Spatial Analysis

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Spatial Analysis research contributes to off-shore, on-shore and border surveillance by using spatial models that anticipate the source of biosecurity risks, identify high risk pathways, predict the spread of current incursions and the locations of future biosecurity incursions. This research will provide government agencies and managers with information to develop cost-effective targeted, monitoring, control or eradication programs.

Spatial Analysis projects

  • 1402A (1302A) : Development of a marine spatial analysis model for improved biofouling risk assessment

    The aim of this project is to complete a scoping study to compare a number of spatial analysis models with the aim to identify a robust method or set of methods - those that provide a sufficiently accurate assessment of species distribution, potential establishment sites or high-risk pathways, and that can be used by non experts to produce practical outcomes for decision makers. The project will include case studies from marine biofouling and terrestrial pre- and post-border contexts.

  • 1402B : Tools and approaches for invasive species distribution modelling for surveillance

    This project aims to deliver something currently missing in existing overviews of methods for predicting distributions of species of biosecurity concern. Overviews usually either describe methods, citing commonly accepted views of their performance, or promote one method, often without clear proof of its generality. This makes it difficult for biosecurity agencies to make informed decisions about which methods to use. By bringing together a team with strong statistical and modelling experience, and with in biosecurity applications, we will target a subset of issues that will help clarify the evidence for existing assertions and develop methods for missing pieces.

  • 1502C (1402C) : Estimation of national-level farm demographic data for preparedness of highly infectious livestock disease epidemics

    The aim of this project is to address the critical information gap represented by the lack of current, reliable farm-level animal demographic data on the most common livestock species: cattle, sheep, goats, deer, horses and pigs. These demographic data will be estimated using existing data sources, applying current analytic techniques and methodologies. There will be direct uptake of these data in surveillance, investigation and response activities.

  • 1502D : Determining the relative sensitivity and contribution of criteria in prioritising plant pests along the biosecurity continuum

    More than five hundred plant pests are classified by Australian plant industries as priority pests.  This project is developing a national framework for prioritising plant pests in order that surveillance resources may be efficiently allocated to those pests posing the greatest threats to Australia.  Pest prioritisation requires the integration of information on the likelihood of pest entry, establishment and spread, an estimation of the impact associated with the pest if established, and our national capacity to detect and eradicate the pest.

  • 1502E : Risk maps for optimising biosecurity surveillance

    This project develops a spatially explicit Bayesian Network to allocate surveillance effort based on risk and a pathway risk map.  The overall aim will be to identify levels of risk along pathways into any country, including Australia and New Zealand, and designate potential high-risk sites where surveillance is more likely to detect invasive organisms.  Recommendations for how the Bayesian Network can be implemented in surveillance planning and instructions on how the tool can be set up for easy implementation by users will also be provided.