Remote Australia Online

Using Advanced Very High Resolution Radiometer data spanning 1981–2006 and calibrated for long-term analyses of vegetation dynamics, we examine whether vegetation cover has increased across Australia and whether there has been a differential response of vegetation functional types in response to changes in climatic growing conditions. Trends in vegetation cover are interpreted within Budyko's energy – water limitation framework. Results from an Australia-wide analysis indicate that vegetation cover (as described by the fraction of Photosynthetically Active Radiation absorbed by vegetation; fPAR) has increased, on average, by 0.0007 per year – an increase of 8% over the 26 years. The majority of this change is due to a 0.0010 per year increase in persistent fPAR (representing nondeciduous perennial vegetation types; up 21%). In contrast, recurrent fPAR (representing deciduous, annual and ephemeral vegetation types) decreased, on average, by 0.0003 per year (down 7%), the trends of which are highly seasonal. Over the same period, Australian average annual precipitation increased by 1.3 mm yr−2 (up 7%). A site-based analysis using 90 long-term meteorological stations with minimal localized land-cover changes showed that energy-limited sites where total fPAR increased generally experienced decreases in precipitation, and water-limited sites that experienced decreases in cover were almost always associated with decreases in precipitation. Interestingly, where vegetation cover increased at water-limited sites, precipitation trends were variable indicating that this is not the only factor driving vegetation response. As Australia is a generally highly water-limited environment, these findings indicate that the effective availability of water to plants has increased on average over the study period. Results also show that persistent vegetation types have benefited more than recurrent types from recent changes in growing conditions. Regardless of what has been driving these changes, the overall response of vegetation over the past 2–3 decades has resulted in an observable greening of the driest inhabited continent on Earth.

This paper describes an innovative method, commonly referred to as ‘spider mapping’, that allows pasture biomass and related data to be collected over large areas in a timely and efficient manner. Spider mapping was developed initially to collect data to allow calibration and validation of a spatial and temporal pasture growth model operating across Queensland on a 5 km grid basis. Two field officers made over 220 000 estimates and collected about 1300 samples of pasture biomass between January 1994 and August 1995. A number of selected biomass samples were analysed for nitrogen, phosphorus and carbon content. In addition, data were also collected on foliage projective cover and tree basal area for a range of woodland communities and both variables compared with mean long-term Normalised Difference Vegetation Index values derived from a time series of National Oceanographic and Atmospheric Administration satellite imagery. Both variables were strongly related to the satellite data with overstorey foliage projective cover having the strongest non-linear correlation (R2 = 0.91). The method described here is currently being used in related work in the rangelands of New South Wales, South Australia, Western Australia and the Northern Territory.

Vegetation indices are widely used for assessing and monitoring ecological variables such as vegetation cover, above-ground biomass and leaf area index. This study reviewed and evaluated different groups of vegetation indices for estimating vegetation cover in southern rangelands in South Australia. Slope-based, distance-based, orthogonal transformation and plant-water sensitive vegetation indices were calculated from Landsat thematic mapper (TM) image data and compared with vegetation cover estimates at monitoring points made during Pastoral Lease assessments. Relationships between various vegetation indices and vegetation cover were compared using simple linear regression at two different scales: within two contrasting land systems and across broader regional landscapes. Of the vegetation indices evaluated, stress related vegetation indices using red, near-infrared and mid-infrared TM bands consistently showed significant relationships with vegetation cover at both land system and landscape scales. Estimation of vegetation cover was more accurate within land systems than across broader regions. Total perennial and ephemeral plant cover was best predicted within land systems, while combined vegetation, plant litter and soil cryptogam crust cover was best predicted at landscape scale. These results provide a strong foundation for use of vegetation indices as an adjunct to field methods for assessing vegetation cover in southern Australia.

