Pulse Brain · Growing Health Evidence Index
Tier 3 — Observational / field trialPeer-reviewed

A suite of global, cross-scale topographic variables for environmental and biodiversity modeling

Amatulli, G. et al

Sci. Data 5, 180040 (2018) · 2018

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Summary

Abstract Topographic variation underpins a myriad of patterns and processes in hydrology, climatology, geography and ecology and is key to understanding the variation of life on the planet. A fully standardized and global multivariate product of different terrain features has the potential to support many large-scale research applications, however to date, such datasets are unavailable. Here we used the digital elevation model products of global 250 m GMTED2010 and near-global 90 m SRTM4.1dev to derive a suite of topographic variables: elevation, slope, aspect, eastness, northness, roughness, terrain roughness index, topographic position index, vector ruggedness measure, profile/tangential curvature, first/second order partial derivative, and 10 geomorphological landform classes. We aggregated each variable to 1, 5, 10, 50 and 100 km spatial grains using several aggregation approaches. While a cross-correlation underlines the high similarity of many variables, a more detailed view in four mountain regions reveals local differences, as well as scale variations in the aggregated variables at different spatial grains. All newly-developed variables are available for download at Data Citation 1 and for download and visualization at http://www.earthenv.org/topography .

Outcomes reported

Referenced by Nature Communications British biodiversity scenarios as citation 132; likely supports topic area: biodiversity / conservation; methods / modelling / statistics. Topics: biodiversity / conservation; methods / modelling / statistics Evidence type: Modelling / projection Source report: Nature Communications British biodiversity scenarios Ref#: Nature Communications British biodiversity scenarios #132 Original: Amatulli, G. et al. A suite of global, cross-scale topographic variables for environmental and biodiversity modeling. Sci. Data 5, 180040 (2018).

Theme
Farming systems, soils & land use
Subject
Other / interdisciplinary
Study type
Research
Source type
Peer-reviewed research
Status
Published
Geography
United Kingdom
System type
Other
DOI
10.1038/sdata.2018.40
Catalogue ID
IRmoq83nfn-de1eb3
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