Skip to main content

JPL implementation of the MOD16 evapotranspiration algorithm for high resolution instantaneous remote sensing imagery

Project description

JPL implementation of the MOD16 evapotranspiration remote sensing model

CI

The MODIS Global Evapotranspiration Project (MOD16) is a software package developed by a team of researchers from NASA Jet Propulsion Laboratory and the University of Montana. This software is a Python implementation of the MOD16 evapotranspiration algorithm, designed to process high-resolution instantaneous remote sensing imagery.

Unique features of the software include the ability to process remote sensing data with the MOD16 model and partition latent heat flux into canopy transpiration, interception, and soil evaporation. The MOD16 algorithm has been re-implemented to run on instantaneous high spatial resolution remote sensing imagery instead of 8-day MODIS imagery, making the model more accessible for remote sensing researchers.

The software is written entirely in Python and is intended to be distributed using the pip package manager.

The software was developed as part of a research grant by the NASA Research Opportunities in Space and Earth Sciences (ROSES) program. It was designed for use by the Ecosystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) mission as a precursor for the Surface Biology and Geology (SBG) mission. However, it may also be useful for general remote sensing and GIS projects in Python. This package can be utilized for remote sensing research in Jupyter notebooks and deployed for operations in data processing pipelines.

The software is being released according to the SPD-41 open-science requirements of NASA-funded ROSES projects.

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

Kanishka Mallick (he/him)
kaniska.mallick@gmail.com
Luxembourg Institute of Science and Technology

Claire Villanueva-Weeks (she/her)
claire.s.villanueva-weeks@jpl.nasa.gov
NASA Jet Propulsion Laboratory 329G

Installation

pip install MOD16-JPL

Usage

import MOD16_JPL

References

  • Mu, Q., Zhao, M., & Running, S. W. (2011). Improvements to a MODIS global terrestrial evapotranspiration algorithm. Remote Sensing of Environment, 115(8), 1781-1800. doi:10.1016/j.rse.2011.02.019
  • Mu, Q., Heinsch, F. A., Zhao, M., & Running, S. W. (2007). Development of a global evapotranspiration algorithm based on MODIS and global meteorology data. Remote Sensing of Environment, 111(4), 519-536. doi:10.1016/j.rse.2007.04.015

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

pm_jpl-1.10.0.tar.gz (1.0 MB view details)

Uploaded Source

Built Distribution

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

pm_jpl-1.10.0-py3-none-any.whl (1.0 MB view details)

Uploaded Python 3

File details

Details for the file pm_jpl-1.10.0.tar.gz.

File metadata

  • Download URL: pm_jpl-1.10.0.tar.gz
  • Upload date:
  • Size: 1.0 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.9.25

File hashes

Hashes for pm_jpl-1.10.0.tar.gz
Algorithm Hash digest
SHA256 adf562c268f846dbf2191c5e2f702c426b41178587c2894f5c427b92050927f9
MD5 3691f91f2d3d908f8a41947db8b03908
BLAKE2b-256 d8149e75d3a181706aa7203a5a7ca02af55a91a03b1fe8622d10f72043d84b7d

See more details on using hashes here.

File details

Details for the file pm_jpl-1.10.0-py3-none-any.whl.

File metadata

  • Download URL: pm_jpl-1.10.0-py3-none-any.whl
  • Upload date:
  • Size: 1.0 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.9.25

File hashes

Hashes for pm_jpl-1.10.0-py3-none-any.whl
Algorithm Hash digest
SHA256 ed4a00471ec4c88b46526bad60f1b75e38c58f741baff17559b3ab0496eadc7b
MD5 45f47f5812f8aedccc03840feaffa6a9
BLAKE2b-256 efd163a59d2baf9ae3425ec291d4ec0e62680a050fa6a5986b028918aba36aac

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