Gingin Banksia Woodland Phenocam Images and Phenology Data Collection 

Fixed cameras installed at the Gingin Banksia Woodland 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 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 Gingin Banksia Woodland SuperSite was established in 2011 and is located in a natural woodland of high species diversity with an overstorey dominated by Banksia species. For additional site information, see https://www.tern.org.au/tern-observatory/tern-ecosystem-processes/gingin-banksia-woodland-supersite/. Other images collected at the site include photopoints, hemispherical upward photographs, 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. The TERN Gingin Banksia Woodland SuperSite was established by CSIRO and is now managed by Edith Cowan University. The site is co-located with the Land Ecosystem Atmosphere Program (LEAP) – Gingin. It is supported by NCRIS through TERN, Edith Cowan University and the WA Government through the Department of Jobs, Tourism, Science and Innovation. 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.