expert knowledge is necessary to choose the appropriate parameters, but the resulting complex boundary will be objectively defined and easily reproduced given the same parameter conditions. We used an “object-oriented” approach to swath analysis, because the key element is to objectively define a topographic object, which is in contrast with previous “functional” approaches. The ultimate goal of this study aims to fulfill the practical needs of swath profile analysis at different levels of research and education while simultaneously facilitating collaborations for new developments.

Section snippets

Linear/curvilinear and circular swath profiles

A swath profile consists of stacking a set of equal-length profile lines (Baulig, 1926; Tricart and Cailleux, 1958) in a rectangular, curvilinear, or circular shape (Karátson et al., 2012; Telbisz et al., 2013; Hergarten et al., 2014), from which data can be sampled. Rectangular swath profiles are a simplified zero-curvature case of a curvilinear swath profile, thus we discuss them jointly. While varying data types (e.g. relief, roughness, precipitation, temperature, etc.) have been

Overview

The structure of the PyOSP library comprises a set of modules with two core computing components: curvilinear swath profile (curvsp) and circular swath profile (cirsp) (Fig. 4). Each module contains an abstract class called Base_curv or Base_cir, which serves as the parent class for subsequent swath profile approaches (i.e., child classes). The main elements necessary to generate a swath profile, such as the input baseline shapefile, a GeoRaster, and desired summary statistics (mean, minimum,

Geologic setting

The Teton Range is located along the eastern margin of the Basin and Range extensional province, bounded by the Teton normal fault to the east and Basin and Range extensional faulting to the west. Inverse thermal-history modeling suggests footwall uplift of the Teton Range was initiated at 15–13 Ma in the northern part of the range and migrated to the south (Brown et al., 2017). The pre-existing extensional topography influenced by exhumation, rock strength, and fluvial erosion was strongly

Conclusions

Python object-oriented swath profile library (PyOSP) is an intelligent open-source swath-analysis tool with more utility and flexibility than traditional fixed-width approaches because of the ability to swath areas with irregularly shaped boundaries by utilizing geoprocessing techniques that objectively identify topographic features. PyOSP is capable of reproducing results despite varying input parameters such as swath width, orientation of the topographic feature, or subjective choice of the

Funding

The authors received no specific funding for this work.

Availability of data and material

The data and material that support the findings are included within the article and the supplementary material. Any additional queries may be directed to the corresponding author.

Code availability

The computational code related to this article can be found at https://github.com/PyOSP-devs/PyOSP, an open-source online data repository hosted by GitHub.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

We thank Meg Smath of the Kentucky Geological Survey for her editorial help. We also thank the reviewers and editor for their careful reading of our manuscript and their constructive comments and suggestions.

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