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

Water

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.

 

       

Integrating satellite observations into environmental accounts

Environmental accounts can help to measure and protect our natural resources but must be detailed, frequent and comprehensive. Field data alone are not enough for this unless they can be integrated with satellite observations into biophysical models. This project makes use of the latest advances in satellite data analysis and model-data fusion to incorporate three valuable long-term satellite land cover data records into sub-accounts for biomass carbon, water and ecosystem integrity for each year since 1990. We will work with end users to cast these annual accounts into a useful form.

This project was funded through an Australian Research Council Linkage Scheme grant (LP130100789) with support from the Bureau of Meteorology. This project has been completed, and was the foundation for our ongoing work in environmental reporting and accounting through “Australia’s Environment” and other projects.



The Phenomic and Environmental Sensor Array

Based at our ANU research forest in the National Arboretum Canberra, the Phenomic and Environmental Sensor Array collects and integrates data from micrometeorological towers, a distributed wireless environmental sensor network, and overlapping multi-billion pixel time-lapse cameras that cover the research site at 1 cm resolution. The Array provides extremely detailed information from individual trees to the entire forest, every minute and hour. It captures how weather and climate affect growth as the individual trees mature into a closed forest. It will allow us to predict drought effects on growth and development for different eucalyptus species and genotypes, with implications for regenerating forest ecosystems under climate change, nationally and globally. [view latest measurements and images]

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.



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: https://github.com/ANU-WALD/burn-mapping



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: https://github.com/awracms/awra_cms)

 

       

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