MultiscaleDTM: An open‐source R package for multiscale geomorphometric analysis

Abstract

Digital terrain models (DTMs) are datasets containing altitude values above or below a reference level, such as a reference ellipsoid or a tidal datum over geographic space, often in the form of a regularly gridded raster. They can be used to calculate terrain attributes that describe the shape and characteristics of topographic surfaces. Calculating these terrain attributes often requires multiple software packages that can be expensive and specialized. We have created a free, open‐source R package, MultiscaleDTM, that allows for the calculation of members from each of the five major thematic groups of terrain attributes: slope, aspect, curvature, relative position, and roughness, from a regularly gridded DTM. Furthermore, these attributes can be calculated at multiple spatial scales of analysis, a key feature that is missing from many other packages. Here, we demonstrate the functionality of the package and provide a simulation exploring the relationship between slope and roughness. When roughness measures do not account for slope, these attributes exhibit a strong positive correlation. To minimize this correlation, we propose a new roughness measure called adjusted standard deviation. In most scenarios tested, this measure produced the lowest rank correlation with slope out of all the roughness measures tested. Lastly, the simulation shows that some existing roughness measures from the literature that are supposed to be independent of slope can actually exhibit a strong inverse relationship with the slope in some cases.

Large-scale bedrock outcrop mapping on the NE Atlantic Irish continental margin

“…These variables were chosen to delineate seafloor terrain where outcrop was observed in the video transects. From the MBES data, seven variables were calculated on a 3 × 3 cell analysis window based on the most common terrain attribute used in seafloor geomorphometry (Lecours et al, 2016;Ilich et al, 2021;Ilich et al, 2023): (1) Gradient of slope in degree, which is the maximum rate of change in elevation values (Ilich et al, 2023) and gives information about the stability of sediments and local acceleration of currents (erosion, movement of sediments, and creation of bedforms) (Lecours et al, 2016); (2) Seafloor aspect, giving the orientation of the seafloor at a referenced location (flat, N, S, E, and W); (3) Mean curvature [slope of slope, which indicates with a positive value an upwardly convex surface, and with a negative value an upwardly concave surface, and a value of 0 indicates a flat surface; really high values (>4 or <−4) indicates high relief]); it gives information about flows and channeling of sediments/currents (Dolan et al, 2012;Lecours et al, 2016); (4) BPI -Broad scale; (5) BPI-Fine scale; BPI expresses a seafloor position relative to the surrounding locations. BPI > 0 indicates topographic features higher than the surrounding area like crests.…”

Ensemble modelling to predict the distribution of vulnerable marine ecosystems indicator taxa on data‐limited seamounts of Cabo Verde (NW Africa)

“…Hence, in this study, slope, aspect (converted to eastness and northness) and three types of terrain curvature (plan, profile and mean) were calculated following a Fibonacci sequence of four increasing n values (n = 3, 9, 17, 33) (Dolan et al, 2008). For this, the functions 'SlpAsp' and 'Qfit' of the 'Multiscale DTM' library (Ilich et al, 2023) were used in R Studio Version 4.1.1 (R Studio Team, 2022). Topographic position index (TPI) and vector ruggedness measure (VRM) were calculated at two scales, both fine and broad scales (n = 3, 33), using the 'tpi' and 'vrm' functions, respectively, of the 'spatialEco' R Package (Evans & Ram, 2021).…”