The Statewide Landcover and Trees Study (SLATS) monitors woody vegetation extent and changes in Queensland using Sentinel-2 satellite imagery as its primary tool. This dataset provides annual summaries of woody vegetation clearing and regrowth from the 2018–19 reporting period onward, aligning with an updated Sentinel-2-based methodology introduced in 2018. The data is presented as annual time series summaries, with each year’s data corresponding to a nominal August-to-August reporting period. Summary statistics are provided at the state-wide scale, as well as for administrative boundaries, natural resource management regions and divisions, and other authoritative datasets. This multi-year dataset includes data from the 2018–19 onwards SLATS reporting periods. It supersedes and is not directly comparable with SLATS data published for reporting periods up to and including 2017–18, due to a methodological change. Note that regrowth was not reported in 2018–19; values for regrowth in that year are represented as zero in the dataset.

These layers show areas of woody vegetation change based on the analysis of multi-date SPOT5 imagery. Woody change is detected though a combination of automated and manual interpretation of the differences between images captured during summer of each year. Satellite images are selected as close as possible to the 1st of January each year and must have a clear view of the ground not impacted by smoke or cloud cover. This requirement can result in a range of imagery dates being selected for each SLATS year. To reflect this, data naming previously included both years in which imagery was captured, for example 2008-2009, 2009-2010, 2010-2011, 2011-2012, 2012-2013, 2013-14 and 2014-15. For clarity data is now named using the year in which the majority of the clearing has taken place i.e. 2008, 2009, 2010, 2011, 2012, 2013, 2014. The woody vegetation change is mapped using the SLATS (Statewide Land and Tree Study) method which applies an automated change analysis process followed by visual interpretation of the results by experienced image interpretation staff. Landcover classes reflect the interpreted cause of woody vegetation change. Each change year has a single statewide point and polygon layer derived from approximately 310 SPOT scenes covering NSW. Vector point format is preferred for analysis to prevent double counting when undertaking regional calculations. Points can only fall into a single region unlike raster pixels which can sit astride a vector boundary. This often occurs with analysis based on vector regions such as Local Government Areas or Bioregions. The woody change data is also used for vegetation compliance analysis. Change statistics are available for all change periods. Contact the data broker on data.broker@environment.nsw.gov.au for further information. Remotely sensed imagery is routinely collected by DPE and used to map vegetation clearing. This data is spatially explicit and can be used with other datasets to identify activity on individual lots. Please read the privacy collection notice for more information.

Vegetation change products are produced annually identifying locations where the perennial woody vegetation from the vegetation cover datasets based on Landsat imagery (30m ground pixel) has changed between the forest, sparse woody and non woody classifications. Change classes include; no change, non-woody to sparse, non-woody to forest, sparse to non-woody, forest to non-woody and forest to sparse. Click here for more information.

Vegetation change products are produced annually identifying locations where the perennial woody vegetation from the vegetation cover datasets based on Landsat imagery (30m ground pixel) has changed between the forest, sparse woody and non woody classifications. Change classes include; no change, non-woody to sparse, non-woody to forest, sparse to non-woody, forest to non-woody and forest to sparse. Click here for more information.

Vegetation change products are produced annually identifying locations where the perennial woody vegetation from the vegetation cover datasets based on Landsat imagery (30m ground pixel) has changed between the forest, sparse woody and non woody classifications. Change classes include; no change, non-woody to sparse, non-woody to forest, sparse to non-woody, forest to non-woody and forest to sparse. Click here for more information.

Vegetation change products are produced annually identifying locations where the perennial woody vegetation from the vegetation cover datasets based on Landsat imagery (30m ground pixel) has changed between the forest, sparse woody and non woody classifications. Change classes include; no change, non-woody to sparse, non-woody to forest, sparse to non-woody, forest to non-woody and forest to sparse. Click here for more information.

Vegetation change products are produced annually identifying locations where the perennial woody vegetation from the vegetation cover datasets based on Landsat imagery (30m ground pixel) has changed between the forest, sparse woody and non woody classifications. Change classes include; no change, non-woody to sparse, non-woody to forest, sparse to non-woody, forest to non-woody and forest to sparse. Click here for more information.

Vegetation change products are produced annually identifying locations where the perennial woody vegetation from the vegetation cover datasets based on Landsat imagery (30m ground pixel) has changed between the forest, sparse woody and non woody classifications. Change classes include; no change, non-woody to sparse, non-woody to forest, sparse to non-woody, forest to non-woody and forest to sparse. Click here for more information.

Vegetation change products are produced annually identifying locations where the perennial woody vegetation from the vegetation cover datasets based on Landsat imagery (30m ground pixel) has changed between the forest, sparse woody and non woody classifications. Change classes include; no change, non-woody to sparse, non-woody to forest, sparse to non-woody, forest to non-woody and forest to sparse. Click here for more information.

Vegetation change products are produced annually identifying locations where the perennial woody vegetation from the vegetation cover datasets based on Landsat imagery (30m ground pixel) has changed between the forest, sparse woody and non woody classifications. Change classes include; no change, non-woody to sparse, non-woody to forest, sparse to non-woody, forest to non-woody and forest to sparse. Click here for more information.