Geomorpho90m - Global high-resolution geomorphometry layers: empirical evaluation and accuracy assessment

Abstract

Topographical relief is composed of the vertical and horizontal variations of the Earth’s terrain and drives processes in geography, climatology, hydrology, and ecology. Its assessment and characterisation is fundamental for various types of modelling and simulation analyses. In this regard, the Multi-Error-Removed Improved Terrain (MERIT) Digital Elevation Model (DEM) is the best global, high-resolution DEM currently available at a 3 arc-seconds (90 m) resolution. This is an improved product as multiple error components have been corrected from the underlying Shuttle Radar Topography Mission (SRTM3) and ALOS World 3D - 30 m (AW3D30) DEMs. To depict topographical variations worldwide, we developed the Geomorpho90m dataset comprising of different geomorphometry features derived from the MERIT-DEM. The fully standardised geomorphometry variables consist of layers that describe (i) the rate of change using the first and second order derivatives, (ii) the ruggedness, and (iii) the geomorphology landform. To assess how remaining artefacts in the MERIT-DEM could affect the derived topographic variables, we compared our results with the same variables generated using the 3D Elevation Program (3DEP) DEM, which is the highest quality DEM for the United States of America. We compared the two data sources by calculating the first order derivative (i.e., the rate of change through space measured in degrees) of the difference between a MERIT-derived vs. a 3DEP-derived topographic variable. All newly-created topographic variables are readily available at resolutions of 3 and 7.5 arc-seconds under the WGS84 geographic system, and at a spatial resolution of 100 m under the Equi7 projection. The newly-developed Geomorpho90m dataset provides a globally standardised dataset for environmental models and analyses in the field of geography, geology, hydrology, ecology and biogeography.

Publication
PeerJ Preprints, (7), pp. e27595v1, https://doi.org/10.7287/peerj.preprints.27595v1