FLiESANN

v1.1.1

Forest Light Environmental Simulator Radiative Transfer Model Artificial Neural Network Implementation in Python For more information about how to use this package see README

Latest version published 27 days ago

License: Apache-2.0

PyPI

GitHub

Package Health Score

63 / 100

security
No known security issues
popularity
Limited
maintenance
Healthy
community
Limited

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Popularity

Limited

GitHub Stars: 2
Forks: 2
Contributors: 2

Direct Usage Popularity

Based on project statistics from the GitHub repository for the PyPI package FLiESANN, we found that it has been starred 2 times.

Security

No known security issues

Security and license risk for latest version

Release Date: Oct 30, 2024
Direct Vulnerabilities: 0
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0
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Indirect Vulnerabilities: 0
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License Risk: 0
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All security vulnerabilities belong to production dependencies of direct and indirect packages.

License

Apache-2.0

Security Policy

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Maintenance

Healthy

Commit Frequency

Open Issues: 0
Open PR: 0
Last Release: 27 days ago
Last Commit: 19 days ago

Further analysis of the maintenance status of FLiESANN based on released PyPI versions cadence, the repository activity, and other data points determined that its maintenance is Healthy.

We found that FLiESANN demonstrates a positive version release cadence with at least one new version released in the past 3 months.

As a healthy sign for on-going project maintenance, we found that the GitHub repository had at least 1 pull request or issue interacted with by the community.

Community

Limited

Readme: Yes
Contributing.md: No
Code of Conduct: No
Contributors: 2
Funding: No

This project has seen only 10 or less contributors.

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Package

Python Versions Compatibility: >=3.11

Age: 2 months
Latest Release: 27 days ago
Dependencies: 7 Direct
Versions: 4
Maintainers: 1
Wheels: OS Independent

Readme

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:

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
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 .

FLiESANN dependencies

geos5fp koppengeiger pandas rasters sentinel-tiles solar-apparent-time sun-angles

FAQs

What is FLiESANN?

Forest Light Environmental Simulator Radiative Transfer Model Artificial Neural Network Implementation in Python. Visit Snyk Advisor to see a full health score report for FLiESANN, including popularity, security, maintenance & community analysis.

Is FLiESANN popular?

We’re still processing downloads data for the python package FLiESANN. Visit the popularity section on Snyk Advisor to see the full popularity analysis.

Is FLiESANN well maintained?

We found that FLiESANN demonstrated a healthy version release cadence and project activity. It has a community of 2 open source contributors collaborating on the project. See the full package health analysis to learn more about the package maintenance status.

Is FLiESANN safe to use?

The python package FLiESANN was scanned for known vulnerabilities and missing license, and no issues were found. Thus the package was deemed as safe to use. See the full health analysis review.

Last updated on 25 November-2024, at 15:44 (UTC).

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