Package: vegindex
Python tools for generating vegetation index timeseries from PhenoCam images.Free software: MIT licenseIntroductionThe PhenoCam Network is a project designed to study the patterns of
seasonal variation (phenology) of vegetation.  The project website is
athttps://phenocam.nau.edu/.  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 projecthere.
The details of the calculation of GCC are presented in thisjupyter notebook.After the package is installed several python scripts should be
available as commands:generate_roi_timeseriesupdate_roi_timeseriesplot_roistatsgenerate_summary_timeseriesgenerate_roi_ir_timeseriesupdate_roi_ir_timeseriesgenerate_ndvi_timeseriesgenerate_ndvi_summary_timeseriesThese scripts allow you to reproduce the PhenoCam network
“standard timeseries products” from downloaded data.  For a description
of the products see the projectTools Page.Quick InstallationFrom the command line type:pip install vegindexSome of the packages thatvegindexdepends on may not install
automatically (usingpip) since they depend on system libraries.
If the above command does not work you can try:pip install Pillow
pip install vegindexThe latest version of the documentation can be found atreadthedocs.ioChangelog0.10.2 (2022-07-27)
* Fix bug in update_summary_timeseries
* change references to UNH to NAU0.10.0 (2021-11-30)Add 3.9 tox environment to tox.iniAdd IR and camera NDVI processing scriptsDrop support for python20.7.2 (2020-04-12)Add 3.8 tox environment to tox.ini0.7.0 (2020-04-01)Add checks when reading an ROI List CSV file that the
time ranges are in order and don’t overlap0.6.1 (2019-07-15)Update installation doc.Simple test for reading roistats file.0.6.0 (2019-07-12)Add awbflag (auto white-balance) to roistats file0.5.3 (2019-04-03)Update requirements for python 3.7Add prefix to regular expressions0.5.2 (2018-04-09)Really fix bug in plot_roistats when no data are filtered.0.5.1 (2018-04-09)Fix bug in plot_roistats when no data are filtered.Update docs0.5.0 (2017-11-29)Fix header on roistats.csv fileAdd plotting script (matplotlib library is now required)Remove timeout on requests query which was causing
tests to fail.Update usage docs0.4.0 (2017-11-27)Add fallback to local site_info.csv file to get basic site metadataUpdate exception handling (removed bare exceptions)0.3.1 (2017-10-06)Change data product name from _roi_statistics.csv to _roistats.csv0.3.0 (2017-09-12)Added support for .meta filesChange data product name from _timeseries.csv to _roi_statistics.csv0.2.0rc1 (2017-06-14)Added support for python30.1.1rc3 (2017-06-13)First release on PyPI.