Grazing is a major land use in Australia’s rangelands. The ‘safe’ livestock carrying capacity (LCC) required to maintain resource condition is strongly dependent on climate. We reviewed: the approaches for quantifying LCC; current trends in climate and their effect on components of the grazing system; implications of the ‘best estimates’ of climate change projections for LCC; the agreement and disagreement between the current trends and projections; and the adequacy of current models of forage production in simulating the impact of climate change. We report the results of a sensitivity study of climate change impacts on forage production across the rangelands, and we discuss the more general issues facing grazing enterprises associated with climate change, such as ‘known uncertainties’ and adaptation responses (e.g. use of climate risk assessment). We found that the method of quantifying LCC from a combination of estimates (simulations) of long-term (>30 years) forage production and successful grazier experience has been well tested across northern Australian rangelands with different climatic regions. This methodology provides a sound base for the assessment of climate change impacts, even though there are many identified gaps in knowledge. The evaluation of current trends indicated substantial differences in the trends of annual rainfall (and simulated forage production) across Australian rangelands with general increases in most of western Australian rangelands (including northern regions of the Northern Territory) and decreases in eastern Australian rangelands and south-western Western Australia. Some of the projected changes in rainfall and temperature appear small compared with year-to-year variability. Nevertheless, the impacts on rangeland production systems are expected to be important in terms of required managerial and enterprise adaptations. Some important aspects of climate systems science remain unresolved, and we suggest that a risk-averse approach to rangeland management, based on the ‘best estimate’ projections, in combination with appropriate responses to short-term (1–5 years) climate variability, would reduce the risk of resource degradation. Climate change projections – including changes in rainfall, temperature, carbon dioxide and other climatic variables – if realised, are likely to affect forage and animal production, and ecosystem functioning. The major known uncertainties in quantifying climate change impacts are: (i) carbon dioxide effects on forage production, quality, nutrient cycling and competition between life forms (e.g. grass, shrubs and trees); and (ii) the future role of woody plants including effects of fire, climatic extremes and management for carbon storage. In a simple example of simulating climate change impacts on forage production, we found that increased temperature (3°C) was likely to result in a decrease in forage production for most rangeland locations (e.g. –21% calculated as an unweighted average across 90 locations). The increase in temperature exacerbated or reduced the effects of a 10% decrease/increase in rainfall respectively (–33% or –9%). Estimates of the beneficial effects of increased CO2 (from 350 to 650 ppm) on forage production and water use efficiency indicated enhanced forage production (+26%). The increase was approximately equivalent to the decline in forage production associated with a 3°C temperature increase. The large magnitude of these opposing effects emphasised the importance of the uncertainties in quantifying the impacts of these components of climate change. We anticipate decreases in LCC given that the ‘best estimate’ of climate change across the rangelands is for a decline (or little change) in rainfall and an increase in temperature. As a consequence, we suggest that public policy have regard for: the implications for livestock enterprises, regional communities, potential resource damage, animal welfare and human distress. However, the capability to quantify these warnings is yet to be developed and this important task remains as a challenge for rangeland and climate systems science.

Changes in vegetation cover over time in arid rangelands can be used to monitor land condition and to identify processes of land degradation. This article describes how a cover index can be derived from Landsat MSS data and how the index can be standardized to remove atmospheric effects and differences in sensor calibration between spacecraft. Tests carried out on 1-m-diameter radiometer targets show that the best separation between soil, rock, or stone and vegetated surfaces occurs in the Band 4–Band 5 data space. This separation includes both dry and green vegetation whereas in the commonly used Band 5–Band 7 data space the separation is much less clear if the vegetation is not green. We have therefore developed a vegetation cover index in the Band 4–Band 5 data space. This index, known as PD54, has a similar form to the perpendicular vegetation index of Richardson and Weigand (1977). It is calculated by identifying a soil line or, more correctly, an upper soil band limit, and then determining the perpendicular distance of each pixel from that line. The perpendicular distance is scaled using distances calculated for points or pixels which have 100% cover. In the normal mix of rangeland vegetation at the pixel scale, these reference pixels occupy a very limited area of the Band 4–Band 5 data space and can be treated as a point or as a line of limited length and with a slope similar to that of the soil line. PD54 performs better than several other indices when tested at the Landsat MSS pixel scale using aircraft-mounted radiometer data. It is also less subject to systematic errors when shifting from one vegetation type to another. The principal difficulty in using PD54 as a cover index arises because there is no single soil line. Instead, the position of that line varies with both Munsell soil hue and chroma. Attempts to standardize PD54 for Landsats 1, 2, 4, and 5 showed that the commonly used approach of converting data to exoatmospheric reflectance based on published radiometer gains and offsets does not work. Furthermore, the dark pixel subtraction method of haze correction does not remove all atmospheric effects. It is, however, possible to remove the effects of differences between the different Landsat MSSs and inadequate haze correction by identifying the extremes of the Band 4–Band 5 data space on a particular scene and using them to scale PD54. Once this is done, PD54 gives substantially better estimates of cover from MSS data than Band 5 values which have supposedly been radiometrically standardised.

