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

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作者
Giuseppe Amatulli
Sami Domisch
Mao-Ning Tuanmu
Benoit Parmentier
Ajay Ranipeta
Jeremy Malczyk
Walter Jetz
机构
[1] Yale University,Department of Ecology and Evolutionary Biology
[2] Yale School of Forestry & Environmental Studies,Division of Biology
[3] Yale University,undefined
[4] Yale Center for Research Computing,undefined
[5] Yale University,undefined
[6] Center for Science and Social Science Information,undefined
[7] Yale University,undefined
[8] Biodiversity Research Center,undefined
[9] Academia Sinica,undefined
[10] University of Maine,undefined
[11] Mitchell Center for Sustainability Solutions,undefined
[12] Imperial College London,undefined
[13] Present address: Leibniz-Institute of Freshwater Ecology and Inland Fisheries,undefined
[14] Department of Ecosystem Research,undefined
[15] Berlin,undefined
[16] D-12489,undefined
[17] Germany.,undefined
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摘要
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.
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