As a follow-on project from Project 2.07, this new project will use remote sensing to facilitate and “unlock” large area synoptic woody monitoring and reporting.
Land management agencies have to fulfil forest reporting objectives at a state, national and international level. In Victoria, this is achieved every five years using forest inventory plot data that is systematically collected at more than 800 plots across the State (the forest inventory plots, although representative of the different forest types present across Victoria, represent less than 1% of the total forest estate).
To provide wall-to-wall coverage on an annual basis, this project will create a framework that will allow ground plot forest inventory data to be extrapolated across Victoria using Landsat time series disturbance maps and other variables as input. This framework will result in new spatial datasets that can help inform land management needs and forest science.
This project will create a framework that allows the integration of Landsat satellite time-series with Victoria’s forest monitoring and forecasting framework (VFMP). The purpose is to:
- Quantify annual impacts of land management, land use change and natural processes on forest lands
- Establish a Land Use Cover Change (LUCC) monitoring structure.
To achieve these objectives the framework has been divided into three workable areas. These are:
- The creation and attribution of annualised state-wide disturbance maps using the Landsat archive
- The extrapolation of the forestry inventory plot data from the disturbance maps
- Development of a case study for validating the results using a secondary data source.
To achieve the above key deliverables include the annual Landsat TM (mid 1980s to present) 30m resolution products for all wooded areas in Victoria and the calculation of:
- Forest disturbance year and magnitude
- Agents of disturbance: clearcuts, partial cuts, dieback, fire, urbanisation
- Forest growth rate and period.
Other important deliverables include a literature review of pixel based time series approaches, characterisation of errors in dynamic disturbance maps, creation of radiometrically stable, temporally-consistent, cloud-free, seamless Landsat image mosaics for each year in time series, integration of disturbance maps and VFMP, intercomparison of LiDAR-based estimates of AGB for several study areas with dynamic disturbance maps.
This is a three year project that began in November 2015 and is scheduled to be completed by March 2018.
Dr Mariela Soto-Berelov
Project Manager, Research Team
Dr Andrew Haywood
European Commission (European Forestry Institute)
Professor Simon Jones
PhD Student, Research Team