https://github.com/pangeo-data/geo-open-hack-2024
Event for geo-coders to explore open tools and approaches for enhancing geospatial analysis
https://github.com/pangeo-data/geo-open-hack-2024
dask hvplot stac xarray
Last synced: 5 months ago
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Event for geo-coders to explore open tools and approaches for enhancing geospatial analysis
- Host: GitHub
- URL: https://github.com/pangeo-data/geo-open-hack-2024
- Owner: pangeo-data
- License: mit
- Created: 2024-05-28T08:40:25.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2024-06-28T07:41:09.000Z (about 2 years ago)
- Last Synced: 2026-01-30T05:39:36.242Z (6 months ago)
- Topics: dask, hvplot, stac, xarray
- Homepage: https://pangeo-data.github.io/geo-open-hack-2024/
- Size: 45.8 MB
- Stars: 3
- Watchers: 10
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Contributing: docs/CONTRIBUTING.md
- License: LICENSE
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README
# geo-open-hack-2024
[](https://github.com/pangeo-data/geo-open-hack-2024/actions/workflows/jupyter-book.yml)
GEO-OPEN-HACK-2024 is a comprehensive and informative event designed for advanced geo-coders to explore various open tools and approaches for upscaling geospatial analysis on open High-Performance Computing (HPC) infrastructure.
The event is organised by the [International Institute of Applied Systems Analysis](https://iiasa.ac.at/) (IIASA) in collaboration with [Spatial Ecology](https://spatial-ecology.net/). This hackathon delves into advanced cutting-edge open techniques, tools, and best practices for efficiently handling and processing vast amounts of geospatial data. Participants will gain hands-on experience in leveraging HPC resources and geo-tools for tasks such as geospatial data preprocessing, spatial modeling and analytics, and visualization.
## Documentation
Documentation can be viewed at [https://pangeo-data.github.io/geo-open-hack-2024/](https://pangeo-data.github.io/geo-open-hack-2024/).
## Hackathon highlights
- **Introduction to Big Geospatial Data**: Understanding the challenges and opportunities presented by large-scale geospatial datasets.
- **High-Performance Computing Basics**: Familiarization with HPC systems, queuing system, parallel processing, and optimization techniques
- **Open Tools and Workflows**: Techniques and tools for geospatial data processing and spatial analytics for applications like remote sensing, GIS, and environmental change monitoring.
- **Modern Geo-analytics**: Exploring emerging trends and technologies in the field, such as machine learning and cloud-based geospatial analytics and visualization.
- **Parallel Computing**: Harnessing the power of parallel and distributed computing for speed and efficiency for geospatial analysis.
- **Performance Tuning**: Strategies to optimize ML models and workflows for HPC environments.
- **Case Studies**: Real-world examples of successful big geospatial data projects on HPC systems.
- **Scalability and Big Data Challenges**: Addressing issues related to data volume, velocity, variety, and veracity in geospatial analysis.
## Clone the github repository
To get a local copy of the `geo-open-hack-2024` repository, you can clone it on your local computer and/or server:
```
git clone https://github.com/pangeo-data/geo-open-hack-2024.git
```
## Install and run `geo-open-hack-2024` jupyter notebooks locally from source
Jupyter notebooks are in the `docs` folder and can be run after installing Python and the required packages listed in the [.binder/environment.yml](https://raw.githubusercontent.com/pangeo-data/geo-open-hack-2024/main/.binder/environment.yml) file.
### Install Python
To install Python, we recommend to install [conda](https://conda.io/projects/conda/en/latest/index.html) or [miniconda](https://docs.anaconda.com/free/miniconda/) and then create a new conda environment using [.binder/environment.yml](https://raw.githubusercontent.com/pangeo-data/geo-open-hack-2024/main/.binder/environment.yml):
```
conda env create -f environment.yml
```
Do not forget to switch to the `geohack` conda environment prior to executing any Jupyter notebooks or programs from the `geo-open-hack-2024` repository.
```
conda activate geohack
```
To deactivate the `geohack` environment:
```
conda deactivate
```
### Start JupyerLab and run the Jupyter notebooks
Once all the required packages are installed, you can start JupyterLab and run the jupyter notebooks from the `docs` folder:
```
jupyter lab
```
## Contributions
To contribute to `geo-open-hack-2024` please refer to [CONTRIBUTING](docs/CONTRIBUTING.md)
## Code of Conduct
Pangeo open source community abide to this [Code of Conduct](https://github.com/pangeo-data/geo-open-hack-2024/tree/main?tab=coc-ov-file#readme)