{"id":27314220,"url":"https://github.com/pangeo-data/geo-open-hack-2024","last_synced_at":"2026-02-12T19:02:40.273Z","repository":{"id":241553590,"uuid":"806967782","full_name":"pangeo-data/geo-open-hack-2024","owner":"pangeo-data","description":"Event for geo-coders to explore open tools and approaches for enhancing geospatial analysis","archived":false,"fork":false,"pushed_at":"2024-06-28T07:41:09.000Z","size":48005,"stargazers_count":3,"open_issues_count":0,"forks_count":0,"subscribers_count":10,"default_branch":"main","last_synced_at":"2026-01-30T05:39:36.242Z","etag":null,"topics":["dask","hvplot","stac","xarray"],"latest_commit_sha":null,"homepage":"https://pangeo-data.github.io/geo-open-hack-2024/","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/pangeo-data.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":"docs/CONTRIBUTING.md","funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2024-05-28T08:40:25.000Z","updated_at":"2024-06-28T12:15:19.000Z","dependencies_parsed_at":"2024-05-29T02:18:25.978Z","dependency_job_id":"abcd2187-181a-4b00-82bf-f33e6fb5da11","html_url":"https://github.com/pangeo-data/geo-open-hack-2024","commit_stats":null,"previous_names":["pangeo-data/geo-open-hack-2024"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/pangeo-data/geo-open-hack-2024","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pangeo-data%2Fgeo-open-hack-2024","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pangeo-data%2Fgeo-open-hack-2024/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pangeo-data%2Fgeo-open-hack-2024/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pangeo-data%2Fgeo-open-hack-2024/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/pangeo-data","download_url":"https://codeload.github.com/pangeo-data/geo-open-hack-2024/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pangeo-data%2Fgeo-open-hack-2024/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":29377911,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-02-12T18:59:55.292Z","status":"ssl_error","status_checked_at":"2026-02-12T18:59:44.289Z","response_time":55,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["dask","hvplot","stac","xarray"],"created_at":"2025-04-12T07:39:57.858Z","updated_at":"2026-02-12T19:02:40.257Z","avatar_url":"https://github.com/pangeo-data.png","language":null,"funding_links":[],"categories":[],"sub_categories":[],"readme":"# geo-open-hack-2024\n\n[![geo-open-hack-2024 Jupyter book](https://github.com/pangeo-data/geo-open-hack-2024/actions/workflows/jupyter-book.yml/badge.svg)](https://github.com/pangeo-data/geo-open-hack-2024/actions/workflows/jupyter-book.yml)\n\nGEO-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.\n\nThe 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.\n\n## Documentation\n\nDocumentation can be viewed at [https://pangeo-data.github.io/geo-open-hack-2024/](https://pangeo-data.github.io/geo-open-hack-2024/).\n\n\n## Hackathon highlights\n\n- **Introduction to Big Geospatial Data**: Understanding the challenges and opportunities presented by large-scale geospatial datasets.\n- **High-Performance Computing Basics**: Familiarization with HPC systems, queuing system, parallel processing, and optimization techniques\n- **Open Tools and Workflows**: Techniques and tools for geospatial data processing and spatial analytics for applications like remote sensing, GIS, and environmental change monitoring. \n- **Modern Geo-analytics**: Exploring emerging trends and technologies in the field, such as machine learning and cloud-based geospatial analytics and visualization.\n- **Parallel Computing**: Harnessing the power of parallel and distributed computing for speed and efficiency for geospatial analysis.\n- **Performance Tuning**: Strategies to optimize ML models and workflows for HPC environments.\n- **Case Studies**: Real-world examples of successful big geospatial data projects on HPC systems.\n- **Scalability and Big Data Challenges**: Addressing issues related to data volume, velocity, variety, and veracity in geospatial analysis.\n\n\n## Clone the github repository\n\nTo get a local copy of the `geo-open-hack-2024` repository, you can clone it on your local computer and/or server:\n\n```\ngit clone https://github.com/pangeo-data/geo-open-hack-2024.git\n```\n\n## Install and run `geo-open-hack-2024` jupyter notebooks locally from source\n\nJupyter 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.\n\n### Install Python\n\nTo 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):\n\n```\nconda env create -f environment.yml\n```\n\nDo not forget to switch to the `geohack` conda environment prior to executing any Jupyter notebooks or programs from the `geo-open-hack-2024` repository.\n\n```\nconda activate geohack\n```\n\nTo deactivate the `geohack` environment:\n\n```\nconda deactivate\n```\n\n### Start JupyerLab and run the Jupyter notebooks\n\nOnce all the required packages are installed, you can start JupyterLab and run the jupyter notebooks from the `docs` folder:\n\n```\njupyter lab\n```\n\n## Contributions\n\nTo contribute to `geo-open-hack-2024` please refer to [CONTRIBUTING](docs/CONTRIBUTING.md)\n\n## Code of Conduct\n\nPangeo 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)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpangeo-data%2Fgeo-open-hack-2024","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpangeo-data%2Fgeo-open-hack-2024","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpangeo-data%2Fgeo-open-hack-2024/lists"}