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An open-source 3D radiative transfer model for Earth observation applications.
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Eradiate is a 3D radiative transfer model designed to support calibration/validation activities in the field of remote sensing. For that purpose, it aims at achieving an accuracy better than 1% on the simulation of satellite images. This requires aggregating modelling advances done by multiple scientific communities, and Eradiate is therefore designed to facilitate the integration of new models and algorithms. High accuracy also requires embracing the full complexity of the world: Eradiate therefore uses the Monte Carlo ray tracing method and utilizes the Mitsuba 3 rendering system as its radiometric kernel.

Eradiate is also free software. We want to provide the scientific community with comprehensive, high-quality software, designed as a common platform to share modelling advances. Learn more about this project.

Detailed Feature List #

  • Spectral computation
    Solar reflective spectral region Eradiate ships spectral data within from 280 nm to 2400 nm. This range can be extended with additional data (just ask for it!).
    Line-by-line simulation These are true monochromatic simulations (as opposed to narrow band simulations).
    Correlated k-distribution band model (1 nm and 10 nm resolution) This method achieves compromise between performance and accuracy for the simulation of absorption by gases.
  • Atmosphere
    One-dimensional atmospheric profiles (AFGL atmospheric constituent profiles) These profiles are available in CKD mode only (the monochromatic mode uses the simpler U.S. Standard Atmosphere (1976) model).
    Plane-parallel and spherical-shell geometries This allows for more accurate results at high illumination and viewing angles.
  • Surface
    Lambertian and RPV reflection models Model parameters can be varied against the spectral dimensions.
    Detailed surface geometry Add a discrete canopy model (either disk-based abstract models, or more realistic mesh-based models).
    Combine with atmospheric profiles Your discrete canopy can be integrated within a scene featuring a 1D atmosphere model in a fully coupled simulation.
  • Illumination
    Directional illumination model An ideal illumination model with a Delta angular distribution.
    Many irradiance datasets Pick your favourite—or bring your own.
  • Measure
    Top-of-atmosphere radiance and BRF computation An ideal model suitable for satellite data simulation.
    Perspective camera sensor Greatly facilitates scene setup: inspecting the scene is very easy.
    Many instrument spectral response functions Our SRF data is very close to the original data, and we provide advice to further clean up the data, trading off accuracy for performance.
  • Monte Carlo ray tracing
    Mitsuba renderer as radiometric kernel We leverage the advanced Python API of this cutting-edge C++ rendering library.
    State-of-the-art volumetric path tracing algorithm Mitsuba ships a null-collision-based volumetric path tracer which performs well in the cases Eradiate is used for.
  • Traceability
    Documented data and formats We explain where our data comes from and how users can build their own data in a format compatible with Eradiate's input.
    Transparent algorithms Our algorithms are researched and documented, and their implementation is open-source.
    Thorough testing Eradiate is shipped with a large unit testing suite and benchmarked periodically against community-established reference simulation software.
  • Interface
    Comprehensive Python interface Abstractions are derived from computer graphics and Earth observation and are designed to feel natural to EO scientists.
    Designed for interactive usage Jupyter notebooks are now an essential tool in the digital scientific workflow.
    Integration with Python scientific ecosystem The implementation is done using the Scientific Python stack.
    Standard data formats (mostly NetCDF) Eradiate uses predominantly xarray data structures for I/O.