A methodology is investigated for assessment of feeding preferences of grazing sheep where satellite tracking is carried out using GPS collar units. Sheep grazing preferences were analysed by a statistically based approach under constraints of spatial error in the GPS tracking data. The statistical significance of grazing locations was determined by testing a null hypothesis on animal locations in two adjacent pastures using the normal approximation to the binomial distribution for proportions. The analysis also included calibration and compensation for the precision of the GPS receiver, which produced an uncertain decision boundary between the paddocks. It was concluded that the approach was effective in dealing with GPS spatial errors and in comparing the feeding preferences of sheep.

Geovisual analytics provides a framework for the development of decision support tools for landscape design, analysis and optimisation. An important application is modelling the spatial-temporal movements of ruminants and their grazing behaviour using global positioning system (GPS) collar units. This study describes the mapping and analysis of spatial distributions of animal waste products (which correlate with farm nitrogen [N] emissions) and also determination of animal feeding preferences (which correlate with animal welfare and production). Segmentation of local regions of animal N emissions provides support in meeting targets for local and international N leaching and greenhouse gas emissions. An agent-based model was used for pre-screening in order to gain insights into the clustering behaviour of sheep during feeding activities. Subsequent spatial analysis demonstrated that livestock excreta are not always randomly located, but concentrated around highly localised animal gathering points, separated by the nature of the excretion. In a separate study, the statistical significance of feeding choices was determined by testing a null hypothesis on animal boundary transitions between adjacent pastures using the binomial approximation. The analysis also included compensation for the precision of the GPS sensor, which produced a fuzzy decision boundary.

Decision makers are facing unprecedented challenges in addressing the likely impacts of climate change on land use. Changes to climate can affect the long-term viability of certain industries in a particular geographical location. Government policies in relation to provision of infrastructure, management of water, and incentives for revegetation need to be planned. Those responsible for key decisions are unlikely to be expert in all aspects of climate change or its implications, and thus require scientific data communicated to them in an easily understood manner with the scope to explore the implications. It is often felt that a range of visualisation techniques, both abstract and realistic, can assist in this communication. However, their effectiveness is seldom evaluated. In this paper we review the literature on processes for the evaluation of visualisation tools and representations. From this review an evaluation framework is developed and applied through an experiment in visualisation of climate change, land suitability, and related data using a variety of tools and representational options to advance our knowledge of which visualisation technique works, when, and why. Our region of interest was the southwestern part of Victoria, Australia. Both regional and local data and their implications were presented to end users through a series of visualisation products. The survey group included policy makers, decision makers, extension staff, and researchers. They explored the products and answered both specific and exploratory questions. At the end of the evaluation session their knowledge and attitudes were compared with those at the commencement and they were also asked to assess the visualisation options subjectively. The findings relate to both the visualisation options themselves and the process of evaluation. The survey group was particularly keen to have access to multiple interactive tools and the ability to see scenarios side-by-side within a deeper informational context. A number of procedural recommendations for further evaluation were developed, including the need for consistency in approach among researchers in order to develop more generalisable findings.

The lamb industry in Victoria is a significant component of the state economy with annual exports in the vicinity of $1 billion. GPS and visualisation tools can be used to monitor grazing animal movements at the farm scale and observe interactions with the environment. Modelling the spatial-temporal movements of grazing animals in response to environmental conditions provides input for the design of paddocks with the aim of improving management procedures, animal performance and animal welfare. The term "biological shepherding" is associated with the re-design of environmental conditions and the analysis of responses from grazing animals. The combination of biological shepherding with geo-visual analytics (geo-spatial data analysis with visualisation) provides a framework for improving landscape design and supports research in grazing behaviour in variable landscapes, heat stress avoidance behaviour during summer months, and modelling excreta distributions (with respect to nitrogen emissions and nitrogen return for fertilising the paddock). Nitrogen losses due to excreta are mainly in the form of gaseous emissions to the atmosphere and leaching into the groundwater. In this study, background and context are provided in the case of biological shepherding and tracking animal movements. Examples are provided of recent applications in regional Australia and New Zealand. Based on experimental data and computer simulation, and using data visualisation and feature extraction, it was demonstrated that livestock excreta are not always randomly located, but concentrated around localised gathering points, sometimes separated by the nature of the excretion. Farmers require information on the nitrogen losses in order to reduce emissions to meet local and international nitrogen leaching and greenhouse gas targets and to improve the efficiency of nutrient management.

We have limited empirical information on the value of different visualisation techniques and how they may best be applied in a range of situations. The goal of this research was to provide insights into the capacity of various visualisation techniques to communicate projected climate change data and their implications for dairy production in the south-western region of Victoria, Australia. We used a combination of technologies including animation of geographical information system outputs, three-dimensional images and Google Earth. The developed visualisation products were presented to a group of local stakeholders for evaluation and feedback. We found, in this preliminary study, that visualisation technology can provide a user-friendly way to access contextualized data with perspectives relevant to stakeholders who may be dealing with a complex multi-dimensional problem such as climate change. We also used the opportunity to find out more about the current usage patterns and expectations with respect to climate change data.

Climate change is predicted to impact countries, regions and localities differently. However, common to the predicted impacts is a global trend toward increased levels of carbon dioxide and rising sea levels. Governments and communities need to take into account the likely impacts of climate on the landscape, both built and natural. There is a growing and significant body of climate change research. Much of this information produced by domain experts for a range of disciplines is complex and difficult for planners, decision makers and communities to act upon. The need to communicate often complex scientific information which can be used to assist in the planning cycle is a key challenge. This paper draws from a range of international examples of the use of visualisation in the context of landscape planning to communicate climate change impact and adaptation options within the context of the planning cycle. Missing from the literature, however, is a multi-scalar approach which allows decision makers, planners and communities to seamlessly explore scenarios at their special level of interest, as well as to collectively understand what is driving these at a larger scale, and what the implications are at ever more local levels. Visualisation tools such as digital globes provide one way to bring together multi-scaled spatial–temporal datasets. We present an initial development with this goal in mind. Future research is required to determine the best tools for communicating particular complex scientific data and also to better understand how visualisation can be used to improve the landscape planning process.

