The TERN-ANU Landscape Data Visualiser

There is an abundance of data on Australia’s natural resources and ecosystems. Often, however, the data are hard to find and cannot easily be explored and analysed by a non-expert user. That is why the ANU Centre for Water and Landscape Dynamics (ANU-WALD) and the Terrestrial Ecosystem Research Network (TERN) have teamed up to develop the TERN-ANU Landscape Data Visualiser, a web atlas of spatial data on our landscapes, soils, ecosystems and water resources available from ANU, TERN and other organisations.

The Visualiser allows you to drill into time series for any location, compare to data sets, and download data for further processing.

You can visualise and analyses data from airborne data collection (e.g. LiDAR and hyperspectral imaging), a range of time series from satellite remote sensing and modelling, data from field surveys (e.g. the TERN Ecosystem Surveillance Plots) and time series from station measurements such as the OzFlux energy, water and carbon flux measurement network.

You can compare time series for any two locations or variables, and easily download the any of the data shown.


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Terms of Use

By using the TERN-ANU Landscape Data Visualiser you are agreeing to be bound by these Terms of Use. These terms may change from time to time.

Copyright: Copyright or other rights in material included within the TERN-ANU Landscape Data Visualiser may belong to Terrestrial Ecosystem Research Network (TERN) at University of Queensland, the Australian National University (ANU) or third parties. Logos are used with consent. Content contained within this portal is accessible under licenses specified by data providers. Please refer to specific licences associated with specific content for relevant terms of use. Requests for further authorisation should be directed via our about page.

Disclaimer: The TERN-ANU Landscape Data Visualiser and its content is provided on an “as is” and “as available” basis. You understand and agree that you use the TERN-ANU Landscape Data Visualiser at your own discretion and risk and that you will be solely responsible for any damage or loss whatsoever that results from such use including use of any data obtained through the TERN-ANU Landscape Data Visualiser. Web links to this site from external, third party websites should not be constructed as implying any relationships with and/or endorsement of the external site or its content by TERN or the ANU. If you have any concerns about the veracity of the data or website content, please inform us via our about page.


Data Documentation

The Landscape Data Visualiser contains a broad array of data from various sources. Links to further documentation are provided below:

Biomass and Carbon


Soils and Landscape

Biodiversity and Habitat



Questions and Feedback

Any trouble using the tools on the Landscape Data Visualiser, difficulty finding the right data, or any other questions?

Please send us an email or contact us in another way

We will be delighted to help you and your feedback can help us improve the usefulness of the TERN-ANU Landscape Data Visualiser.



Mapping Bushfire Hazard and impact

This project uses cutting-edge technology to produce spatial information on fuel condition, fire hazard and impact. Such information can support a wide range of fire risk management and response activities such as hazard reduction burning and pre-positioning firefighting resources and, in the longer term, the new National Fire Danger Rating System (NFDRS). The project is part of the Bushfire & Natural Hazards CRC.

Image result for marta yebra fire

The first phase of this project (2014-2017) involved the parallel investigation of a number of promising data sources and methods that can be categorised as either ‘in-field’ or ‘national-scale’ methods. In-field methods provide detailed information at the plot scale of metres to hectares. They provide more accurate and spatially concentrated measurements but can also be relatively costly – examples investigated previously in this project include on-ground networks of field sensors measuring grass curing or fuel moisture content (FMC), and automated ground-based LiDAR laser scanning for fuel characterisation. National-scale methods are generally derived from already available satellite imagery and other spatial data. Two such methods were successfully developed in this project: the Australian Flammability Monitoring System (AFMS), and the High-resolution Fire Risk and Impact (HiFRI) model-data fusion framework. The former was implemented at national-scale, whereas the latter was tested for a smaller region but can be applied anywhere in Australia.

