The demand for being able to predict the canopy cover of sites where infrastructure is being developed, of local government areas with either strategic canopy cover targets or prescribed tree planting rates, and of newly planted green infrastructure has increased dramatically over the last 2 years. In Victoria, canopy replacement requirements on contractors supplying major infrastructure projects such as the North East Link have moved from the previous “2 for one” tree replacement to the restoration of canopy cover over a time frame. Across Australia, LGA’s are setting strategic canopy targets based on aspirational objectives without necessarily being well informed on the quantum of key drivers such as change (trend) in private landholder canopy areas (typically declining due to developmental pressure), the effect of Council activities such as planting rates and socio-ecological factors such as planting mortality impacted by management practices and increasingly extreme weather events.

Traditional estimation of future canopy has typically rested with ad hoc work by landscape architects, consultants and the like. Work using i-Tree Forecast has been published in the northern hemisphere but, to date, has not found favour here. Tools utilizing insights and experience from local experts do not appear to be available. Further, benchmarking canopy cover starting points, changes and trends has only become practical with reasonable accuracy with the advent of remote sensing and AI technologies coupled with GIS tools and cadastral data pertaining to land ownership which enable essential data determination at the scale and stakeholder relevance required.

Working with both major infrastructure partners and local government authorities and their tree experts, models have been developed to enable the scenario testing of major input variables – planting numbers, species growth rates, mortality rates, per-landowner category canopy cover growth and decline, and the number of forecast years. Simple extrapolation of the outputs of the model can then be used for asset management, budget planning and community engagement purposes.

In showcasing the model and using it to test the assumptions required to deliver specific canopy targets, alignment in canopy strategy and target setting was achieved in both commercial and local government settings. Commercially, the benefit of canopy preservation versus new plantings and ongoing management was better quantified and demonstrated, helping to support the preferred strategy of project design to minimise tree removals. In the local government setting, existing planting rates and associated budgetary and human resources were assessed against those required to deliver various, nominated canopy cover targets demonstrating the practical limitations of aspirational versus pragmatic ones