Long-term vegetation dynamics associated with climatic changes can be assessed using Advanced Very High Resolution Radiometer (AVHRR) red and near-infrared reflectance data provided that the data have been processed to remove the effects of non-target signal variability, such as atmospheric and sensor calibration effects. Here we present a new method that performs a relative calibration of reflectance data to produce consistent long-term vegetation information. It is based on a simple biological framework that assumes that the position of the vegetation cover triangle is invariant in reflectance space. This assumption is in fact an intrinsic assumption behind the commonly used Normalised Difference Vegetation Index (NDVI) and is violated when the NDVI is calculated from inadequately corrected reflectance data. In this new method, any temporal variability in the position of the cover triangle is removed by geometrically transforming the observed reflectance data such that two features of the triangle—the soil line and the dark point—are stationary in reflectance space. The fraction of Photosynthetically Active Radiation absorbed by vegetation (fPAR; 0.0–0.95) is then calculated, via the NDVI, from calibrated reflectances. This method was tested using two distinct, monthly AVHRR products for Australia: (i) the coarse-resolution, fully calibrated, partially atmospherically corrected PAL data (1981–1994); and (ii) the fine-resolution, fully calibrated, non-atmospherically corrected HRPT data (1992–2004). Results show that, in the 20-month period when the two datasets overlap (1992–1994), the Australia-wide, root mean square difference between the two datasets improved from 0.098 to 0.027 fPAR units. The calibrations have produced two approximately equivalent datasets that can be combined as a single input into time-series analyses. The application of this method is limited to areas that have a wide-enough variety of land-cover types so that the soil line and dark point are evident in the cover triangle in every image of the time-series. Another limitation is that the methodology performs only bulk, relative calibrations and does not remove the absolute effects of observation uncertainties. The simplicity of the method means that the calibration procedure can be easily incorporated into near-real-time operational remote-sensing environments. Vegetation information produced using this invariant-cover-triangle method is expected to be well suited to the analysis of long-term vegetation dynamics and change.

Pasture management in the pastoral zone is crucial to long-term sustainability of woolgrowing enterprises, but the large size of properties and scarcity of labour make it difficult for pastoralists to know the condition of the pasture base across the whole property. As well, like all agricultural producers, pastoralists are under increasing scrutiny to ‘prove’ whether they are managing their natural resources well. The ability of satellite imagery to provide frequent and whole-of-property information that can be easily archived over many years means that satellites are potentially useful for pastoral management. However, to date, impediments in processing and interpreting satellite imagery have rendered it beyond the reach of most pastoralists. Gary Bastin from CSIRO Sustainable Ecosystems in Alice Springs, led a team who worked with eight pastoral families in northern South Australia to devise a prototype for presenting satellite information in a useful format. Three products in particular seem to show the most potential, namely: (a) maps of cover at various times for the property (or particular paddocks) scaled between the historically lowest and highest values of cover for the area of interest; (b) maps of vegetation cover summarised as time traces of average cover across land types within paddocks; and (c) cover values showing changes in categories (such as low, medium, high) over time hence allowing woolgrowers to manage against preset cover targets.

Woody weed infestations that cover large open grassland areas are difficult to control and their management is extremely costly and time consuming. The aim of this project was to develop and test Unmanned Aerial Vehicle (UAV) surveillance systems which can detect woody weed infestations and provide the information needed for woody weed control and eradication. The project focussed on the sensor and data fusion algorithms needed for weed detection and the precise positioning of a dispenser for the distribution of herbicide at the infestation point. Two types of UAV systems were used in the project, a fixed-wing UAV (FUAV) for broad acre surveillance, and a rotary-wing UAV (RUAV) for precision targeting around the weed. Results of the project demonstrated the ability to build high-resolution maps over farmland areas and classify different species of weeds within the maps using vision data collected from the UAV, and the ability to hover of specific geo-referenced locations of where weeds were detected for the distribution of the herbicide.