Generally, information derived from the national-scale methods appear to represent better return on investment and generated greater interest among end users (Yebra et al 2016c). They therefore appear to have greater utilization potential than in-field methods, which require careful consideration of the cost and the representativeness of the sample locations. However, end users did recognise the importance of in-field methods as part of the verification, acceptance and tuning of large-scale methods. Moreover, adoption of some in-field technologies was considered more likely to occur once data acquisition and analysis technologies become cheaper.

Over the second phase (2017-2020), this research project will focus on increasing the understanding, reliability and long- term continuity of the AFMS, and through this, its acceptance and adoption. In addition, a small number of promising, low-cost in-field techniques will continue to be investigated to improve their cost/benefit ratio and utility.

 1. AFMS understanding and reliability. The algorithm we have developed to map FMC for Australia is physically-based using reflectance data from MODIS satellite and radiative transfer models (RTM) Look-up Table inversion techniques. The evaluation of the algorithm for different vegetation types in Australia (Yebra et al. 2016a) has shown that better description of the links between vegetation biophysical and structural properties and leaf reflectance is a critical need, especially for sclerophyll forests. This is because existing RTMs that describe vegetation chemical, structural and optical properties are mainly derived for European vegetation types. Further advancement towards physically-based satellite FMC monitoring methods can be realised through the development of RTMs suited for Australian temperate sclerophyll forest. Field measurement of leaf spectra and corresponding leaf biochemical traits of key species will be essential to that end and will be undertaken as part of the project.

2. AFMS long-term continuity. The current AFMS relies on MODIS instruments on board the Terra and Aqua satellites. Image result for marta yebra fireHowever, the expected lifetime of the Terra and Aqua satellites has already been exceeded, and at some point in the not-too-distant future they will become inoperative. To support a AFMS continuity strategy we will evaluate the feasibility and relative benefits of using alternative satellites, in collaboration with Geoscience Australia and Bureau of Meteorology. The most promising candidate data sources are the geostationary Japanese Himawari-8 satellite, the European Sentinel-2 and the Landsat and VIIRS satellites. Apart from ensuring data continuity and redundancy, the use of these satellites may also create the opportunity to increase the temporal and/or spatial resolution of the AFMS. The benefits of this will also be investigated.

3. Towards comprehensive characterization of flammability. The AFMS provides the first Australia-wide product of flammability from satellite estimates of live FMC (Yebra et al. 2016b). The flammability index was adjusted using a continuous logistic probability model between fire occurrence and live FMC. However, live FMC is only one of the variables that influences fire occurrence, and therefore the importance of other factors (e.g. fire weather, dead FMC, total fine live and dead fuel load, and ignition) should also be considered for a comprehensive characterization of flammability, where possible. For example, weather observations and forecasts are available from Bureau of Meteorology, method of Matthews et al. (2006) can be used to predict dead FMC and Quan et al. (2016) to estimate grassland aboveground biomass. We will quantitatively integrate these additional factors by including them in probabilistic prediction framework. Such an approach will provide a more observation-based and comprehensive assessment of flammability, where current national approaches (e.g. the MacArthur-type methods) are conceptual and focused on meteorological variables.



Forecasting drought impacts months ahead using satellite data

Skilful seasonal water and crop forecasts can do much to help cope with drought and water-related crises. Rapid advances in computing and in satellite remote sensing of precipitation, soil moisture, landscape water storage and vegetation biomass have created the opportunity to produce such forecasts over large areas with fine detail.
With support from the Australian Research Council and in collaboration with Princeton University, Monash University and Deltares, we have been developing technologies to measure and forecast river flows, soil moisture, irrigation water use and vegetation condition with local relevance and global coverage.
For example, we have developed methods to assimilate water storage observations from the GRACE satellite mission and soil moisture observations from passive microwave satellite instruments to achieve remarkable improvements in the estimation of soil moisture at different depths. This has allowed us to predict vegetation response to developing droughts several months in advance. In other examples, we have developed a technology to accurately measure irrigation water use at fine scale with global coverage, and we developed methods to use river water extent remote sensing to monitor river flows.

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.

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:

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.




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]