README

Alexander Ilich January 30, 2023

MultiscaleDTM

R-CMD-check CRAN License: GPLv3 DOI

Please cite as

Ilich, Alexander R.; Misiuk, Benjamin; Lecours, Vincent; Murawski, Steven A.; 2021. “MultiscaleDTM”, https://doi.org/10.5281/zenodo.5548338. https://github.com/ailich/MultiscaleDTM.

Purpose

This package calculates multi-scale geomorphometric terrain attributes from regularly gridded digital terrain models (DTM; i.e. elevation or bathymetry rasters) via a specified window size.

Figure adapted from Wilson et al. (2007)

Install and Load Package

The package can be installed from CRAN using install.packages("MultiscaleDTM") or the development version can be installed from github using the code remotes::install_github("ailich/MultiscaleDTM"). If you are using Windows, you may need to install Rtools using the instructions found here). To install from github you must already have the remotes package installed, which can be installed using install.packages("remotes")

This package relies on the terra package for handling of spatial raster data.

Main Functions

Slope, Aspect and Curvature

Figure adapted from Walbridge et al., (2018)

Roughness

Figure adapted from Sappington et al. (2007)

Figure adapted from Habib (2021)

Figure adapted from Friedman et al. (2012) and created with BioRender.com.

Figure adapted from Jenness (2004)

Figure adapted from Cavalli et al. (2008)

Relative Position

Figure adapted from Lundblad et al., (2006)

Tutorial

In this tutorial we will calculate various terrain attributes using a 5 x 5 cell rectangular window. Any rectangular odd numbered window size however could be used (see figure directly below). Window sizes are specified with a vector of length 2 of c(n_rows, n_cols). If a single number is provided it will be used for both the number of rows and columns. The only metric that does not follow this syntax is BPI which uses an annulus shaped focal window which we will calculate using an inner radius of 4 and an outer radius of 6 cells.

Load packages

library(MultiscaleDTM) #Load MultiscaleDTM package

See package help page

help(package="MultiscaleDTM")

Read in Data

r<- rast(volcano, extent= ext(2667400, 2667400 + ncol(volcano)*10, 6478700, 6478700 + nrow(volcano)*10), crs = "EPSG:27200")

Slope, Aspect, and Curvature

slp_asp<- SlpAsp(r = r, w = c(5,5), unit = "degrees", method = "queen", metrics = c("slope", "aspect", "eastness", "northness"))

qmetrics<- Qfit(r, w = c(5,5), unit = "degrees", metrics = c("elev", "qslope", "qaspect", "qeastness", "qnorthness", "profc", "planc", "twistc", "meanc", "maxc", "minc", "features"), na.rm = TRUE)

To explore these measures in an interactive environment use explore_terrain() or go to this website

Roughness

vrm<- VRM(r, w=c(5,5), na.rm = TRUE)

Note: multi-scale SAPA is experimental. The established metric by De Preez (2015) would use w=1.

sapa<- SAPA(r, w=c(5,5), slope_correction = TRUE)

adj_SD<- AdjSD(r, w=c(5,5), na.rm = TRUE)

rie<- RIE(r, w=c(5,5), na.rm = TRUE)

Relative Position

tpi<- TPI(r, w=c(5,5), na.rm = TRUE)

rdmv<- RDMV(r, w=c(5,5), na.rm = TRUE, method="range")

bpi<- BPI(r, radius = c(4,6), unit = "cell", na.rm = TRUE)

The annulus window for BPI can be specified in either cell units (number of raster cells) or in map units (e.g. meters) which can be useful if your x and y resolutions are not equal. Additionally, the function annulus_window can be used to verify that you are specifying your window correctly (NA’s are excluded cells and 1’s are included cells) and can be directly supplied to the w argument in the BPI funtion instead of using radius and unit arguments.

annulus_window(radius = c(4,6), unit = "cell")
##       [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
##  [1,]   NA   NA   NA   NA   NA   NA    1   NA   NA    NA    NA    NA    NA
##  [2,]   NA   NA   NA    1    1    1    1    1    1     1    NA    NA    NA
##  [3,]   NA   NA    1    1    1    1    1    1    1     1     1    NA    NA
##  [4,]   NA    1    1    1   NA   NA   NA   NA   NA     1     1     1    NA
##  [5,]   NA    1    1   NA   NA   NA   NA   NA   NA    NA     1     1    NA
##  [6,]   NA    1    1   NA   NA   NA   NA   NA   NA    NA     1     1    NA
##  [7,]    1    1    1   NA   NA   NA   NA   NA   NA    NA     1     1     1
##  [8,]   NA    1    1   NA   NA   NA   NA   NA   NA    NA     1     1    NA
##  [9,]   NA    1    1   NA   NA   NA   NA   NA   NA    NA     1     1    NA
## [10,]   NA    1    1    1   NA   NA   NA   NA   NA     1     1     1    NA
## [11,]   NA   NA    1    1    1    1    1    1    1     1     1    NA    NA
## [12,]   NA   NA   NA    1    1    1    1    1    1     1    NA    NA    NA
## [13,]   NA   NA   NA   NA   NA   NA    1   NA   NA    NA    NA    NA    NA

References

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Du Preez, C., 2015. A new arc–chord ratio (ACR) rugosity index for quantifying three-dimensional landscape structural complexity. Landscape Ecol 30, 181–192. https://doi.org/10.1007/s10980-014-0118-8

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Friedman, A., Pizarro, O., Williams, S.B., Johnson-Roberson, M., 2012. Multi-Scale Measures of Rugosity, Slope and Aspect from Benthic Stereo Image Reconstructions. PLOS ONE 7, e50440. https://doi.org/10.1371/journal.pone.0050440

Habib, M., 2021. Quantifying Topographic Ruggedness Using Principal Component Analysis. Advances in Civil Engineering 2021, e3311912. https://doi.org/10.1155/2021/3311912

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Lecours, V., Devillers, R., Simms, A.E., Lucieer, V.L., Brown, C.J., 2017. Towards a Framework for Terrain Attribute Selection in Environmental Studies. Environmental Modelling & Software 89, 19–30. https://doi.org/10.1016/j.envsoft.2016.11.027

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Misiuk, B., Lecours, V., Dolan, M.F.J., Robert, K., 2021. Evaluating the Suitability of Multi-Scale Terrain Attribute Calculation Approaches for Seabed Mapping Applications. Marine Geodesy 44, 327–385. https://doi.org/10.1080/01490419.2021.1925789

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Sappington, J.M., Longshore, K.M., Thompson, D.B., 2007. Quantifying Landscape Ruggedness for Animal Habitat Analysis: A Case Study Using Bighorn Sheep in the Mojave Desert. The Journal of Wildlife Management 71, 1419–1426. https://doi.org/10.2193/2005-723

Walbridge, S., Slocum, N., Pobuda, M., Wright, D.J., 2018. Unified geomorphological analysis workflows with benthic terrain modeler. Geosciences 8, 94. https://doi.org/10.3390/geosciences8030094

Weiss, A., 2001. Topographic Position and Landforms Analysis. Presented at the ESRI user conference, San Diego, CA.

Wilson, M.F., O’Connell, B., Brown, C., Guinan, J.C., Grehan, A.J., 2007. Multiscale Terrain Analysis of Multibeam Bathymetry Data for Habitat Mapping on the Continental Slope. Marine Geodesy 30, 3-35. https://doi.org/10.1080/01490410701295962

Wood, J., 1996. The geomorphological characterisation of digital elevation models (Ph.D.). University of Leicester.