{"id":65571,"url":"https://github.com/beatrizmilz/Environmental-Data-Science","name":"Environmental-Data-Science","description":"A list of books, events, articles, journals, courses, etc related to Environmental Data Science.","projects_count":51,"last_synced_at":"2026-09-04T08:00:29.869Z","repository":{"id":108242938,"uuid":"364571699","full_name":"beatrizmilz/Environmental-Data-Science","owner":"beatrizmilz","description":"A list of books, events, articles, journals, courses, etc related to Environmental Data Science.","archived":false,"fork":false,"pushed_at":"2024-08-22T13:43:17.000Z","size":111,"stargazers_count":47,"open_issues_count":0,"forks_count":3,"subscribers_count":5,"default_branch":"main","last_synced_at":"2026-08-15T15:08:14.475Z","etag":null,"topics":["awesome-list","data-analysis","data-science","datascience","environmental-data","environmental-data-science","environmental-monitoring","environmental-science","environmetrics","machine-learning","r","statistics"],"latest_commit_sha":null,"homepage":"https://beatrizmilz.github.io/Environmental-Data-Science/","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/beatrizmilz.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"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}},"created_at":"2021-05-05T12:38:47.000Z","updated_at":"2026-06-02T09:44:53.000Z","dependencies_parsed_at":"2024-09-05T00:01:06.112Z","dependency_job_id":"18bba33e-9371-4447-8e7a-2eef54f868f0","html_url":"https://github.com/beatrizmilz/Environmental-Data-Science","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/beatrizmilz/Environmental-Data-Science","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/beatrizmilz%2FEnvironmental-Data-Science","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/beatrizmilz%2FEnvironmental-Data-Science/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/beatrizmilz%2FEnvironmental-Data-Science/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/beatrizmilz%2FEnvironmental-Data-Science/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/beatrizmilz","download_url":"https://codeload.github.com/beatrizmilz/Environmental-Data-Science/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/beatrizmilz%2FEnvironmental-Data-Science/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":37020395,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-08-22T15:14:58.755Z","status":"online","status_checked_at":"2026-09-04T02:00:06.169Z","response_time":115,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"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"}},"created_at":"2024-09-05T00:00:20.794Z","updated_at":"2026-09-04T08:00:29.869Z","primary_language":null,"list_of_lists":false,"displayable":true,"categories":["Other","Courses","Organizations","Events","Groups","Books","Blogs and Newsletters","Articles","Special issues","Journals","R Packages","Environmental Data Journalism","Data visualizations","Workshops"],"sub_categories":["Content from courses at the Master of Environmental Data Science (MEDS) - Bren School","Free courses","Past events","About Data Science","About Environmental Data Science","Disciplinas de pós-graduação no Brasil","Academic courses"],"readme":"# Environmental Data Science\nWelcome!\n\nThis repository gathers information about Environmental Data Science, such as events, groups, books, papers, journals, courses, etc.\n\nThe idea is to have a place to find information about environmental data science and share it with others.\n\nFeel free to contribute by suggesting contents (e.g., [open an issue](https://github.com/beatrizmilz/Environmental-Data-Science/issues)) or by making a pull request to [add new content in this file](https://github.com/beatrizmilz/Environmental-Data-Science/blob/main/README.Rmd).\n\nThis repository was created by [Beatriz Milz](https://beamilz.com/) in March 2021.