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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 and (experimentally) SPART.
  • 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, Landsat 8 and 9, and PlanetScope SuperDove.

Please note: rtm_inv does not provide any capabilities to query and load satellite data. We recommend to use 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) Radiometric uncertainty propagation. Python
Graf et al. (2023, RSE) Crop trait retrieval. Python
Graf et al. (under review) Crop trait time series reconstruction. Python