This paper describes the development of a regression model for predicting foliage projective cover (FPC) using an extensive set of over 2000 field observations for Queensland, Australia. The model includes Landsat TM and ETM+ imagery and a climatological ancillary variable, vapour pressure deficit. The resulting model was validated using independent site data and preliminary validation against FPC estimates from airborne laser scanner data is presented. Results suggest the model is robust and performing well over a range of soil types and vegetation communities. This regression-based methodology is currently included in the process of monitoring annual woody vegetation change over Queensland and will form the basis of new products for monitoring longer term trends in FPC.

Advanced Remote Livestock Management

This report provides a comparative overview of software mapping packages for use by primary producers. It examines the range of software products available to assist landholders and natural resource managers. It suggests a decision matrix for primary producers to assess their needs, and the ability of mapping packages to meet their needs and expectations.

Within this project Agri-Science Queensland (within DEEDI) and Meat and Livestock Australia conducted a preliminary investigation into the viability, likely uptake and benefits of developing an ‘app’ (a software application hosted on a smart phone) to assist northern Australian graziers with their land condition monitoring and forage budgeting. Undertaking regular land condition assessments and forage budgets to match pasture supply to animal demand is considered part of best-practice management for graziers in northern Australia. Undertaking these management tasks, however, is often complex and requires a number of steps, both in the paddock and the office along with supporting tools and learnt skills to reach the end points; “what is the current condition of my pastures” and “how long will this feed last given the stock in the paddock”. A specifically designed app for a smart phone or tablet was proposed as a potential solution to increase the adoption of these management practices amongst graziers. Three tasks were undertaken concurrently as part of the investigation; a review of literature, a survey of graziers and advisors in northern Australia, and consultation with software developers to scope the technical feasibility of developing the proposed app. The review of literature considered the evolution of hand-held decision support tools, a comparison of operating platforms and ‘smart’ devices for the task, and currently available agricultural apps and their uptake. A survey of northern Australian graziers and advisors sought views from industry what would be the likely benefit and uptake of this proposed app. The survey found that 76% of respondents thought this 'app' would be either useful or very useful for the grazing industry generally. Around 74% and 73% of respondents respectively said the app would increase the number or frequency of forage budgets and land condition assessments undertaken. Approximately 80% of respondents said the app would help them get started on forage budgeting and land condition assessments if they did not currently undertake these practices already. There are no technical constraints to developing the desired app and development costs were investigated. If development of an app proceeds, it will be important to provide a strong extension framework to support its piloting and promotion.

Remote Cattle Management

Water availability and management has always been a key issue for pastoralism in the arid and semi-arid regions. Recent drought conditions throughout Australia have highlighted the need to seek new and innovative ways to plan for future challenges in water supply management. This handbook aims to be an initial source of information for pastoralists. It details important considerations for stock water delivery and outlines technologies which can reduce the cost of water delivery and storage. The handbook details siting a new bore, equipping a bore, grazing impacts of a bore, animal water requirements, water storage and water point monitoring.

“Tracking Changes in the Victoria River District (VRD) Pastoral District” was commissioned by the Australian Collaborative Rangeland Information System (ACRIS) and the Northern Territory (NT) Government. The aim was to demonstrate the value of rangeland monitoring information for detecting and reporting change over a vast area as well as providing useful natural resource monitoring information to assist decisionmaking in the NT. This activity was part of a larger project, to test the ability of ACRIS to report nationally on changes in Australia’s rangeland from ecological, economic and social perspectives. Information and results contained in this report were primarily derived from the NT pastoral monitoring program — a program based on the operational use of ground site data and satellite monitoring technology. Complementary data have also been sourced to facilitate reporting from a wider perspective (e.g. modelled pasture biomass data). Five key questions on rangeland change have been addressed by collating relevant data and extracting summary information for interpretation. Assessments have been based on the combined evidence from all data. The ACRIS reporting period was 1992–2002, although much of the results for the VRD Pastoral District are placed into the context of preceding (or longer term) information. The five questions on rangeland change were: What is the change in critical stock forage productivity? What is the change in native plant species? What is the change in landscape function? What is the change in cover? What is the capacity for change in the region?