Three-dimensional (3D) modelling of plants can be an asset for creating agricultural based visualisation products. The continuum of 3D plants models ranges from static to dynamic objects, also known as smart 3D objects. There is an increasing requirement for smarter simulated 3D objects that are attributed mathematically and/or from biological inputs. A systematic approach to plant simulation offers significant advantages to applications in agricultural research, particularly in simulating plant behaviour and the influences of external environmental factors. This approach of 3D plant object visualisation is primarily evident from the visualisation of plants using photographed billboarded images, to more advanced procedural models that come closer to simulating realistic virtual plants. However, few programs model physical reactions of plants to external factors and even fewer are able to grow plants based on mathematical and/or biological parameters. In this paper, we undertake an evaluation of plant-based object simulation programs currently available, with a focus upon the components and techniques involved in producing these objects. Through an analytical review process we consider the strengths and weaknesses of several program packages, the features and use of these programs and the possible opportunities in deploying these for creating smart 3D plant-based objects to support agricultural research and natural resource management. In creating smart 3D objects the model needs to be informed by both plant physiology and phenology. Expert knowledge will frame the parameters and procedures that will attribute the object and allow the simulation of dynamic virtual plants. Ultimately, biologically smart 3D virtual plants that react to changes within an environment could be an effective medium to visually represent landscapes and communicate land management scenarios and practices to planners and decision-makers.

Using landscape objects with geo-visualisation tools to create 3D virtual environments is becoming one of the most prominent communication techniques to understand landscape form, function and processes. Geo-visualisation tools can also provide useful participatory planning support systems to explore current and future environmental issues such as biodiversity loss, crop failure, competing pressures on water availability and land degradation. These issues can be addressed by understanding them in the context of their locality. In this paper we discuss some of the technologies which facilitate our work on the issues of sustainability and productivity, and ultimately support for planning and decision-making. We demonstrate an online Landscape Object Library application with a suite of geo-visualisation tools to support landscape planning. This suite includes: a GIS based Landscape Constructor tool, a modified version of a 3D game engine SIEVE (Spatial Information Exploration and Visualisation Environment) and an interactive touch table display. By integrating the Landscape Object Library with this suite of geo-visualisation tools, we believe we developed a tool that can support a diversity of landscape planning activities. This is illustrated by trial case studies in biolink design, whole farm planning and renewable energy planning. We conclude the paper with an evaluation of our Landscape Object Library and the suite of geographical tools, and outline some further research directions.

This paper describes a project developed to help communicate and provide access to data relative to climate change impact on farming systems. We developed a number of web enabled visualization products for illustrating present and potential future farming systems and help improve the communicability of climate change related information to local farming communities and other stakeholders. Our prototype virtual farming system focused on a dairy farm in South West Victoria, Australia. The produced visualizations and information were brought together in the Google Earth digital globe environment and made available online to stakeholders. The use of a digital globe interface allowed the creation of a contextualized virtual farming system that could be explored by the user and where hyperlinks could be activated to obtain detailed information on climate change impacts model outputs for that particular farm. A stakeholder workshop was then conducted to evaluate the capacity of each visualization help communicate climate change data, and early findings are presented.

This paper further articulates the role of ubiquitous spatial technologies (e.g. Google Earth) as tools for analyzing, visualizing, and developing policy responses to predicted climate change impacts. Specifically, the efficiency and effectiveness of using the tools in the production of visualizations for the local level is studied. A brief background to climate change response reveals limited data and visualizations at the local level: ubiquitous spatial technologies can potentially fill the void. Case study data including temperature, rainfall and land suitability information from southwest Victoria (Australia) are used to test the hypothesis. The research team produced thirty short visualizations using minimal time, resources and a moderate skill base. The effectiveness of the visualizations was tested on a diverse group of stakeholders. It was found that the visuals provided contextual information and understandings of overarching climate change trends, however, integration with other datasets and higher levels of detail are required if the platform is to be used as a stand alone policy development tool. Moreover, the need to further develop design guidelines to guard against, or at least inform users about visual sensationalism is required.

Geographical visualisation is an extremely powerful communication tool for better understanding landscape processes, functions and futures. Visual communication is an increasingly common part of environmental decision-making, being used as a 'common currency' to facilitate dialogue between policy-makers and non-experts to increase understanding and thereby improve the decisions made. In recent years we have witnessed the proliferation of geographical visualisation technologies such as digital globes, virtual worlds and game engines. Such technologies provide a powerful front-end to spatial datasets and models and support policy-makers, planners and communities to make better land management decisions. In order to create collaborative virtual environments where end users can fly-through landscapes and interact with one another in a virtual world there is a need for realistic, accessible and contextualised three-dimensional (3D) objects. Collaborative virtual environments typically comprise: vegetation (trees, shrubs etc.), people (avatars), animals (domestic, wild) and built infrastructure (buildings, farm equipment, street furniture. Such 3D objects are the basic building blocks for creating a collaborative virtual environment. This paper reports on the development of a 3D object library which comprises flora, fauna and built infrastructure objects which can be used to create Australian virtual landscapes. The 3D object library is accessible through the Victorian Resources Online (VRO) website and is an online resource for scientists, students and communities to assist in building geographical visualisation products. Further research is necessary in working towards a robust 3D spatial data infrastructure to better support the storage management and dissemination of such information.