Australia’s Environment: routine, comprehensive national reporting

National-scale, comprehensive information on the condition, change and trajectory of our environment is essential for successful environmental management. At national scale, the State of Environment report is produced once every five years, with measurements that are often already some years old. There is an urgent need for a continuous and up-to-date environmental monitoring system that can provide the basis for regular state-of-environment and environmental accounts.

Since 2015, we have been developing a data processing system that integrates and summarises spatial data to produce an annual report. The system provides continuity and regularity in environmental condition data. A backbone to the system is our OzWALD technology, a model-data fusion system that integrates satellite remote sensing into spatial computer models to estimate important components of the water and carbon cycles.

In collaboration with the Terrestrial Ecosystem Research Network, Integrated Marine Observing System, Geoscience Australia, CSIRO and the Australian Bureau of Statistics, we have developed ‘’Australia’s Environment”, an annual briefing on the state of our environment. We provide the information at different formats and levels of detail to make them as relevant, accessible and easily interpreted as possible.

The information can be accessed in digest through the annual Fact Sheet, Briefing Material, and summary article.

For those wishing to use the data in accounting or reporting, we provide Australia’s Environment Explorer, a web atlas that allows you to visualise and investigate environmental changes by region, location or land cover type.




Vegetation structure from laser scanning

Detailed knowledge of the structure of overstorey and understorey vegetation around us has many applications, from nature conservation to forest management and fire risk reduction. Current measurement methods are slow and labour intensive.
Together with CSIRO and the Terrestrial Ecosystem Research Network, we have been developing automated technologies to map vegetation structure from LiDAR – laser scanning data derived from handheld scanners or airborne measurements.
These data have a wide range of applications. They help ecologists understand habitat quality and its suitability for different species. They also help fire managers to assess fire risk and plan hazard reduction burns. The data can also be used to measure biomass and carbon storage in forests.


Soil moisture forecasting at property level

Soil moisture information and forecasts are of great help in dryland farming, to provide early warning of drought, flood and fire risk, and to monitor environmental health, to name a few. Current soil moisture mapping services from models and satellite remote sensing are useful, but are often too coarse or inaccurate or do not provide forecasts.
With support from the Terrestrial Ecosystem Research Network and together with the Bureau of Meteorology, we are developing more accurate soil moisture mapping methods with greater spatial detail at the level of individual properties. We do this by combining different rainfall and soil moisture information sources through data assimilation. Our techniques can operate at different scales, providing forecasts at 10 km resolution for the entire world, down to 25 meters for individual properties.


The Spectroscope

Satellite images in the optical and thermal part of the electromagnetic spectrum are routinely used to infer important information about the land surface, such as vegetation density and health, developing water or heat stress, and flammability. However, there are still some big uncertainties in deriving that information that we are seeking to address.

We developed the Spectroscope together with forest ecology and plant phenomics research groups in ANU’s Research School of Biology (Borevitz’ Plant Genomics for Climate Adaptation lab and Meir Tropical Forest ecosystems group). The Spectroscope is a unique multi-sensor hyperspectral imaging system that scans the entire environment around it simultaneously in optical and thermal wavelengths and using laser scanning. Development was supported by an ANU Major Equipment Grant.

For example, we use it at our outdoor research laboratory in the National Arboretum Canberra. With so many different single-species forests, it serves as a type of ‘colour checker’ for calibration and validation as part of new satellite instruments, missions and data products.

Using the Spectroscope, we get a uniquely detailed understanding of the three-dimensional reflectance and emissions from the three-dimensional vegetation. This helps answer questions around the interaction between the sun, the vegetation and the sensor that will help improve satellite-based measurement methods. This detailed understanding helps us scale new insights about the response of individual leaves, trees and forests to national and global scales with remote sensing.


Automated burn mapping with Digital Earth Australia

Some states have automated or semi-automated methods for rangeland burn extent mapping. However, in forests, burnt area extent and burn severity mapping is currently usually done ad hoc after major events.

