{"id":26668760,"url":"https://github.com/brazil-data-cube/code-gallery","last_synced_at":"2025-04-09T07:08:13.973Z","repository":{"id":40259413,"uuid":"310025209","full_name":"brazil-data-cube/code-gallery","owner":"brazil-data-cube","description":"A gallery of interesting Jupyter Notebooks based on Brazil Data Cube data and technologies","archived":false,"fork":false,"pushed_at":"2025-03-27T14:13:23.000Z","size":106884,"stargazers_count":65,"open_issues_count":3,"forks_count":28,"subscribers_count":7,"default_branch":"master","last_synced_at":"2025-04-02T04:09:36.802Z","etag":null,"topics":["earth-observation","earth-science","geospatial","gis","image-database","python","r"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/brazil-data-cube.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"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}},"created_at":"2020-11-04T14:23:07.000Z","updated_at":"2025-03-31T02:15:43.000Z","dependencies_parsed_at":"2023-09-24T12:11:01.598Z","dependency_job_id":"c2ce9b3e-69b9-4ad8-bea7-c9a409cdb0cd","html_url":"https://github.com/brazil-data-cube/code-gallery","commit_stats":{"total_commits":162,"total_committers":9,"mean_commits":18.0,"dds":0.7592592592592593,"last_synced_commit":"a1354da8355a31a114ac9ef28d70644cd1e74c84"},"previous_names":[],"tags_count":1,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/brazil-data-cube%2Fcode-gallery","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/brazil-data-cube%2Fcode-gallery/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/brazil-data-cube%2Fcode-gallery/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/brazil-data-cube%2Fcode-gallery/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/brazil-data-cube","download_url":"https://codeload.github.com/brazil-data-cube/code-gallery/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247994121,"owners_count":21030050,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","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":["earth-observation","earth-science","geospatial","gis","image-database","python","r"],"created_at":"2025-03-25T21:34:49.881Z","updated_at":"2025-04-09T07:08:13.933Z","avatar_url":"https://github.com/brazil-data-cube.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cimg src=\"./img/logo-bdc.png\" align=\"right\" width=\"64\" /\u003e\n\n# Brazil Data Cube Code Gallery\n\n\n\u003c!-- badges: start --\u003e\n\n[![Software License](https://img.shields.io/badge/license-MIT-green)](https://github.com/brazil-data-cube/code-gallery/blob/master/LICENSE)\n[![Software Life Cycle](https://img.shields.io/badge/lifecycle-maturing-blue.svg)](https://www.tidyverse.org/lifecycle/#maturing)\n[![nbviewer](https://raw.githubusercontent.com/jupyter/design/master/logos/Badges/nbviewer_badge.svg)](https://nbviewer.jupyter.org/github/brazil-data-cube/code-gallery/blob/master/table-of-contents.ipynb)\n[![Join us at Discord](https://img.shields.io/discord/689541907621085198?logo=discord\u0026logoColor=ffffff\u0026color=7389D8)](https://discord.com/channels/689541907621085198#)\n\n\u003c!-- badges: end --\u003e\n\nThis repository contains a gallery of interesting Jupyter Notebooks, R Markdown and scripts based on Brazil Data Cube data and technologies.\n\n\n# Jupyter Notebooks\n\n\n## Data Access through SpatioTemporal Asset Catalog API (STAC)\n\n- Introduction to the SpatioTemporal Asset Catalog. ([Python](https://github.com/brazil-data-cube/code-gallery/blob/master/jupyter/Python/stac/stac-introduction.ipynb), [R](https://github.com/brazil-data-cube/code-gallery/blob/master/jupyter/R/stac/stac-introduction.ipynb))\n\n- Image processing on images obtained through STAC. ([Python](https://github.com/brazil-data-cube/code-gallery/blob/master/jupyter/Python/stac/stac-image-processing.ipynb)).\n\n\n## Web Time Series Service (WTSS)\n\n- Introduction to the Web Time Series Service (WTSS). ([Python](https://github.com/brazil-data-cube/code-gallery/blob/master/jupyter/Python/wtss/wtss-introduction.ipynb), [R](https://github.com/brazil-data-cube/code-gallery/blob/master/jupyter/R/wtss/wtss-introduction.ipynb)).\n\n- Web Time Series Service (WTSS) examples. ([Python](https://github.com/brazil-data-cube/code-gallery/blob/master/jupyter/Python/wtss/wtss-examples.ipynb), [R](https://github.com/brazil-data-cube/code-gallery/blob/master/jupyter/R/wtss/wtss-examples.ipynb)).\n\n- Web Time Series Service 2 - Time series from geometry. ([Python](https://github.com/brazil-data-cube/code-gallery/blob/master/jupyter/Python/wtss/wtss2.ipynb)).\n\n## Web Land Trajectory Service (WLTS)\n\n- Introduction to the Web Land Trajectory Service (WLTS). ([Python](https://github.com/brazil-data-cube/code-gallery/blob/master/jupyter/Python/wlts/wlts-introduction.ipynb), [R](https://github.com/brazil-data-cube/code-gallery/blob/master/jupyter/R/wlts/wlts-introduction.ipynb))\n\n- Web Land Trajectory Service (WLTS) examples. ([Python](https://github.com/brazil-data-cube/code-gallery/blob/master/jupyter/Python/wlts/wlts-example.ipynb)).\n\n## Web Crop Phenology Metrics Service (WCPMS)\n\n- Introduction to the Web Crop Phenology Metrics Service (WCPMS). ([Python](https://github.com/brazil-data-cube/code-gallery/blob/master/jupyter/Python/wcpms/wcpms-introduction.ipynb)).\n\n- Web Crop Phenology Metrics Service (WCPMS) Examples. ([Python](https://github.com/brazil-data-cube/code-gallery/blob/master/jupyter/Python/wcpms/wcpms-example.ipynb)).\n\n\n## Land Cover Classification System Service (LCCS)\n\n* Introduction to the Land Cover Classification System Service (LCCS). ([Python](https://github.com/brazil-data-cube/code-gallery/blob/master/jupyter/Python/lccs/lccs-introduction.ipynb))\n\n## Sample Database (SAMPLE-DB)\n\n* Introduction to the Sample Database (SAMPLE-DB). ([Python](https://github.com/brazil-data-cube/code-gallery/blob/master/jupyter/Python/sample/sample-introduction.ipynb))\n\n## Tile Map Service (BDC-Tiler)\n\n- Introduction to the Tile Map Service (BDC-Tiler). ([Python](https://github.com/brazil-data-cube/code-gallery/blob/master/jupyter/Python/tiler/bdc-tiler_introduction.ipynb))\n\n## Mapping LULC using BDC Data Cubes\n\n- Earth Observation Data Cubes for Brazil: Requirements, Methodology and Products. ([R](https://github.com/brazil-data-cube/code-gallery/tree/master/jupyter/R/bdc-article))\n\n# R Markdown\n\n## Mapping LULC using BDC Data Cubes\n\n- Earth Observation Data Cubes for Brazil: Requirements, Methodology and Products. ([R](https://github.com/brazil-data-cube/code-gallery/tree/master/rmarkdown/R/bdc-article))\n\n# Scripts\n\n**R**\n\n- Earth Observation Data Cubes for Brazil: Requirements, Methodology and Products. ([R](https://github.com/brazil-data-cube/code-gallery/tree/master/scripts/R/bdc-article))\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbrazil-data-cube%2Fcode-gallery","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbrazil-data-cube%2Fcode-gallery","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbrazil-data-cube%2Fcode-gallery/lists"}