\n\n# Content\n\n## Organizations\n\n- [Openscapes](https://openscapes.org/) \n   - [Open educational resources for Openscapes Champions](https://openscapes.github.io/series/)\n   - [NASA Openscapes](https://nasa-openscapes.github.io/)\n\n## Events\n\n### Future events\n\n- [Environmental Data Science Summit - February 4 - 6, 2025 - Santa Barbara, California](https://www.nceas.ucsb.edu/environmental-data-science-summit)\n\n### Past events\n\n\n- [Environmental Data Science Summit - February 6 - 8, 2024 - Santa Barbara, California](https://www.nceas.ucsb.edu/environmental-data-science-summit)\n\n- [Environmental Data Science Summit - February 7 \u0026 8, 2023 - Santa Barbara, California](https://eds-summit.github.io/)\n\n- [Environmental Data Science Summit - February 8-9, 2022 \\| Santa Barbara, California](https://eds-summit.github.io/)\n\n- [TAI4ES 2022 Summer School](https://www2.cisl.ucar.edu/events/tai4es-2022-summer-school)\n\n## Groups\n\n- [EcoDataScience](https://eco-data-science.github.io/) - [GitHub](https://github.com/eco-data-science), [Slack](https://join.slack.com/t/ecodatascience/shared_invite/enQtNTE1MjAxMTU2NjQwLTZmYjQ5OGIyNjM0YTM4ZDhiMTA2Njc1Mjg2YjFlYWEwZDhlNjJmMTE3MzI2ZmM4ZTJhYTczNmZhYjk3YTI5NjU)\n\n## Books\n\n- [Environmental Data Analysis - An Introduction with Examples in R](https://link.springer.com/book/10.1007/978-3-030-55020-2), by Carsten Dormann\n\n- [Introduction to Environmental Data Science](https://bookdown.org/igisc/EnvDataSci/), by Jerry Davis (SFSU Institute for Geographic Information Science) - \u003chttps://doi.org/10.1201/9781003317821\u003e\n\n- [Environmental Data Analysis - Methods and Applications](https://www.degruyter.com/document/doi/10.1515/9783111012681/html?lang=en), by Zhihua Zhang.\n\n- [Deep Learning for the Earth Sciences: A Comprehensive Approach to Remote Sensing, Climate Science, and Geosciences](https://onlinelibrary.wiley.com/doi/book/10.1002/9781119646181), by Gustau Camps-Valls, Devis Tuia, Xiao Xiang Zhu, Markus Reichstein.\n\n- [Análises Ecológicas no R](https://analises-ecologicas.com/), by FR Da Silva, T Gonçalves-Souza, GB Paterno, DB Provete, MH Vancine (in portuguese)\n\n ## Blogs and Newsletters\n\n - [Dynamic Ecology](https://dynamicecology.wordpress.com/)\n \n - [Theoretical Ecology](https://theoreticalecology.wordpress.com/)\n\n - [Methods in Ecology \u0026 Evolution - Blog](https://methodsblog.com/)\n\n## Articles\n\n### About Data Science\n\n- [50 years of Data Science](https://www.tandfonline.com/doi/full/10.1080/10618600.2017.1384734) - David Donoho\n\n### About Environmental Data Science\n\n- [Data Science of the Natural Environment: A Research Roadmap](https://doi.org/10.3389/fenvs.2019.00121)\n\n- [Data Analytics for Environmental Science and Engineering Research](https://doi.org/10.1021/acs.est.1c01026)\n\n- [Machine Learning and Data Analytics for Environmental Science: A Review, Prospects and Challenges](https://iopscience.iop.org/article/10.1088/1757-899X/955/1/012107/meta)\n\n- [Evolution of machine learning in environmental science — A perspective](https://doi.org/10.1017/eds.2022.2)\n\n- [Why we need to focus on developing ethical, responsible, and trustworthy artificial intelligence approaches for environmental science](https://doi.org/10.1017/eds.2022.5)\n\n- [Machine learning and deep learning—A review for ecologists](https://besjournals.onlinelibrary.wiley.com/doi/10.1111/2041-210X.14061)\n\n- [Welcoming More Participation in Open Data Science for the Oceans](https://doi.org/10.1146/annurev-marine-041723-094741)\n\n## Special issues\n\n- [Environmetrics - Special Issue: Environmental Data Science: Part 1 - February 2023](https://onlinelibrary.wiley.com/toc/1099095x/2023/34/1)\n\n- [Environmetrics - Special Issue: Environmental Data Science: Part 2 - March 2023](https://onlinelibrary.wiley.com/toc/1099095x/2023/34/2)\n\n- [Methods in Ecology and Evolution - Special Feature: Realising the Promise of Large Data and Complex Models](https://besjournals.onlinelibrary.wiley.com/toc/2041210x/2023/14/1)\n\n\n## Journals\n\n- [Environmental Data Science - ISSN 2634-4602](https://www.cambridge.org/core/journals/environmental-data-science)\n\n- [Environmental Science and Technology](https://pubs.acs.org/journal/esthag)\n\n- [Frontiers in Environmental Science](https://www.frontiersin.org/journals/environmental-science)\n\n- [Environmetrics](https://onlinelibrary.wiley.com/toc/1099095x/current)\n\n- [Methods in Ecology and Evolution](https://besjournals.onlinelibrary.wiley.com/journal/2041210X)\n\n\n## R Packages\n\n- [CRAN Task View: Analysis of Ecological and Environmental Data](https://cran.r-project.org/web/views/Environmetrics.html)\n\n## Environmental Data Journalism\n\n- [New Data Tools and Tips for