Skip to main content

Forest Light Environmental Simulator Radiative Transfer Model Artificial Neural Network Implementation in Python

Project description

Forest Light Environmental Simulator Radiative Transfer Model Artificial Neural Network 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

Citations

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

Installation

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

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-0.1.0.tar.gz (21.4 MB view details)

Uploaded Source

Built Distribution

FLiESANN-0.1.0-py3-none-any.whl (11.2 kB view details)

Uploaded Python 3

File details

Details for the file fliesann-0.1.0.tar.gz.

File metadata

  • Download URL: fliesann-0.1.0.tar.gz
  • Upload date:
  • Size: 21.4 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.11.10

File hashes

Hashes for fliesann-0.1.0.tar.gz
Algorithm Hash digest
SHA256 17af2718cd7efc64cdc87cf2249db3d0482a4e090c6f34a6259abfe61e1301d4
MD5 92139953cef2a1377a443abc60bca7a2
BLAKE2b-256 c9e9ddf41acd0ea510608fa3e63038542ba5e02e0f60e756d386a84e98f13c2d

See more details on using hashes here.

File details

Details for the file FLiESANN-0.1.0-py3-none-any.whl.

File metadata

  • Download URL: FLiESANN-0.1.0-py3-none-any.whl
  • Upload date:
  • Size: 11.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.11.10

File hashes

Hashes for FLiESANN-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 0477dfc451fb21f71c5b73e1fa7713c89a304f53e51fb91791890ec609400a89
MD5 ee35000b2fa24cc15d4c175f1cd9998f
BLAKE2b-256 60582688ca8b9968b56b4c6dc9ac5a2fbebfa83b09a677098c86916b536b30ca

See more details on using hashes here.

Supported by

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