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This hands-on clinic will introduce partic … This hands-on clinic will introduce participants to GRASS GIS, an open-source geospatial processing engine, and Tangible Landscape, a tangible user interface for GRASS GIS. We will explain and practice GRASS GIS concepts, and work through example Python-based workflows for topics such as hydrology, flood modeling, and viewshed analysis. These workflows will be implemented as a series of computational notebooks. Then, we will show how these workflows can be configured as activities on Tangible Landscape. Using GRASS GIS as a backend, Tangible Landscape is an interactive, open-source platform that integrates physical sand models of landscapes with digital simulations by using a scanner (xBox Kinect) and projector. It allows users to interact in real-time with models by, for example, carving the sand and seeing the resulting water flow pattern. By the end of the clinic, participants will have hands-on experience with: </br></br>- Setting up GRASS projects and importing data </br>- Visibility analysis </br>- Configuring and running overland flow models </br>- Creating timeseries of inundation flooding </br>- Building Tangible Landscape activities
- Building Tangible Landscape activities +
United States +
chaedri@ncsu.edu +
CSDMS 2025: Exploring Earth's Surface with Models, Data & AI +
Caitlin +
Pratikshya +
North Carolina State University +
North Carolina State University +
Haedrich +
Regmi +
Clinic +
North Carolina +
North Carolina +
An Introduction to GRASS GIS and Tangible Landscape +
United States +
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20:10:48, 6 January 2025 +
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22:33:43, 11 June 2025 +
Terrestrial Working Group +, Coastal Working Group +, Marine Working Group +, Education and Knowledge Transfer (EKT) Working Group +, Cyberinformatics and Numerics Working Group +, Hydrology Focus Research Group +, Chesapeake Focus Research Group +, Critical Zone Focus Research Group +, Human Dimensions Focus Research Group +, Geodynamics Focus Research Group +, Ecosystem Dynamics Focus Research Group +, Coastal Vulnerability Initiative +, Continental Margin Initiative +, Artificial Intelligence & Machine Learning Initiative +, Modeling Platform Interoperability Initiative + and River Network Modeling Initiative +
