Wombat Stringybark Eucalypt Phenocam Images and Phenology Data Collection 

Fixed cameras installed at the Wombat Stringybark Eucalypt SuperSite provide a time series of fine scale data as a long-term record of vegetation structure and condition. This dense time series of phenocam images provides data for analysis of ecological responses to climate variability, and when consolidated across the entire terrestrial ecosystem research network, supports calibration and validation of satellite-derived remote sensing data, ensuring delivery of higher quality results for broader scale environmental monitoring products.
Images are captured half hourly during daylight hours. Images and data products, including timeseries of the Green Chromatic Coordinate (Gcc) for a region-of-interest (ROI) that delineates an area of specific vegetation type, are made available on an almost real-time basis.
The site was established in 2010 in the Wombat State Forest in Central Victoria. The site is dry eucalypt forest with main species Eucalyptus obliqua, Eucalyptus radiata and Euclayptus rubida. For additional site information, see https://www.tern.org.au/tern-observatory/tern-ecosystem-processes/wombat-stringybark-eucalypt-supersite/.
Other images collected at the site include photopoints, digital cover photography (DCP), and ancillary images of fauna and flora.
 

We at TERN acknowledge the Traditional Owners and Custodians throughout Australia, New Zealand and all nations. We honour their profound connections to land, water, biodiversity and culture and pay our respects to their Elders past, present and emerging. TERN Wombat Stringybark Eucalypt SuperSite is managed by the University of Melbourne. This work was jointly funded by the Terrestrial Ecosystem Research Network (TERN), an Australian Government National Collaborative Research Infrastructure Strategy (NCRIS) project. 

Time series of vegetation phenological observations are collected to understand ecosystems annual cycles. Phenological timeseries can be used for ground-truthing remote sensing data products, for studies of climate change impacts on terrestrial ecosystems, and as a standard for earth system models. 

For generating ROI chromatic indices the python library vegindex (0.7.2) in python is used. For calculating hazeness values the R hazer (1.1.1.) and jpeg (0.1) libraries are used.