Agriculture

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.

 

       

Training

OzEWEX – the Australian Energy and Water Exchange initiative

We host the secretariat of OzEWEX and organise its annual Summer Institute and workshops.

OzeWEX is the Australian Energy and Water Exchange initiative. We are a non-profit volunteer organisation that is part of the international Global and regional Energy and Water Exchanges project (GEWEX). Our goal is to promote and increase measurement, understanding and prediction of the water and energy cycles and related variables over the Australian continent. Examples of important related variables include vegetation dynamics and ecosystem carbon fluxes.

You can find our 2014-2019 Science Plan here.

OZEWEX aims to achieve its goal by promoting and facilitating data collection and sharing; collaborative research activities across organisations, and engagement between researchers, research users and research managers.  Data brokering, collaborative research experiments, and workshops are considered important means.

Visit the OzEWEX website

Workshops

Earth observations for water-related applications

On 28 March 2018, 22 experts from research, government and industry came together in Canberra to discuss the use of Earth observation for a range of water-related applications, including water management, economic production, natural hazards and scientific research.

The event was jointly organised by the Australian National University, the CSIRO, Geoscience Australia, the Bureau of Meteorology, the Terrestrial Ecosystem Research Network (TERN), Earth Observation Australia, and the Australian Energy and Water Exchanges Initiative (OzEWEX)

Hosted by our Centre for Water and Landscape Dynamics, the workshop was prompted by the establishment of the Earth Observation for Government Network and the expected establishment of an Australian Space Agency, as well as upcoming international deliberations by the International Committee on Earth Observation Systems (CEOS) co-chaired by Australia.

A number of themes were explored during the two-day event from which seven recommendations emerged, namely :

  1. That Australian organisations and a future Australian space agency emphasise maintenance of long-term data time series, providing continuity in satellite data archives and derived products, and promoting gapless and seamless consistency between different missions for key hydrological and environmental variables.
     
  2. That Australia’s data custodians undertake steps to optimise the timeliness of data provision, either through reviewing their own processes or through advocacy at international fora.
     
  3. That the Australian space agency formalise Australia’s contribution through cal/val activities, and actively support the maintenance and expansion of this capacity to support continuous satellite data benchmarking.
     
  4. That the National Collaborative Research Infrastructure Strategy (NCRIS) invest in the development of a suite of satellite products along with support for cal/val activities for continuous benchmarking of key water-related variables, and that investment occur to address mismatches between information requirements and current NCRIS foci.
     
  5. That Australia’s strengths in developing pragmatic Earth observation applications and multi-sensor and model-data blending approaches are formally recognised and strengthened and contributed to international efforts where appropriate. Furthermore, that this capacity be supported and contributed at global scale in the context of international efforts.
     
  6. That Geoscience Australia develop analysis-ready data products from Sentinel-1 radar data that can be used to infer inundation dynamics, and that universities develop training programs for the use of radar observations in water-related applications.
     
  7. That Australia advocate for a hyperspectral mission suited to water quality monitoring where opportunities arise.

The full workshop report can be downloaded here.

Data

Global 5-km resolution estimates of secondary evaporation including evaporation

A portion of generated surface and groundwater resources evaporates from wetlands, water bodies and irrigated areas. At the global scale, a lack of detailed water balance studies and direct observations limits our understanding of the magnitude and spatial and temporal distribution of this ‘secondary’ evaporation.

We assimilated satellite-derived information into the landscape hydrological model W3 at 0.05°, or ca. 5km resolution globally. The assimilated data are all derived from MODIS observations, including surface water extent, surface albedo, vegetation cover, leaf area index, canopy conductance and land surface temperature (LST). The information from these products is imparted on the model in a simple but efficient manner, through a combination of direct insertion of the surface water extent, an evaporation flux adjustment based on LST and parameter nudging for the other observations.

Reference

van Dijk, A. I. J. M., Schellekens, J., Yebra, M., Beck, H. E., Renzullo, L. J., Weerts, A., and Donchyts, G.: Global 5 km resolution estimates of secondary evaporation including irrigation through satellite data assimilation, Hydrol. Earth Syst. Sci., 22, 4959-4980, https://doi.org/10.5194/hess-22-4959-2018, 2018.

 

Data access

You can find daily 0.05° estimates of ET and its components for the period 2000-2014 via our OpenDAP THREDDS catalogue:  http://dapds00.nci.org.au/thredds/catalog/ub8/global/W3/v2/0_05d/catalog.html

Available ET variables include:

  • potential evaporation (E0)
  • total ET (ETtot)
  • secondary ET (Elat)
  • transpiration (Et)
  • soil evaporation (Es)
  • water evaporation (Er)

Estimates of other radiation, water and energy balance terms as well as gross primary production are also available from the same location.

Notes:

  • It is recommended to disregard data for 2000 as spin-up artefacts can occur.
  • secondary ET has not been attributed to the evaporation mechanism. A method to do so can be found in the reference paper.
Careers

Full-stack web developers

We are currently looking to strengthen our team with one or more full-stack web developers to develop innovative back end services and effective front end user experiences for environmental information services.

