Geomorphometric Analysis using Whitebox Tool - Revision history

Catherine: /* Advantage of Whitebox Tool for geomorphometric analysis */

2025-12-17T18:18:44Z

Advantage of Whitebox Tool for geomorphometric analysis

Catherine: /* Topographic visualization */

2025-12-17T18:13:43Z

Topographic visualization

Catherine: /* Hypsometrically Tinted Hillshade */

2025-12-17T18:10:43Z

Hypsometrically Tinted Hillshade

Catherine: /* Plugin installation */

2025-12-17T18:01:22Z

Plugin installation

Catherine: /* Geomorphons */

2025-12-17T18:00:31Z

Geomorphons

Catherine: /* Reference */

2025-12-17T17:55:54Z

Reference

Catherine: /* Common Pitfalls and Best Practices */

2025-12-17T17:44:37Z

Common Pitfalls and Best Practices

Catherine: /* Conclusion */

2025-12-17T17:43:58Z

Conclusion

Catherine: /* Reference */

2025-12-17T17:41:22Z

Reference

Catherine at 17:35, 17 December 2025

2025-12-17T17:35:16Z

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 [https://www.whiteboxgeo.com/manual/wbt_book/available_tools/geomorphometric_analysis.html WhiteBox] tool offers several significant advantages for performing geomorphometric analysis, particularly in an academic or research environment. As a free and open-source GIS processing library, it provides access to a wide range of terrain-analysis algorithms without the cost barriers associated with commercial software. WhiteboxTools is optimized for raster processing and uses efficient parallel computation, allowing users to work with large DEMs and complex workflows quickly and reliably. Its seamless integration with QGIS makes it easy for students and researchers to incorporate advanced geomorphometric tools into everyday GIS projects.
-Another major advantage is the availability of specialized geomorphometry functions—such as curvature, ruggedness, topographic position, downslope indices, and feature-preserving smoothing—that are not always included in standard GIS packages. These tools help users extract meaningful quantitative metrics describing the shape and structure of the landscape. Because WhiteboxTools is actively maintained and scientifically oriented, it is ideal for teaching, research, hydrology, geomorphology, environmental modeling, and preparing high-quality outputs suitable for academic reports and publications.
+Another major advantage is the availability of specialized geomorphometry functions (such as curvature, ruggedness, topographic position, downslope indices, and feature-preserving smoothing) that are not always included in standard GIS packages. These tools help users extract meaningful quantitative metrics describing the shape and structure of the landscape. Because WhiteboxTools is actively maintained and scientifically oriented, it is ideal for teaching, research, hydrology, geomorphology, environmental modeling, and preparing high-quality outputs suitable for academic reports and publications.
 === Target audience and scope ===

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 To generate this output, go to WhiteboxTools → Geomorphometric Analysis → Hypsometrically Tinted Hillshade. This tool includes several important parameters that control the final visualization. The illumination altitude parameter defines the height of the virtual light source and influences how shadows are cast across the terrain surface. The hillshade weight controls the balance between the hillshade and the elevation color ramp: higher values emphasize relief and terrain texture, while lower values place more emphasis on elevation differences through color. The brightness option enhances overall contrast, improving the visibility of subtle geomorphic features. Together, these parameters allow the user to produce a clear, visually appealing map that supports both qualitative terrain interpretation and high-quality cartographic presentation.
+[[File:HypsometricallTinted.png|thumb|thumb|none|frame|3000px|''Figure 2: Hypsometrically tinted Hillshade generated with Whitebox Tools '']]
-File:HypsometricallTinted.png
 === Hillshade ===

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 To generate this output, go to WhiteboxTools → Geomorphometric Analysis → Hypsometrically Tinted Hillshade. This tool includes several important parameters that control the final visualization. The illumination altitude parameter defines the height of the virtual light source and influences how shadows are cast across the terrain surface. The hillshade weight controls the balance between the hillshade and the elevation color ramp: higher values emphasize relief and terrain texture, while lower values place more emphasis on elevation differences through color. The brightness option enhances overall contrast, improving the visibility of subtle geomorphic features. Together, these parameters allow the user to produce a clear, visually appealing map that supports both qualitative terrain interpretation and high-quality cartographic presentation.
+File:HypsometricallTinted.png
 === Hillshade ===

