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Data Publisher for Earth & Environmental Science

Amatulli, Giuseppe; Domisch, Sami; Tuanmu, Mao-Ning; Parmentier, Benoit; Ranipeta, Ajay; Malczyk, Jeremy; Jetz, Walter (2018): A suite of global, cross-scale topographic variables for environmental and biodiversity modeling, links to files in GeoTIFF format [dataset publication series]. PANGAEA, https://doi.org/10.1594/PANGAEA.867115, Supplement to: Amatulli, G et al. (2018): A suite of global, cross-scale topographic variables for environmental and biodiversity modeling. Scientific Data, 5, 180040, https://doi.org/10.1038/sdata.2018.40

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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 basic research and analytical applications, however to date, such datasets are unavailable. Here we used the digital elevation model products of global 250 m GMTED2010 and near-global 90m 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.
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