Description: GRASS GIS (Geographic Resources Analysis Support System) stands at the forefront of open-source geospatial analysis software, offering comprehensive tools for hydrological modeling and environmental analysis. This powerful suite excels in processing raster, vector, and time-series data. At its core, GRASS GIS provides sophisticated modules for essential hydrological tasks, from watershed delineation and stream network extraction to flow accumulation and surface runoff modeling. The software's robust Digital Elevation Model (DEM) processing capabilities enable detailed terrain analysis, crucial for understanding water movement across landscapes. What sets GRASS GIS apart is its flexibility and extensibility. Users can create advanced workflows by coupling hydrological models through BASH and Python scripting, and its plugin architecture is well suited for specialized hydrological analyses. The software's dual interface approach, combining an intuitive GUI with powerful command-line functionality, accommodates both newcomers and experienced users. Our upcoming workshop at Geomorphometry 2025 conference will explore the breadth of GRASS GIS’ capabilities and demonstrate the groundbreaking methodology developed by Amatulli et al. (2022) for creating the Hydrography90m dataset. Participants will gain hands-on experience in using GRASS GIS to generate high-resolution global hydrographic products, and learn techniques that are directly applicable to their own projects.

Workshop material: https://colab.research.google.com/drive/1o_YYiH03MZElLhAvOsAw-fhNZhQU6y6I?usp=sharing

Additional details here (PDF)

Description: GRASS GIS is an open-source geospatial processing engine. With over 400 tools available in the core distribution and an additional 400+ tools available as extensions, GRASS GIS has broad applicability in the Earth Sciences and geomorphometry in particular. In this workshop, we will give an introduction to GRASS GIS and demonstrate some of the geomorphometry tools available in GRASS GIS. Specifically, we will show to compute stream extraction uncertainty using a workflow adapted from Hengl (2009). We will begin by downloading publicly available LiDAR data of the Perugia area using GRASS GIS data fetching tools. Then, we will use R’s kriging functions to create 100 iterations of a DEM. After exploring some of the stream extraction and flow routing methods available in GRASS GIS, we will extract streams from each of the 100 DEMs to compute stream uncertainty. The workshop will be conducted as a series of Jupyter Notebooks that are hosted in Google Colab. By the end of the workshop, participants will have hands on experience with:
- Creating GRASS GIS projects and importing datasets
- Adjusting the computational extent and resolution
- Creating DEMs from point data using a variety of methods implemented in GRASS GIS
- Using the R interface for GRASS GIS and R packages with GRASS GIS data
- Computing Stream Uncertainty
- Developing publication-quality figures with grass.jupyter

Workshop material in github (click on "open in colab" button): https://github.com/ncsu-geoforall-lab/geomorphometry2025_workshop

Additional details here (PDF)