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 To install the WhiteboxTools plugin in QGIS, the process begins by opening the Plugins menu and selecting Manage and Install Plugins. In the search bar, typing “Whitebox” displays the list of available Whitebox-related extensions. The correct plugin to install is WhiteboxTools for QGIS. If the plugin does not appear automatically, the standalone WhiteboxTools package must be downloaded from the official website: https://www.whiteboxgeo.com/download-whiteboxtools
-. After downloading, the folder containing the executable file ( whitebox_tools.exe ) should be extracted. Once installed, the path to the executable must be configured in QGIS: this is done by navigating to Settings → Options → Processing → Providers → WhiteboxTools, and selecting the extracted whitebox_tools.exe file as the executable. After this configuration is completed, the full suite of geomorphometric tools becomes available in the QGIS Processing Toolbox under WhiteboxTools
+. After downloading, the folder containing the executable file ( whitebox_tools.exe ) should be extracted. Once installed, the path to the executable must be configured in QGIS: this is done by navigating to Settings → Options → Processing → Providers → WhiteboxTools, and selecting the extracted whitebox_tools.exe file as the executable (fig 1). After this configuration is completed, the full suite of geomorphometric tools becomes available in the QGIS Processing Toolbox under WhiteboxTools
 [[File:Plugin Installation .png|thumb|thumb|none|frame|3000px|''Figure 1: WhiteboxTools Plugin Setup in QGIS'']]

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 In WhiteboxTools, geomorphons can be computed by navigating to Whitebox Tools → Geomorphometric Analysis → Geomorphons. The primary input is a DEM. Several parameters control the scale and sensitivity of the analysis. The search distance defines how far the algorithm looks in each direction to detect elevation differences; increasing this value emphasizes broader landforms, while smaller values highlight fine-scale features. The flatness distance specifies the elevation tolerance used to identify flat surfaces—larger values result in more areas classified as flat. The skip distance allows the algorithm to ignore very near cells, reducing the influence of local noise or small artifacts. Together, these parameters allow the user to tailor the geomorphon output to the spatial scale and geomorphic characteristics of the study area.
-The output raster encodes landform types using integer values, where each value corresponds to a specific geomorphic class defined by Whitebox '''(fig. .. to...????????? insert complete the legend with the whiteBix legend 0-8).'''
+The output raster encodes landform types using integer values, where each value corresponds to a specific geomorphic class defined by Whitebox (figure6)
 [[File:GeomorphonsFigure.png|thumb|thumb|none|frame|3000px|''Figure 6. Geomorphons-Based Landform Classification'']]

← Older revision		Revision as of 17:55, 17 December 2025
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	Lindsay, J. B. (2016). Whitebox GAT: A case study in geomorphometric analysis. Computers & Geosciences, 95, 75–84. https://doi.org/10.1016/j.cageo.2016.07.003		Lindsay, J. B. (2016). Whitebox GAT: A case study in geomorphometric analysis. Computers & Geosciences, 95, 75–84. https://doi.org/10.1016/j.cageo.2016.07.003

	~~Whitebox~~ ~~Geospatial~~ - Geomorphometric analysis. https://www.whiteboxgeo.com/manual/wbt_book/available_tools/geomorphometric_analysis.html		Lindsay, J. B. (2023, March 25). Geomorphometric analysis tools. WhiteboxTools User Manual. https://www.whiteboxgeo.com/manual/wbt_book/available_tools/geomorphometric_analysis.html

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 When conducting a geomorphometric analysis, several common issues can significantly affect the quality and interpretation of results. Digital Elevation Models may contain noise or artefacts, particularly in older or low-resolution datasets, and applying geomorphometric derivatives directly to such data can lead to misleading outputs; therefore, DEM smoothing should be performed prior to analysis. Care must also be taken with the Z conversion factor, as inconsistent vertical and horizontal units can distort slope, curvature, and related parameters. In addition, certain visualizations, such as grayscale aspect maps, may be difficult to interpret and should be symbolized using appropriate color schemes. Finally, individual geomorphometric parameters should not be interpreted in isolation; combining multiple metrics (e.g., slope, curvature, TPI, downslope index) provides a more robust and meaningful understanding of landscape structure and processes.
+Beyond technical considerations, best practice in geomorphometric analysis also requires a strong emphasis on scale, context, and reproducibility. Many geomorphometric parameters are scale-dependent, meaning that window sizes, search distances, or filter dimensions must be selected in relation to the resolution of the DEM and the spatial extent of the study area; inappropriate scale choices can either oversimplify landforms or exaggerate local noise. It is therefore recommended to test multiple parameter settings and explicitly justify the selected values. Furthermore, geomorphometric outputs should always be interpreted in the context of regional geology, geomorphic history, and surface processes rather than as purely mathematical products. Documenting processing steps, parameter choices, and data sources is essential to ensure transparency and reproducibility, especially when results are intended for academic publication or decision-making. By combining careful preprocessing, thoughtful parameter selection, multi-metric interpretation, and clear documentation, geomorphometric analysis becomes a robust and scientifically defensible tool for understanding landscape structure and dynamics.
 == Conclusion ==

