What question did this study set out to answer?

The aim is to demonstrate GRASS's effectiveness in geomorphometry, especially after landscape changes such as Hurricane Helene.

April 5, 2026Open Access

Geomorphometry with GRASS

Key Points

The aim is to demonstrate GRASS's effectiveness in geomorphometry, especially after landscape changes such as Hurricane Helene.
Analyzed landscape changes post-Hurricane Helene using GRASS.
Developed addon functionalities for DEM data fusion and terrain modeling.
Utilized Python, R, and Jupyter for reproducible workflows.
Demonstrated GRASS's core analytical strengths in geomorphometry.
Highlighted how GRASS supports terrain flow simulations and uncertainty modeling.

Abstract

GRASS is a modern, actively developed, and extensible geospatial processing engine forgeomorphometry. This session draws on post-Hurricane Helene landscape change analysis and ongoing addondevelopment for DEM data fusion, terrain uncertainty modeling, and overland flow simulation to showcasewhat GRASS does well and where it fits in contemporary geomorphometric practice. Beyond its core analyticalcapabilities, GRASS's Python, R, and Jupyter integration make it straightforward to build reproducible, scriptableterrain workflows that move easily from exploration to publication. Join this informal discussion to explore howGRASS serves not only as a research tool but as a community platform where geomorphometric methods canbe developed, shared, and reused through its open addon ecosystem. Google Slides Deck YouTube Recording

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