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    "info": {
        "author": "Thomas Milliman",
        "author_email": "thomas.milliman@unh.edu",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 2 - Pre-Alpha",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: MIT License",
            "Operating System :: Microsoft :: Windows",
            "Operating System :: POSIX",
            "Operating System :: Unix",
            "Programming Language :: Python",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7",
            "Topic :: Scientific/Engineering :: Bio-Informatics"
        ],
        "description": "========\nvegindex\n========\n\n.. image:: https://img.shields.io/pypi/v/vegindex.svg\n       :alt: PyPI Package latest release\n       :target: https://pypi.python.org/pypi/vegindex\n\n.. image:: https://img.shields.io/travis/tmilliman/python-vegindex.svg\n       :alt: Travis-CI Build Status\n       :target: https://travis-ci.org/tmilliman/python-vegindex\n\n.. image:: https://readthedocs.org/projects/python-vegindex/badge/?version=latest\n       :target: https://python-vegindex.readthedocs.io/en/latest/?badge=latest\n       :alt: Documentation Status\n\n.. image:: https://img.shields.io/pypi/pyversions/vegindex.svg\n       :target: https://pypi.python.org/pypi/vegindex\n       :alt: Supported versions\n\nPython tools for generating vegetation index timeseries from PhenoCam images.\n\n* Free software: MIT license\n\nIntroduction\n============\n\nThe PhenoCam Network is a project designed to study the patterns of\nseasonal variation (phenology) of vegetation.  The project website is\nat `https://phenocam.sr.unh.edu/ <https://phenocam.sr.unh.edu/webcam/>`_.  The\nnetwork consists of many cameras collecting images of various types of\nvegetation.  By analysing the images we can quantify the seasonal\nchanges at a particular camera site.\n\nA \"vegetation index\" refers to a quantity calculated using information\nfrom various spectral bands of an image of a vegetated area.  The image is\ntypically obtained from a remote-sensing instrument on an earth\norbiting satellite. There are several vegetation index values in\ncommon usage.  The most widely used are NDVI (Normalized Difference\nVegetation Index) and EVI (Enhanced Vegetation Index).  For the PhenoCam\nproject the Green Chromatic Coordinate or GCC is our standard vegetation\nindex.\n\nFor the PhenoCam network, the images are obtained from webcams (usually\ninstalled on towers) looking across a vegetated landscape.  These\nimages are typically in JPEG format and have 3-bands (Red, Green, and\nBlue).  For some cameras a separate image dominated by an IR (infrared)\nband is collected.\n\nThe algorithms used in in this package have been discussed in numerous\npublications.  You can find a list of publications for the PhenoCam\nNetwork project `here <https://phenocam.sr.unh.edu/webcam/publications/>`_.\nThe details of the calculation of GCC are presented in this\n`jupyter notebook <https://nbviewer.jupyter.org/github/tmilliman/phenocam_notebooks/blob/master/Standard_Processing_ROI_Stats/PhenoCam_ROI_stats.ipynb>`_\n.\n\n..\n   Richardson, A.D., Hufkens, K., Milliman, T., Aubrecht, D.M.,\n   Chen, M., Gray, J.M., Johnston, M.R., Keenan, T.F., Klosterman,\n   S.T., Kosmala, M., Melaas, E.K., Friedl, M.A., Frolking, S. 2017.\n   Vegetation Phenology from PhenoCam v1.0. ORNL DAAC, Oak Ridge, Tennessee,\n   USA. https://doi.org/10.3334/ORNLDAAC/1358\n\n\nAfter the package is installed two python scripts should be available:\n\n* ``generate_roi_timeseries``\n* ``generate_summary_timeseries``\n\nThese scripts allow you to reproduce the PhenoCam network\n\"standard timeseries products\" from downloaded data.  For a description\nof the products see the project\n`Tools Page <https://phenocam.sr.unh.edu/webcam/tools/>`_.\n\n\nQuick Installation\n==================\n\nFrom the command line type:\n\n::\n\n   pip install vegindex\n\n\nSome of the packages that ``vegindex`` depends on may not install\nautomatically (using ``pip``) since they depend on system libraries.\nIf the above command does not work you can try:\n\n::\n\n   pip install Pillow\n   pip install vegindex\n\n\nThe latest version of the documentation can be found at\n`readthedocs.io <https://python-vegindex.readthedocs.io/en/latest/>`_\n\nChangelog\n=========\n\n0.6.1 (2019-07-15)\n------------------\n* Update installation doc.\n* Simple test for reading roistats file.\n\n0.6.0 (2019-07-12)\n------------------\n* Add awbflag (auto white-balance) to roistats file\n\n0.5.3 (2019-04-03)\n------------------\n* Update requirements for python 3.7\n* Add prefix to regular expressions\n\n0.5.2 (2018-04-09)\n------------------\n* Really fix bug in plot_roistats when no data are filtered.\n\n0.5.1 (2018-04-09)\n------------------\n* Fix bug in plot_roistats when no data are filtered.\n* Update docs\n\n0.5.0 (2017-11-29)\n--------------------\n* Fix header on roistats.csv file\n* Add plotting script (matplotlib library is now required)\n* Remove timeout on requests query which was causing\n  tests to fail.\n* Update usage docs\n\n0.4.0 (2017-11-27)\n--------------------\n* Add fallback to local site_info.csv file to get basic site metadata\n* Update exception handling (removed bare exceptions)\n\n0.3.1 (2017-10-06)\n---------------------\n* Change data product name from _roi_statistics.csv to _roistats.csv\n\n0.3.0 (2017-09-12)\n---------------------\n* Added support for .meta files\n* Change data product name from _timeseries.csv to _roi_statistics.csv\n\n0.2.0rc1 (2017-06-14)\n---------------------\n* Added support for python3\n\n0.1.1rc3 (2017-06-13)\n----------------------\n* First release on PyPI.\n\n\n",
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        "keywords": "phenology,phenocam,vegetation,index",
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