Sheffield, Kathryn; Morse-McNabb, Elizabeth; Clark, Rob; Robson, Susan; Lewis, Hayden (2015): Victorian Dominant Land Cover, 2009-2013 [dataset]. PANGAEA, https://doi.org/10.1594/PANGAEA.845372,

---

Supplement to: Sheffield, K et al. (2015): Mapping dominant annual land cover from 2009 to 2013 across Victoria, Australia using satellite imagery. Scientific Data, 2, 150069, https://doi.org/10.1038/sdata.2015.69

There is a demand for regularly updated, broad-scale, accurate land cover information in Victoria from multiple stakeholders. This paper documents the methods used to generate an annual dominant land cover (DLC) map for Victoria, Australia from 2009 to 2013. Vegetation phenology parameters derived from an annual time series of the Moderate Resolution Imaging Spectroradiometer Vegetation Indices 16-day 250 m (MOD13Q1) product were used to generate annual DLC maps, using a three-tiered hierarchical classification scheme. Classification accuracy at the broadest (primary) class level was over 91% for all years, while it ranged from 72 to 81% at the secondary class level. The most detailed class level (tertiary) had accuracy levels ranging from 61 to 68%. The approach used was able to accommodate variable climatic conditions, which had substantial impacts on vegetation growth patterns and agricultural production across the state between both regions and years. The production of an annual dataset with complete spatial coverage for Victoria provides a reliable base data set with an accuracy that is fit-for-purpose for many applications.

The Victorian Dominant Land Cover data set is a spatial grid of land cover classification for the state of Victoria from 2009-2013 created by the Spatial Sciences Group of the Agriculture Research Division in the Victorian Department of Economic Development, Jobs, Transport and Resources. For each year, three spatial grids are provided which give differing levels of dominant land cover class detail (primary, secondary and tertiary). The land cover classes are derived from satellite imagery (MODIS).