{"id":48593180,"url":"https://github.com/eoa-team/rtm_inv","last_synced_at":"2026-04-08T20:53:26.858Z","repository":{"id":174779385,"uuid":"518106630","full_name":"EOA-team/rtm_inv","owner":"EOA-team","description":"A Python-backend for radiative transfer model inversion for crop trait retrieval","archived":false,"fork":false,"pushed_at":"2023-11-17T13:59:39.000Z","size":11454,"stargazers_count":5,"open_issues_count":0,"forks_count":1,"subscribers_count":0,"default_branch":"main","last_synced_at":"2026-04-08T20:53:24.271Z","etag":null,"topics":["crops","earth-observation","inversion","radiative-transfer-models","remote-sensing","traits"],"latest_commit_sha":null,"homepage":"","language":"Python","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/EOA-team.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}},"created_at":"2022-07-26T14:59:05.000Z","updated_at":"2024-12-19T11:29:02.000Z","dependencies_parsed_at":null,"dependency_job_id":"ee01a5f6-f14e-45a1-b4c7-7bb42c3e3944","html_url":"https://github.com/EOA-team/rtm_inv","commit_stats":{"total_commits":152,"total_committers":3,"mean_commits":"50.666666666666664","dds":"0.48026315789473684","last_synced_commit":"a3e47f59136079bb4107dbfe7848468cb38cc17b"},"previous_names":["eoa-team/rtm_inv"],"tags_count":1,"template":false,"template_full_name":null,"purl":"pkg:github/EOA-team/rtm_inv","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/EOA-team%2Frtm_inv","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/EOA-team%2Frtm_inv/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/EOA-team%2Frtm_inv/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/EOA-team%2Frtm_inv/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/EOA-team","download_url":"https://codeload.github.com/EOA-team/rtm_inv/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/EOA-team%2Frtm_inv/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":31573788,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-08T14:31:17.711Z","status":"ssl_error","status_checked_at":"2026-04-08T14:31:17.202Z","response_time":54,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.5:443 state=error: 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":["crops","earth-observation","inversion","radiative-transfer-models","remote-sensing","traits"],"created_at":"2026-04-08T20:53:26.182Z","updated_at":"2026-04-08T20:53:26.836Z","avatar_url":"https://github.com/EOA-team.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# rtm_inv - Radiative Transfer Modelling and Inversion in Python\n\nThis repository allows you to run radiative transfer models (RTM) to model the optical properties of vegetation canopies (mainly crops).\n`rtm_inv` is essentially a \"backend\" repository containing\n\n* functions to generate lookup-tables from forward runs of [PROSAIL](http://teledetection.ipgp.jussieu.fr/prosail/) and (experimentally) [SPART](https://doi.org/10.1016/j.rse.2020.111870).\n* functions to \"invert\" optical data by comparing observed with simulated spectra to obtain canopy and leaf traits from optical (satellite) imagery\n\nThe focus of `rtm_inv` currently is on optical satellite missions including [Sentinel2A and B](https://sentinel.esa.int/web/sentinel/missions/sentinel-2), [Landsat 8 and 9](https://landsat.gsfc.nasa.gov/satellites/landsat-9/), and [PlanetScope SuperDove](https://pubs.usgs.gov/of/2021/1030/f/ofr20211030f.pdf).\n\n\u003e Please note:\n    `rtm_inv` does *not* provide any capabilities to query and load satellite data. We recommend to use [EOdal](https:\\\\github.com\\EOA-Team\\eodal) for this purpose.\n\nFurther sensors can be added as, both, PROSAIL and SPART output simulated spectra at a resolution of 1nm in the solar domain (400 to 2500 nm).\n\n## Minimum Usage Example\n\nComing soon ...\n\n## Work built on rtm_inv\n\n`rtm_inv` has been used in the following scientific studies:\n\n| Study | Purpose |  Code |\n| ----- | ------- | ------ |\n| [Graf et al. (2022, IEEE-JSTARS)](https://doi.org/10.1109/JSTARS.2023.3297713) | Radiometric uncertainty propagation. | [Python](https://github.com/EOA-team/s2toarup) |\n| [Graf et al. (2023, RSE)](https://doi.org/10.1016/j.rse.2023.113860) | Crop trait retrieval. | [Python](https://github.com/EOA-team/sentinel2_crop_traits) |\n| [Graf et al. (under review)]() | Crop trait time series reconstruction. | [Python](https://github.com/EOA-team/sentinel2_crop_trait_timeseries) |\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Feoa-team%2Frtm_inv","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Feoa-team%2Frtm_inv","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Feoa-team%2Frtm_inv/lists"}