Investigating Climate Change](https://gijn.org/stories/new-data-tools-and-tips-for-investigating-climate-change/)\n\n- [Journalists Toolbox - Environment Resources](https://www.journaliststoolbox.org/2023/05/25/miscellaneous_environment_sites/)\n\n## Data visualizations \n\n- [water data visualizations - USGS](https://labs.waterdata.usgs.gov/visualizations/index.html)\n   - [USGS - Water Data For The Nation Blog](https://waterdata.usgs.gov/blog/)\n\n## Workshops\n\n- [Environmental Data Visualization Literacy Workshop With R](https://www.library.upenn.edu/rdds/work/r-data-visualization-workshop)\n\n## Courses\n\n### Free courses\n\n- [Data Science for Ecologists and Environmental Scientists](https://ourcodingclub.github.io/course)\n\n- [Data Carpentry Ecology Curriculum](https://datacarpentry.org/lessons/#ecology-workshop)\n\n### Disciplinas de pós-graduação no Brasil\n\n- [PRPG CIAMB - UFG](https://ciamb.prpg.ufg.br/) - [Análise de Dados Ambientais](https://files.cercomp.ufg.br/weby/up/104/o/An%C3%A1lise_de_Dados_Ambientais.pdf) - [Material da disciplina](https://lhmet.github.io/adar-ebook/)\n\n### Academic courses\n\n- [University of California, Santa Barbara - Bren School of Environmental Science \u0026 Management - Master of Environmental Data Science](https://bren.ucsb.edu/masters-programs/master-environmental-data-science)\n\n- [Imperial College London - Msc Environmental Data Science and Machine Learning](https://www.imperial.ac.uk/study/pg/earth-science/environmental-data-science-machine-learning/)\n\n- [WEC-33806 - Data Science for Ecology - Wageningen University \u0026 Research](https://wec.wur.nl/dse/) (online course)\n\n### Content from courses at the Master of Environmental Data Science (MEDS) - Bren School\n\n- [Reference](https://my.sa.ucsb.edu/catalog/Current/CollegesDepartments/bren/Index.aspx?DeptTab=Graduate)\n\n- [About MEDS](https://ucsb-meds.github.io/)\n\n- [All courses](https://ucsb-meds.github.io/courses.html)\n\n- [EDS 211 Team Science, Collaborative Analysis and Project\n  Management](https://bbest.github.io/eds211-team/)  \n\n- [EDS 212 Essential Math for Environmental Data\n  Science](https://allisonhorst.github.io/EDS_212_essential-math/)\n\n- [EDS 213 Metadata Standards, Data Modeling and Data\n  Semantics](https://brunj7.github.io/EDS-213-metadata/)\n\n- [EDS 214 Analytical Workflows and Scientific\n  Reproducibility](https://brunj7.github.io/EDS-214-analytical-workflows/)\n\n- [EDS 215 Introduction to Data Storage and\n  Management](https://jamesfrew.github.io/EDS_215_data_management/)\n\n- [EDS 216 Meta-analysis and Systematic\n  Reviews](https://ucsbhydro.github.io/EDS_216_meta-analysis/)\n\n- [EDS 220 Remote Sensing and Environmental\n  Data](https://samanthastevenson.github.io/EDS220_site/)\n\n- [EDS 221 Scientific Programming\n  Essentials](https://allisonhorst.github.io/EDS_221_programming-essentials/)\n\n- [EDS 222 Statistics for Environmental Data\n  Science](https://tcarleton.github.io/EDS-222-stats/)\n\n- [EDS 223 Spatial Analysis for Environmental Data\n  Science](https://jamesfrew.github.io/EDS_223_spatial_analysis/)\n\n- [EDS 230 Modeling Environmental\n  Systems](https://naomitague.github.io/ESM232_course/)\n\n- [EDS 231 Text and Sentiment Analysis for Environmental\n  Problems](https://maro406.github.io/EDS_231-text-sentiment/)\n\n- [EDS 232 Machine Learning in Environmental\n  Science](https://bbest.github.io/eds232-ml/)\n\n- [EDS 240 Data Visualization and\n  Communication](https://bren.ucsb.edu/courses/eds-240)\n\n- [EDS 241 Environmental Policy\n  Evaluation](https://bren.ucsb.edu/courses/eds-241)\n\n- [EDS 242 Ethics and Bias in Environmental Data\n  Science](https://bren.ucsb.edu/courses/eds-242)\n\n## Other\n\n- [Publications from AI2ES](https://www.ai2es.org/publications/)\n\n- [Better Science in Less time](http://ohi-science.org/betterscienceinlesstime/our_story.html)\n\n# Contributing\n\nContributions are welcome! Please submit a pull request or open an issue to discuss a new resource.\n\nWe follow this [code of conduct](https://www.contributor-covenant.org/version/2/1/code_of_conduct/) for contributors.\n\nContributors: Beatriz Milz, Maurício Vancine, Juliano Van Melis\n","projects_url":"https://awesome.ecosyste.ms/api/v1/lists/beatrizmilz%2Fenvironmental-data-science/projects"}