Data used in mapping normally include satellite imagery enhanced with on-ground mapping and insights, using mapping techniques that are fine-tuned to suit the characteristics of the event and data. This approach produces appropriate results for the event at hand, but does not produce a longer burn history, which is needed to understand current and future fire risk.

There is a clear need for automated techniques for mapping burnt area extent and severity and fire risk that can be applied anywhere in Australia, including in woody vegetation systems. Continuous mapping of burnt area will also help to inform and attribute land cover change mapping carried out by state and Commonwealth agencies (e.g. NCAS).

ANU and Geoscience Australia together developed an automated workflow to develop a full continental fire history for Australia by processing the enormous volume of Landsat imagery in GA’s Digital Earth Australia data cube. The goal was to map burnt area extent in a manner that is suitable for Australia-wide operationalisation, with a focus on woody vegetation. The method and data were validated against events for which independent spatial data were available.

The algorithm includes a sequence of (i) change detection, (ii) change characterization, (iii) region growing and (iv) attribution steps. You can find the Python code that includes the full workflow in our GitHub repository:


Water license compliance monitoring from space

In New South Wales, monitoring whether water licence holders use river and groundwater in accordance with their licence is a major challenge. Distances are vast, and extraction is often directly from river floodplains during floods, which makes it very hard to keep an eye on compliance.
Together with New South Wales Government, we are developing a satellite-based system to monitor irrigation water use and water extraction. The proposed system will provide guidance to assist compliance officers in targeting properties for inspection, by determining the likelihood that the amount of irrigation on individual properties estimated from satellite observations exceeds extraction limits.





The Australian Flammability Monitoring System

Flammability is strongly determined by the amount of moisture in the dead and living vegetation matter. Fire services and land managers need information of fuel moisture content to undertake hazard reduction burns, to prepare for the fire season, and to anticipate the difficulty of suppressing bushfires throughout the fire season. At present, very simple equations are used to get an approximate estimate of flammability.

We are developing the next generation of fire risk monitoring tools and making them available to land managers and fire services across Australia through our Australian Flammability Monitoring System. To do that, we are using satellite remote sensing to measure the moisture content of living vegetation. In addition, we are developing new methods to estimate moisture in the surface litter layer by understanding how these are linked to moisture in the soil.





Improving spatial water information through data assimilation

Up-to-date spatial water information and forecasts are tremendously valuable for farmers, land and water managers, emergency services, and many other users. For example, to assess crop and pasture growing conditions, soil mechanical properties and fire risk.
Computer models, satellite remote sensing and station measurements all provide valuable information on the water cycle. The best possible up-to-date information and forecasts are derived by combining these data sources through data assimilation: a set of data integration tools that is already used in weather forecasting.
We are working closely with the Bureau of Meteorology to improve the operational water information produced by their Australian Water Resources Assessment (AWRA) system. Together, we are developing practical data assimilation techniques to blend satellite observations, for example relating to soil moisture, total water storage and evapotranspiration, as well as station observations of river flows.

Natural Environment

Environmental model software: W3 and OzWALD

The World-Wide Water model (W3) and its Australian version, OzWALD, are two near-identical models for grid-based estimation of daily water balance dynamics and water-related vegetation dynamics. Both are evolutions of the original AWRA-L model. The example Matlab implementation of the models is freely available for download. You can find the code, relevant literature, and some course material via this link or the download button below.
(Note that this is not the AWRA Community Modelling System (AWRA CMS), which also an evolution of the original AWRA-L model but is maintained by the Bureau of Meteorology and can be found here:




Cosmic rays for fire and flood risk monitoring

The cosmic ray soil moisture probe is a recently invented technology that is set to revolutionise our ability to monitor soil and biomass moisture content.
With support from CSIRO and the Actew/ActewAGL Endowment Fund, we are investigating the potential of this technology for flood and fire risk monitoring in a remote part of the Cotter catchment in Namadgi National Park.
[View latest measurements here or here]