Rangelands occur around the globe in areas to dry or with soils and topography unsuitable for broad-acre farming but fertile and wet enough for pastoralism. Because pastoralism may intensively utilise water and vegetation some rangeland areas can become damaged. This damage means that pastoralism itself ultimately suffers and damage causes conflicts with other land uses such as conserving biodiversity, hunting and gathering bush foods or firewood. Conflicts occur over these multiple uses because people with a sincere interest in rangelands (stakeholders) desire to maintain them in a state of good condition. We define rangelands in good condition as those systems having healthy (i) biophysical functions that include a high capacity to retain water, capture energy, produce biomass, cycle nutrients and provide habitats for diverse populations of native animals, plants and microorganisms, and (ii) socio-economic functions that adequately provide people with their material, cultural and spiritual needs. To maintain rangelands in good condition, these biophysical and socio-economic functions need to be measured and reported. This involves developing monitoring procedures and a system for reporting monitoring information to stakeholders. In Australia, monitoring has historically been conducted by those responsible for maintaining healthy rangelands, typically State and Territory Government Department personnel in collaboration with local land managers and, in some cases, with regional catchment management authorities and natural resource management boards. Reporting rangeland monitoring information to stakeholders is facilitated by the Australian Collaborative Rangeland Information System (ACRIS), which was formed as a partnership between government agencies concerned with rangeland issues. State and Territory Departments provide rangeland monitoring data to the ACRIS, and assist with analysis, synthesis and reporting these data to stakeholders. Two national reports have been produced for stakeholders: Rangelands – Tracking Changes, the Australian Collaborative Rangelands Information System (in 2001), in which ACRIS was proposed, and Rangelands 2008 – Taking the Pulse. The ACRIS Management Committee commissioned this discussion paper to evaluate the way in which biophysical information on vegetation and soils was compiled in the latter report – biodiversity information is being evaluated in another paper – and to recommend possible ways to improve future reporting. This paper also reviews the literature describing the concept of rangeland condition and what it means according to different stakeholders’ values and land use goals.

The Dynamic Land Cover Dataset of Australia is the first nationally consistent and thematically comprehensive land cover reference for Australia. It is the result of a collaboration between Geoscience Australia and the Australian Bureau of Agriculture and Resource Economics and Sciences, and provides a base-line for identifying and reporting on change and trends in vegetation cover and extent. The dataset comprises digital files of the land cover classification, three trend datasets showing the change in behaviour of land cover across Australia for the period 2000 to 2008 and a digital copy of the technical report.

This report was commissioned by MLA to look at the current state of the north Australian beef industry in terms of productivity and profitability. The research shows that profit maximisation amongst the enterprises studied, is a function of both cost minimisation and optimisation of production levels Enterprises which maximised profit, did not rely on price received, had slightly higher production per large stock unit (LSU), had lower stocking rates when adjusted for rainfall, significantly higher gross margins and significantly lower overheads in the business. The major issues facing the industry include inadequate scale in the more closely settled areas, significant cost escalations in both overheads and direct costs, doubling of debt per LSU over the last decade while return on assets (ROA) has declined to very low levels of 0.3% to 2.0% on average. Approximately half of the producers studied have spent more than they earned for six of the last seven years, indicating the northern beef industry is generally in a very unprofitable and unsustainable state.

To understand and communicate both the impacts of grazing and opportunities for improved management, information on where and when vegetation has changed is critical. This research proposal sought MLA funding to develop a practical software toolbox i.e. ‘VegMachine’ for interrogating time-series satellite data and to provide support in the use of this monitoring information at enterprise and regional levels. The purpose of this project was to: 1.Provide pastoralists with the VegMachine software package so that remote sensing pasture condition information can be used in grazing management representing various biophysical environments and beef operations. 2.Ensure that pastoral properties in the VRD and southwest Qld can use VegMachine to benefit from the application of satellite-based monitoring products for pastoral land management. 3.Develop a land condition monitoring program in southwest Qld, based on time-series Landsat data and ground data related to landscape function.