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 To combine these layers, each raster is first normalized using the QGIS Raster Calculator so that values range between 0 and 1. The operation are : slope_normalized=("slope@1" - SLOPE_MIN) / (SLOPE_MAX - SLOPE_MIN); Mean Curvature_normalized = (abs("curvature@1") - CURVABS_MIN) / (CURVABS_MAX - CURVABS_MIN); Downslope_normalized=("downslope@1" - DOWN_MIN) / (DOWN_MAX - DOWN_MIN);  The normalized slope, curvature, and downslope index are then combined using a weighted linear model. A simple formulation assigns equal weights to each parameter, producing a relative erosion susceptibility index where higher values represent greater potential erosion risk. The resulting raster can be classified into low, moderate, and high susceptibility classes for interpretation and visualization.
+==Common Pitfalls and Best Practices==
-== Conclusion ==
-===Common Pitfalls and Best Practices===
 When conducting a geomorphometric analysis, several common issues can significantly affect the quality and interpretation of results. Digital Elevation Models may contain noise or artefacts, particularly in older or low-resolution datasets, and applying geomorphometric derivatives directly to such data can lead to misleading outputs; therefore, DEM smoothing should be performed prior to analysis. Care must also be taken with the Z conversion factor, as inconsistent vertical and horizontal units can distort slope, curvature, and related parameters. In addition, certain visualizations, such as grayscale aspect maps, may be difficult to interpret and should be symbolized using appropriate color schemes. Finally, individual geomorphometric parameters should not be interpreted in isolation; combining multiple metrics (e.g., slope, curvature, TPI, downslope index) provides a more robust and meaningful understanding of landscape structure and processes.
+== Conclusion ==
+This tutorial demonstrated a complete and reproducible workflow for conducting a geomorphometric analysis using WhiteboxTools within QGIS, relying entirely on free and open-source software. Starting from a Digital Elevation Model, the methodology guided users through DEM preprocessing, noise reduction, and the extraction of key primary and secondary geomorphometric parameters such as slope, aspect, curvature, downslope index, geomorphons, and topographic indices. Each parameter was presented not only from a computational perspective, but also with an emphasis on geomorphic interpretation and visualization.
+By integrating multiple geomorphometric derivatives rather than relying on a single parameter, the tutorial highlights how terrain structure, processes, and landform patterns can be quantitatively characterized in a robust and meaningful way. The use of feature-preserving smoothing, appropriate visualization techniques (hillshade, directional relief, hypsometric tinting), and careful parameter selection ensures that the derived outputs are both scientifically reliable and visually interpretable.
+Overall, this workflow provides a transferable framework applicable to a wide range of disciplines, including geomatics, geology, environmental studies, geography, and hydrology. The tutorial equips users with practical skills to analyze and interpret topography, supports academic research and publication-quality outputs, and encourages best practices in geomorphometric analysis using modern, open-source geospatial tools.
 == Reference ==

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 == Reference ==
-WhiteBox tool user online manual : https://www.whiteboxgeo.com/manual/wbt_book/available_tools/geomorphometric_analysis.html
+Lindsay, J. B. (2016). Whitebox GAT: A case study in geomorphometric analysis. Computers & Geosciences, 95, 75–84. https://doi.org/10.1016/j.cageo.2016.07.003
+Whitebox Geospatial - Geomorphometric analysis. https://www.whiteboxgeo.com/manual/wbt_book/available_tools/geomorphometric_analysis.html