Australian Mountain Research Facility, Aqueduct Site, Phenology and Phenocam Data Collection, 2021 ongoing 

The record contains a dense time series of phenocam images collected from a fixed camera at the AMRF Aqueduct (PER) site near Perisher in Kosciuszko National Park to enable long‑term monitoring of vegetation phenology and ecosystem condition. These high‑frequency image series provide phenocam‑derived metrics that support analysis of ecological responses to climate variability. When integrated across the Terrestrial Ecosystem Research Network (TERN), they also contribute to the calibration and validation of satellite remote‑sensing data, improving the quality and reliability of continental‑scale environmental monitoring products. Images are captured at half‑hourly intervals during daylight and are made available, together with derived data products such as time series of Green Chromatic Coordinate (GCC), Red Chromatic Coordinate (RCC) and Blue Chromatic Coordinates (BCC), along with statistical summaries for defined vegetation regions of interest (ROIs), on a near real‑time basis. 

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 Australian Mountain Research Facility (AMRF) operates a phenocam at the Aqueduct (PER) site to support long‑term monitoring of vegetation phenology. These observations are integrated within the Australian Mountain Observation Network (AMON), which combines phenocams with a suite of sensor arrays to provide transdisciplinary data on climate impacts on landscapes and ecosystems. Key measurements include carbon and water fluxes, productivity and flammability, supporting emerging systems models and adaptive management. Changes in vegetation structure, species composition and phenology are assessed at the community level on a regular basis. Time series of vegetation phenological observations are collected to understand ecosystems’ annual cycles. 

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.