FORAGE - Framework for Online Report Generation (Long Paddock)

A bio-economic modelling framework was developed to examine biophysical and economic impacts of several grazing management practices at a property level. These practices were: stocking rates and their adjustment; pasture resting and burning to manage unwanted woody growth. In general, stocking at or slightly below the long-term safe carrying capacity gave good pasture condition and good economic performance, compared to high stocking rates. Systems which limited annual changes in stock numbers to a modest increase (~10%) and a larger decrease (~40%) appear to give better economic performance and still maintain good pasture condition. However, a protracted sequence of poor years can lead to a large drop in animal numbers and with a slow buildup, the economic performance can be unsatisfactory. Pasture resting simulations showed that frequent and long rests were the most beneficial to pasture condition. Resting paddocks for 6 months, once every 4 years, was profitable and allowed pasture to improve if cattle were agisted. If cattle were ‘loaded up’ into other paddocks on the property, then some paddocks can suffer longterm damage. At moderate levels of woody cover and moderate rates of tree growth in reasonably productive land types, burning improved economic performance. A burn every 4 years may be sufficient to maintain woody cover at an acceptable level and maintain animal production and economic performance. This work has supported the findings of the review of literature by McIvor et al. (2011). More thorough analyses of completed trials and improvements in the ability of the framework to analyse real-world management practices are needed to gain further insights.

The aim of the Producer Demonstration Site (PDS) project on remote water management for the Roma region was to increase adoption of remote management technologies and to address producers’ concerns about telemetry equipment e.g. reliability, serviceability and technical support while demonstrating the financial and other benefits of this technology. The design and installation of equipment within each PDS was overseen by the Department of Employment, Economic Development and Innovation (DEEDI) who also monitored the use and quantified the benefits for each PDS. Field days that demonstrated the benefits for each producer site were well supported by local producers, financial providers and other government and non-government agencies. The results of the PDS have shown that producers can expect to recover their investment outlay within the first year or two of adopting this technology. Those who attended the field days now have a better understanding of the costs and benefits of remote monitoring and are more likely to adopt this technology in the future.

Defining drought, categorising current droughts, and assessing grassland and rangeland sustainability in a quantitative and scientific manner are important national issues for Australian State and Commonwealth governments, landholders and agribusiness. A challenge for ecologists and modellers of Australia’s grasslands and rangelands is to integrate biological models, geographic information systems, satellite imagery, economics, climatology and visual high-performance computing into readily available products that can provide monitoring and prediction advice in near real-time. The QDNR systems approach to the management of native grasslands recognises that drought occurs at a regional scale, and that impacts on livestock and natural resources can be forecast using simple models of soil water, plant growth and animal performance Our vision for a comprehensive Australian Grassland and Rangeland Assessment System (Aussie GRASS) is one that consists of the best combination of rainfall analyses, seasonal climate forecasts, satellite and terrestrial monitoring, and simulation models of relevant biological processes. This will provide a rational basis for large-scale management decisions by graziers, extension workers, land resource managers, bureaucrats and politicians. Aussie GRASS products are currently used within the Queensland government for drought declaration assessments and applications for Drought Exceptional Circumstances. The Aussie GRASS national spatial modelling framework allows agricultural simulation models to be run at a continental scale on a 0.05 degree (~5 km) grid. The simulation model currently in use by the Aussie GRASS project is the GRASP pasture model developed for tropical native pastures in Queensland by QDPI and QDNR. In the latest Aussie GRASS project, other regional models are being examined for their applicability to areas such as the southern winter perennial grass zone, chenopod shrublands or the high rainfall temperate zone. The Queensland version of the Aussie GRASS model is currently used to produce data for a monthly report — A Summary of Seasonal Conditions in Queensland. Model outputs are used in conjunction with recorded and forecast rainfall, satellite imagery, Southern Oscillation Index and current drought declarations to build a comprehensive picture of the current and future seasonal conditions impacting on primary producers. Other numerous outputs from the model can be produced and tailored as required.

State-wide inter-annual changes to foliage projective cover: better products from higher resolution satellite imagery and improved processing methodologies

The 2012 Indigenous Expenditure Report is the second in a series, prepared by the Steering Committee for the Review of Government Service Provision under the auspice of the Council of Australian Governments (COAG). It provides estimates of expenditure on services provided to Aboriginal and Torres Strait Islander people by the Australian Government, and State and Territory governments. Estimates are provided for each level of government, Australia as a whole, and by state and territory geographical basis, for 2008-09 and 2010-11. These estimates provide one element of the evidence base that policy makers need to gain a clearer picture of the efficiency of government services provided to Indigenous Australians.