/Innovation-Summit-2024__13_Using-AI-to-understand-environmental-change

Primary LanguageJupyter NotebookMIT LicenseMIT

DOI

Environmental & human wildfire AI

Welcome to the Environmental & human wildfire AI repository, an integral part of ESIIL and Earth Lab's Forest Carbon Codefest. This repository is the central hub for our team, encompassing our project overview, team member information, codebase, and more...

#practice edit

Our Project

Our team is hoping to answer the question of how wildfire severity, human, and other environmental factors effect down stream water quality. We hope to use AI to combine many disparate datasets and use those to predict water quality post-fire.

Specifically, we ask: How does wildfire severity alongside human and environmental factors effect downstream water quality?

Specific Goals

  • Publish a paper on our work
  • Practice and utiliza multiple machine learning approaches
  • Find meaningful results

Documentation

Group Members

  • Member 1: Brief description
  • Member 2: Brief description
  • ...
  • [Link to more detailed bios or profiles if available and desired.]

Code Repository Structure

  • Data Processing: Scripts for cleaning, merging, and managing datasets.
  • Analysis Code: Scripts for data analysis, statistical modeling, etc.
  • Visualization: Code for creating figures, charts, and interactive visualizations.

Meeting Notes and Agendas

  • Regular updates to keep all group members informed and engaged with the project's progress and direction.

Contributing to This Repository

  • Contributions from all group members are welcome.
  • Please adhere to these guidelines:
    • Ensure commits have clear and concise messages.
    • Document major changes in the meeting notes.
    • Review and merge changes through pull requests for oversight.

Getting Help

  • If you encounter any issues or have questions, please refer to the ESIIL Support Page or contact the repository maintainers directly.

Customize Your Repository

  • Edit This Readme: Update with information specific to your project.
  • Update Group Member Bios: Add detailed information about each group member's expertise and role.
  • Organize Your Code: Use logical structure and clear naming conventions.
  • Document Your Data: Include a data directory with README files for datasets.
  • Outline Your Methods: Create a METHODS.md file for methodologies and tools.
  • Set Up Project Management: Use 'Issues' and 'Projects' for task tracking.
  • Add a License: Include an appropriate open-source license.
  • Create Contribution Guidelines: Establish a CONTRIBUTING.md file.
  • Review and Merge Workflow: Document your process for reviewing and merging changes.
  • Establish Communication Channels: Set up channels like Slack or Discord for discussions.

Remember, the goal is to make your repository clear, accessible, and useful for all current and future researchers. Happy researching!