https://github.com/eoa-team/rtm_inv
A Python-backend for radiative transfer model inversion for crop trait retrieval
https://github.com/eoa-team/rtm_inv
crops earth-observation inversion radiative-transfer-models remote-sensing traits
Last synced: 2 months ago
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A Python-backend for radiative transfer model inversion for crop trait retrieval
- Host: GitHub
- URL: https://github.com/eoa-team/rtm_inv
- Owner: EOA-team
- Created: 2022-07-26T14:59:05.000Z (almost 4 years ago)
- Default Branch: main
- Last Pushed: 2023-11-17T13:59:39.000Z (over 2 years ago)
- Last Synced: 2026-04-08T20:53:24.271Z (2 months ago)
- Topics: crops, earth-observation, inversion, radiative-transfer-models, remote-sensing, traits
- Language: Python
- Homepage:
- Size: 10.9 MB
- Stars: 5
- Watchers: 0
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# rtm_inv - Radiative Transfer Modelling and Inversion in Python
This repository allows you to run radiative transfer models (RTM) to model the optical properties of vegetation canopies (mainly crops).
`rtm_inv` is essentially a "backend" repository containing
* 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).
* functions to "invert" optical data by comparing observed with simulated spectra to obtain canopy and leaf traits from optical (satellite) imagery
The 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).
> Please note:
`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.
Further 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).
## Minimum Usage Example
Coming soon ...
## Work built on rtm_inv
`rtm_inv` has been used in the following scientific studies:
| Study | Purpose | Code |
| ----- | ------- | ------ |
| [Graf et al. (2022, IEEE-JSTARS)](https://doi.org/10.1109/JSTARS.2023.3297713) | Radiometric uncertainty propagation. | [Python](https://github.com/EOA-team/s2toarup) |
| [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) |
| [Graf et al. (under review)]() | Crop trait time series reconstruction. | [Python](https://github.com/EOA-team/sentinel2_crop_trait_timeseries) |