geomorphometry2025_workshop

Workshop: Propagating DEM Uncertainty to Stream Extraction using GRASS at Geomorphometry 2025

https://github.com/ncsu-geoforall-lab/geomorphometry2025_workshop

Science Score: 75.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
    Found CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 3 DOI reference(s) in README
  • Academic publication links
    Links to: zenodo.org
  • Academic email domains
  • Institutional organization owner
    Organization ncsu-geoforall-lab has institutional domain (geospatial.ncsu.edu)
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (9.8%) to scientific vocabulary
Last synced: 6 months ago · JSON representation ·

Repository

Workshop: Propagating DEM Uncertainty to Stream Extraction using GRASS at Geomorphometry 2025

Basic Info
  • Host: GitHub
  • Owner: ncsu-geoforall-lab
  • License: gpl-3.0
  • Language: Jupyter Notebook
  • Default Branch: main
  • Size: 24.1 MB
Statistics
  • Stars: 0
  • Watchers: 5
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created 10 months ago · Last pushed 7 months ago
Metadata Files
Readme License Citation

README.md

Geomorphometry2025 Workshop

Workshop: Propagating DEM Uncertainty to Stream Extraction using GRASS at Geomorphometry 2025

Open In ColabDOI

Local Setup

The project uses Jupyter Notebook and can be run locally. To do this, you need to have Python installed on your machine. The project is managed with uv to install uv you can use the following command:

macOS or Linux

bash curl -LsSf https://astral.sh/uv/install.sh | sh

wget

bash wget -qO- https://astral.sh/uv/install.sh | sh

Windows

bash powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

You can also install uv though various package manganger by following the instruction found here. Once you have uv installed, you can run the following command to create a virtual environment and install the required packages:

bash uv sync

This will create a virtual environment in the .venv directory and install all the required packages listed in the uv.lock file. Once the installation is complete, you can activate the virtual environment using the following command:

Activate the Virtual Environment

bash source .venv/bin/activate

Make sure your Jupyter Notebooks kernal is set to the virtual environment.

Owner

  • Name: NCSU GeoForAll Lab
  • Login: ncsu-geoforall-lab
  • Kind: organization
  • Email: ncsu_osgeorel@ncsu.edu
  • Location: Raleigh, NC, USA

Open Source Geospatial Foundation Research and Education Laboratory at North Carolina State University

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "White"
  given-names: "Corey"
  orcid: "https://orcid.org/0000-0002-2903-9924"
- family-names: "Haedrich"
  given-names: "Caitlin"
  orcid: "https://orcid.org/0000-0003-4373-5691"
title: "Workshop: Propagating DEM Uncertainty to Stream Extraction using GRASS"
version: 2.0.0
doi: 10.5281/zenodo.15283713
date-released: 2025-04-25
url: "https://github.com/ncsu-geoforall-lab/geomorphometry2025_workshop"
preferred-citation:
  type: conference-paper
  authors:
    - affiliation: North Carolina State University
      family-names: "White"
      given-names: "Corey"
      orcid: "https://orcid.org/0000-0002-2903-9924"
    - affiliation: North Carolina State University
      family-names: "Haedrich"
      given-names: "Caitlin"
      orcid: "https://orcid.org/0000-0003-4373-5691"
  doi: 10.5281/zenodo.15283713
  conference:
    name: "Geomorphometry 2025"
  year: 2025
  place: "Perugia, IT"
  license:
    - cc-by-4.0
  message: If you use this work, please cite it using the metadata from this file.
  title: 'Workshop: Propagating DEM Uncertainty to Stream Extraction using GRASS'
  keywords:
    - geomorphometry
    - streams
    - conditional Gaussian simulation
    - grass
    - DEM

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