The Centre for Water and Landscape Dynamics is a team of about 20 scientists, technical experts and PhD students based at the Fenner School of Environment & Society of the Australian National University. We develop highly innovative ways of generating and delivering timely information about our environment to people and organisations that have real power to improve our future. For example, to better anticipate bushfire danger, manage our scarce water resources, provide growth forecasts to farmers, and protect our natural environment (see some examples here). Satellites, drones and sensor networks are revolutionising our ability to observe the environment around us, and rapid progress in computing and web technology allows us to turn these measurements into useable information and forecasts.

What you would do

Within our small team, you would be the go-to person to help or lead

  • develop everything between the data server and the user: from designing a useful interface to translating it into code and API calls against the data services.
  • creatively design new and extend existing services.
  • design and create high profile, performing, scalable, available, and stable websites combining front-end web development and server-side web development interfaces tailored to geospatial data, using online mapping tools and modern JavaScript frameworks and libraries.
  • research into new techniques and technologies that may be beneficial, and constantly seek to innovate our current development systems, work practices and processes.
  • work with information users to improve and design new services and user interface
  • work closely with environmental, remote sensing and machine-learning researchers to develop for new opportunities.

What we can offer:

  • ongoing full-time employment. However we are also happy to consider part-time working arrangements or other forms of flexibility to suit your situation and ambitions.
  • many opportunities to get involved in cutting edge research and technology where this appeals to you, for example in big data analytics, high performance computing, machine learning, satellite remote sensing, sensor engineering.
  • a highly competitive salary to reflect your experience, skills and talent.
  • A great working environment. Our small team is co-located on a floor of the Fenner School, the first ACT building with a 6 Star Green rating located on ANU’s wonderful campus. We have our own team meeting area, kitchen and showers, and great access to sporting and outdoor facilities on campus and nearby Black Mountain reserve.

What you would bring:

  • background in web services with an interest in environmental information, or as a trained environmental scientist with some great experience in data analytics and web development.
  • a strong desire to keep learning, researching and innovating in big data and web technologies
  • a few or several years of experience in front-end web design and development. Ideally also some experience with server-side web development using open-source and cloud platforms would be a bonus.
  • hands-on experience using modern JavaScript frameworks and libraries such as Angular and React.
  • experience using online mapping tools, and preferably also with geospatial data, formats and web services.
  • hands-on experience with tools for code management, continuous integration and deployment.
  • great team and communication skills, including the ability to work collaboratively as a member of a small and diverse team, and to plan and prioritise work activities with competing priorities.

How to apply

We have not advertised this position formally, as it would require narrowing down to a particular level of experience or salary level. Instead, we are keen to talk to you directly and explore the options directly with you.

Does this sound like you? Then send Albert van Dijk an email with your CV and a brief statement of what attracts you about this opportunity and any questions you might have. Email me via the link below.

(posted 12 September 2018, open until filled)


Data

Satellite-based river gauging

On this web page you can find background information and data for satellite gauging reaches (SGRs) as published in Van Dijk et al. (2016). You are welcome to use these data in any way you see fit. To cite them do not refer to these web site but to the original paper, which includes this URL:

Van Dijk, A. I. J. M., G. R. Brakenridge, A. J. Kettner, H. E. Beck, T. De Groeve, and J. Schellekens (2016), River gauging at global scale using optical and passive microwave remote sensing, Water Resour. Res., 52, doi:10.1002/2015WR018545. LINK TO ARTICLE  

The easiest way to explore the available SGRs is by downloading the KML-formatted files and exploring them in Google Earth, which also gives you direct access to estimated hydrographs, performance metrics and the location of SGR cells. The KML files are organised and named by upstream catchment area, viz. large (1000-10,000 km2) and largest (>10,000 km2) and by performance, viz. best (Rmax>0.9), good (0-8-0.9), moderate (0.6-0.8) and poor (<0.6) (see paper for further details on the calculation of Rmax). DATA LINK

Alternatively, if you wish to replicate our experiment or undertake your own research using the same data we used, you can download all constructed SGRs including estimated the inundation signal from MODIS or GFDS, as well as the discharge observations used to construct and evaluate the SGRs. The data are formatted in 3 separate, self-described NetCDF files. DATA LINK

Fig7 Examples of good, bad and ugly satellite-gauging reaches (see paper for detailed explanation)



Workshops

ACT environmental sensing activities

This workshop was held 13 February 2015 in Canberra. It was prompted by the recognition that there were various ongoing research activities related to environmental sensing and monitoring in the ACT, including the National Arboretum Phenomic Sensor Array, the ACT grass curing trial,  the Namadgi NP cosmic ray sensor, airborne LiDAR and hyperspectral data collection, terrestrial laser scanning activities, and unmanned aerial vehicle sensing development and trialling. No doubt there are other relevant activities not mentioned here, as well as future activities at different stages of planning. This one day workshop was intended to (1) exchange information on relevant recent, current and near-future R&D activities through brief presentations; (2) find common interests and new opportunities for collaboration; (3) determine priorities in terms of data collection and (web) sharing; and (4) discuss where coordination or expansion would be beneficial and agree how to go about it. You can find the presentations and other material on this legacy page.

Natural Environment

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.



Bushfires

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.