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Habitat condition data for Australia from expert elicitation

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About this Collection

Habitat condition data for Australia from expert elicitation


These data relate to a project that aimed to construct and test a method for habitat condition data capture across Australia using expert elicitation. The data derived from experts are in two forms: (1) habitat condition scores for specified areas at a specified date range, and; (2) habitat condition scores based on images (photographs) of ecosyste... more


Conservation and Biodiversity Environmental Monitoring Landscape Ecology


https://doi.org/10.25919/5c7da9661dbcc


01 Jan 1982


11 Nov 2018


Karel Mokany
Karel.Mokany@csiro.au

habitat condition biodiversity image site assessment


Objectives The project developed a novel approach to creating a continent-wide library of ecological condition data suitable for training and validation of model-based approaches to habitat condition assessment. Rather than attempting to aggregate complex raw attribute data, the project collated expert interpretations of habitat condition. Reliable condition assessment is heavily dependent on the deep ecological knowledge of members of Australia’s ecological science and natural resource management communities, hence this project engaged with experts in a wide range of ecosystem types across Australia. Methods – site assessments Experts recorded their assessment of habitat condition for areas within Australia using a data capture tool hosted by the Atlas of Living Australia. Experts mapped site/s with which they have deep familiarity, using polygons. The sites may be small or large, depending on the area over which a consistent condition score can be applied. For each site, experts provided a condition score between 0 and 1 (1=pristine; 0=natural habitat completely removed), the time period of their assessment, and (optionally) disturbances influencing the score. For further details on how data were captured via the online tool, see the document ‘Expert-Elicitation-Guidance.pdf’ provided alongside the data. Methods – image assessments Experts recorded their assessment of images using a data capture tool hosted by the Atlas of Living Australia. The image assessment scores are intended to be used to calibrate the site assessment condition scores contributed by experts. Experts were asked to provide a condition score for a suite of images allocated to them based on the Major Vegetation Groups (MVG) and Hutchinson bioclimatic classifications that they nominated familiarity with during the project registration process. The calibration images characterised each ecosystem in several different condition states. Data preparation Following completion of the data capture phase of the project, data were downloaded from the online tool hosted by Biocollect on the Atlas of Living Australia on 23 November 2018. The data were reformatted and refined using a customised script in R. This processing involved reading in the data from file, removing entries associated with system testing, reformatting from multiple rows per entry to a single row, correcting a range of minor data issues, de-identifying records where requested by experts, writing the processed data out to file. All of the images that were assessed within the HCAT were downloaded from Biocollect. The shapefile holding the spatial polygons for the expert contributed site condition assessments were downloaded from biocollect, processed to remove polygons entered as part of testing, and written out to a single shapefile. Data products The condition assessments of sites contributed by experts were formatted and prepared into the following files: SiteConditionAssessment.csv - Site assessment data of on-ground habitat condition for the 314 sites contributed by experts. Descriptor_SiteConditionAssessment.csv – A file describing the fields used in the SiteConditionAssessment data file. SiteAssessmentShapefile – A folder holding the shapefile (projectSites) specifying the 314 spatial polygons for which site assessments were contributed by experts, with a matching identifier (‘siteID’) to each record in the SiteConditionAssessment file (‘location’). The image assessment data were formatted and prepared into the following files: ImageAssessment.csv – Data on the 278 image assessments of habitat condition, undertaken by experts. Descriptor_ImageAssessment.csv – A file describing the fields used in the ImageAssessment.csv data file. ImageAssessmentImages – A folder holding the 77 habitat images that were assessed by experts, as cross-referenced in the ImageAssessment.csv data file.


Matt White, Nat Raisbeck-Brown, Kristen Williams, Amy Warnick, Karel Mokany, Peter Brenton, Sathish Sathya Moorthy, Rebecca Pirzl


Creative Commons Attribution 4.0 International Licence


CSIRO (Australia), Arthur Rylah Institute for Environmental Research (Victorian Department for Environment and Primary Industries) (Australia), Australian Government Department of the Environment and Energy (Australia), Terrestrial Ecosystem Research Network (TERN) (Australia)


White, Matt; Raisbeck-Brown, Nat; Williams, Kristen; Warnick, Amy; Mokany, Karel; Brenton, Peter; Sathya Moorthy, Sathish; Pirzl, Rebecca (2019): Habitat condition data for Australia from expert elicitation. v2. CSIRO. Data Collection. https://doi.org/10.25919/5c7da9661dbcc


All Rights (including copyright) CSIRO 2019.


The metadata and files (if any) are available to the public.

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Location Details

10°0′0″ S


44°0′0″ S


154°0′0″ E


113°0′0″ E


WGS84


More about this Collection

Karel Mokany


Senior Research Scientist





Textual or tabular




eng


UTF8


Environment


About this Project

Habitat condition data capture using expert elicitation


This project developed a novel approach to creating a library of reference, training and validation site habitat condition data which places ecological expertise at the centre of a system that uses remote sensing to monitor the quality of habitat for biodiversity. It developed an approach for eliciting, deploying and verifying on-ground condition a... more


Rebecca Pirzl


National Reference Library of Expert Site Condition Assessments


This project aimed to develop a robust method of eliciting site condition data from experts in order to build a national reference library of site condition assessments based on reliable expert knowledge of ecological condition.


DesktopStudy


Matt White


Nat Raisbeck-Brown


Kristen Williams


Amy Warnick


Karel Mokany


Peter Brenton


Sathish Sathya Moorthy


Rebecca Pirzl


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