Classification of elevation rasters with this digital model of hillslope position represent base maps that can be used to (1) improve research on toposequences by providing explicit definitions of each hillslope element’s location, (2) facilitate the disaggregation of soil map unit complexes, and (3) identify map unit inclusions that occur due to subtle topographic variation.[Read More...]
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1 February 2015 Author: Dr. Miller
4 November 2014 Author: Dr. Miller
This poster provides examples from different landscapes demonstrating the hillslope position model’s ability to better place soil delineations where defendable landscape breaks exist. The results of this model are base maps that can be used to (1) improve research on toposequences by providing explicit definitions of each hillslope element’s location, (2) facilitate the disaggregation of soils currently mapped as complexes due to topographic variation, and (3) identify map unit inclusions in areas of subtle topographic variation. The base maps developed by the model can also help identify areas of possible mismapping, especially where soil boundaries cross topographic breaks.[Read More...]
16 June 2014 Author: Dr. Miller
The central purpose of this toolbox is to provide ArcGIS users a convenient way to calculate hillslope position from elevation grids. However, the Relief Analysis Toolbox also includes some other ArcGIS models that may be of interest to anyone working with landscape and landform segmentation. The main features of this toolbox are:
- hillslope position (calibrated to the U.S. Soil Survey),
- relative elevation (a moving-window approach as described in Miller, 2014; middle elevation used for reference),
- topographic position index (modified from Weiss, 2001; mean elevation used for reference),
- TPI slope position,
- TPI landform class,
- plus a couple of data classification tools that might come in handy.
More about the Digital Classification of Hillslope Position
Classification of hillslope position has a long history in soil geomorphology. However, its roots in tacit field knowledge has prevented its use in GIS. The model provided here has been calibrated and validated on soil scientists’ observations in the field. The resulting maps of hillslope position represent base maps that can be used to (1) improve research on toposequences by providing explicit definitions of each hillslope element’s location, (2) facilitate the disaggregation of soils currently mapped as complexes, and (3) identify map unit inclusions that exist due to subtle topographic variation. The base maps developed by the model can also help identify areas of possible mismapping, especially where soil boundaries cross topographic breaks. This information can enable the mapper to redefine many existing soil map unit boundaries, placing them more correctly at locations where defendable landscape breaks exist.
- Demonstration Pack
- A set of grid files for testing the Hillslope Position model without the need to create any of the prerequisite terrain derivatives.
- Profile Curvature in GRASS (for those not familiar with GRASS)
- Using different analysis scales is key to correctly calculating hillslope position. Profile curvature is the one terrain derivative that we can’t do a user-specified analysis scale in ArcGIS yet. But don’t worry, these supplemental instructions will walk you through the process for using GRASS to get the job done.
- ArcGIS layer file for recommended color scheme
Development of the hillslope position classification tool is documented in the following publications and dissertation, and should be used for citation as appropriate:
Miller, B.A. and R.J. Schaetzl, 2015. Digital classification of hillslope position. Soil Science Society of America Journal 79(1):132-145. doi:10.2136/sssaj2014.07.0287.
Miller, B.A., 2014. Semantic calibration of digital terrain analysis. Cartography and Geographic Information Science Journal 41:166-176. doi:10.1080/15230406.2014.883488.
Miller, B.A. 2013. Incorporating tacit knowledge of soil-landscape relationships for digital soil and landscape mapping applications. Dissertation, Department of Geography, Michigan State University, USA.