Skip to main content

Forest Light Environmental Simulator (FLiES) Radiative Transfer Model Artificial Neural Network (ANN) Implementation in Python

Project description

Forest Light Environmental Simulator (FLiES) Radiative Transfer Model Artificial Neural Network (ANN) Implementation in Python

This package is an artificial neural network emulator for the Forest Light Environmental Simulator (FLiES) model using keras and tensorflow in Python. This model is used to estimate solar radiation for the Breathing Earth Systems Simulator (BESS) model used to estimate evapotranspiration (ET) and gross primary productivity (GPP) for the ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) and Surface Biology and Geology (SBG) thermal remote sensing missions.

Contributors

Gregory H. Halverson (they/them)
gregory.h.halverson@jpl.nasa.gov
Lead developer
NASA Jet Propulsion Laboratory 329G

Hideki Kobayashi (he/him)
FLiES algorithm inventor
Japan Agency for Marine-Earth Science and Technology

Installation

git clone git@github.com:JPL-Evapotranspiration-Algorithms/FLiESANN.git
cd FLiES
mamba install pykdtree
pip install .

References

If you use the Forest Light Environmental Simulator (FLiES) model in your work, please cite the following references:

  1. Kobayashi, H., & Iwabuchi, H. (2008). A coupled 1-D atmospheric and 3-D canopy radiative transfer model for canopy reflectance, light environment, and photosynthesis simulation in a heterogeneous landscape. Remote Sensing of Environment, 112(1), 173-185.
    https://doi.org/10.1016/j.rse.2007.04.010

  2. Kobayashi, H., Ryu, Y., & Baldocchi, D. D. (2012). A framework for estimating vertical profiles of canopy reflectance, light environment, and photosynthesis in discontinuous canopies. Agricultural and Forest Meteorology, 150(5), 601-619.
    https://doi.org/10.1016/j.agrformet.2010.12.001

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

fliesann-1.4.1.tar.gz (8.5 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

fliesann-1.4.1-py3-none-any.whl (113.3 kB view details)

Uploaded Python 3

File details

Details for the file fliesann-1.4.1.tar.gz.

File metadata

  • Download URL: fliesann-1.4.1.tar.gz
  • Upload date:
  • Size: 8.5 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.9.21

File hashes

Hashes for fliesann-1.4.1.tar.gz
Algorithm Hash digest
SHA256 96f328e6040b873821a87f8e71cc386e623b498c11dfe8d391c7177910e0c6e0
MD5 2bddcc7bd1720678f1b26fb19aff6b3e
BLAKE2b-256 e1aea4b5cc31492f2fc915b9923f4378b6ea9b8b4c9207cd9542be7235890308

See more details on using hashes here.

File details

Details for the file fliesann-1.4.1-py3-none-any.whl.

File metadata

  • Download URL: fliesann-1.4.1-py3-none-any.whl
  • Upload date:
  • Size: 113.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.9.21

File hashes

Hashes for fliesann-1.4.1-py3-none-any.whl
Algorithm Hash digest
SHA256 7594d95a6b37a8766ad785aaf9979bb3816950d38870b877cf6ae6601e661592
MD5 e2e523774f6c347bd13ed7ae16dab28c
BLAKE2b-256 9ebe084f072dafb28c0929f51726f1f3a9b9c0c7ce5b7fd0cd825168a48033e0

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page