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CSDMS 2025: Exploring Earth's Surface with Models, Data & AI

An Introduction to GRASS GIS and Tangible Landscape

Caitlin Haedrich
North Carolina State University, United States
chaedri@ncsu.edu

Pratikshya Regmi North Carolina State University United States

Abstract
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:

- Setting up GRASS projects and importing data - Visibility analysis - Configuring and running overland flow models - Creating timeseries of inundation flooding

- Building Tangible Landscape activities

Please acknowledge the original contributors when you are using this material. If there are any copyright issues, please let us know (CSDMSweb@colorado.edu) and we will respond as soon as possible.

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Of interest for:

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

River Network Modeling Initiative