Metadata-Version: 1.1
Name: vegindex
Version: 0.3.0rc7
Summary: Python tools for generating vegetation index timeseries from PhenoCam images.
Home-page: https://github.com/tmilliman/python-vegindex
Author: Thomas Milliman
Author-email: thomas.milliman@unh.edu
License: MIT
Description: ========
        vegindex
        ========
        
        .. image:: https://img.shields.io/pypi/v/vegindex.svg
               :alt: PyPI Package latest release
               :target: https://pypi.python.org/pypi/vegindex
        
        .. image:: https://img.shields.io/travis/tmilliman/python-vegindex.svg
               :alt: Travis-CI Build Status
               :target: https://travis-ci.org/tmilliman/python-vegindex
        
        .. image:: https://readthedocs.org/projects/python-vegindex/badge/?version=latest
               :target: https://python-vegindex.readthedocs.io/en/latest/?badge=latest
               :alt: Documentation Status
        
        .. image:: https://img.shields.io/pypi/pyversions/vegindex.svg
               :target: https://pypi.python.org/pypi/vegindex
               :alt: Supported versions
        
        Python tools for generating vegetation index timeseries from PhenoCam images.
        
        * Free software: MIT license
        
        Introduction
        ============
        
        The PhenoCam Network is a project designed to study the patterns of
        seasonal variation (phenology) of vegetation.  The project website is
        at `https://phenocam.sr.unh.edu/ <https://phenocam.sr.unh.edu/webcam/>`_.  The
        network consists of many cameras collecting images of various types of
        vegetation.  By analysing the images we can quantify the seasonal
        changes at a particular camera site.
        
        A "vegetation index" refers to a quantity calculated using information
        from various spectral bands of an image of a vegetated area.  The image is
        typically obtained from a remote-sensing instrument on an earth
        orbiting satellite. There are several vegetation index values in
        common usage.  The most widely used are NDVI (Normalized Difference
        Vegetation Index) and EVI (Enhanced Vegetation Index).  For the PhenoCam
        project the Green Chromatic Coordinate or GCC is our standard vegetation
        index.
        
        For the PhenoCam network, the images are obtained from webcams (usually
        installed on towers) looking across a vegetated landscape.  These
        images are typically in JPEG format and have 3-bands (Red, Green, and
        Blue).  For some cameras a separate image dominated by an IR (infrared)
        band is collected.
        
        The algorithms used in in this package have been discussed in numerous
        publications.  You can find a list of publications for the PhenoCam
        Network project `here <https://phenocam.sr.unh.edu/webcam/publications/>`_.
        The details of the calculation of GCC are presented in this
        `python notebook <https://github.com/tmilliman/phenocam_notebooks/blob/master/Standard_Processing_ROI_Stats/PhenoCam_ROI_stats.ipynb>`_
        .
        
        ..
           Richardson, A.D., Hufkens, K., Milliman, T., Aubrecht, D.M.,
           Chen, M., Gray, J.M., Johnston, M.R., Keenan, T.F., Klosterman,
           S.T., Kosmala, M., Melaas, E.K., Friedl, M.A., Frolking, S. 2017.
           Vegetation Phenology from PhenoCam v1.0. ORNL DAAC, Oak Ridge, Tennessee,
           USA. https://doi.org/10.3334/ORNLDAAC/1358
        
        
        After the package is installed two python scripts should be available:
        
        * ``generate_roi_timeseries``
        * ``generate_summary_timeseries``
        
        These scripts allow you to reproduce the PhenoCam network
        "standard timeseries products" from downloaded data.  For a description
        of the products see the project
        `Tools Page <https://phenocam.sr.unh.edu/webcam/tools/>`_.
        
        
        Quick Installation
        ==================
        
        From the command line type:
        
        ::
        
           pip install vegindex
        
        
        Some of the packages that ``vegindex`` depends on may not install
        automatically (using ``pip``) since they depend on system libraries.
        If the above command does not work you can try:
        
        ::
        
           pip install Pillow
           pip install vegindex
        
        
        The latest version of the documentation can be found at
        `readthedocs.io <https://python-vegindex.readthedocs.io/en/latest/>`_
        
        Changelog
        =========
        
        0.3.0 (2017-09-12)
        ------------------
        
        * Added support for .meta files
        * Change data product name from _timeseries.csv to _roi_statistics.csv
        
        0.2.0rc1 (2017-06-14)
        ---------------------
        
        * Added support for python3
        
        
        0.1.1rc3 (2017-06-13)
        ----------------------
        
        * First release on PyPI.
        
Keywords: phenology,phenocam,vegetation,index
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: Unix
Classifier: Operating System :: POSIX
Classifier: Operating System :: Microsoft :: Windows
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
