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|Created:||Dec 06, 2018 at 6:32 p.m.|
|Last updated:|| Dec 06, 2018 at 6:34 p.m.
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LYONS, Nathan J.1, BANDARAGODA, Christina2, BARNHART, Katherine R.3, GASPARINI, Nicole M.1, HOBLEY, Daniel E.J.4, HUTTON, Eric5, ISTANBULLUOGLU, Erkan2, MOUCHENE, Margaux3, SIDDHARTHA NUDURUPATI, Sai2 and TUCKER, Gregory E.3, (1)Department of Earth and Environmental Sciences, Tulane University, New Orleans, LA 70118, (2)Civil & Environmental Engineering, University of Washington, Seattle, WA 98195, (3)CIRES, University of Colorado, Boulder, CO 80309, (4)School of Earth and Ocean Sciences, Cardiff University, Cardiff, United Kingdom, (5)INSTAAR, University of Colorado, Boulder, CO 80303
Landlab is designed for scientists and students to build numerical landscape models of earth surface dynamics. This open-source software is written in the popular and user-friendly Python programming language. The toolkit includes an engine to construct regular and irregular model grids; a library of components that simulate earth surface processes; support functions for tasks such as reading in a DEM and input variables, setting boundary conditions, and plotting and outputting data; and data structures for storing and operating on datasets with spatial and temporal dimensions. With these tools, a Landlab user can build a unique model to explore earth surface dynamics by coupling process components that act on the data associated with a model grid. This approach eliminates the need to recode fundamental model elements each time a new problem is explored and provides the flexibility to include the processes relevant to the problem. The software, tutorials, and documentation are freely available for download (http://landlab.github.io). Landlab models can also be built and run on Hydroshare (www.hydroshare.org), an online collaborative environment for sharing data, models, and code. This software can also be used in geoscience education. Landlab teaching tools illustrate examples of physical processes using numerical models intended for undergraduate and graduate students including for those without computer programming experience (https://github.com/landlab/landlab_teaching_tools). Here we present Landlab, its data capabilities, and demonstrate recent and forthcoming additions to the software.
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|GSA 2018 Pardee: Earth as a Big Data Puzzle: Advancing Information Frontiers in Geoscience||Leslie Hsu||Public & Shareable||Open Access|
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