This layer shows state-wide SLATS Non-Woody data based on the analysis of multi-date Sentinel2 and Planet Maps imagery for 2018, 2019 & 2020. Non-woody disturbance (removal of grasses, small shrubs and groundcover) is identified by interpreters by comparing two high-resolution satellite images and analysing changes using a range of additional data and imagery products. NWD eras are defined by the year that the majority of clearing took place. Interpreters assign a replacement landcover class that indicates the likely purpose for which the vegetation was disturbed. A summary of the method is as follows: Non-woody disturbance across the state is detected in areas that have low disturbance from 1990. State forest and National Park are excluded from this analysis. Visual assessment is done at a scale of 1:20,000 across the state using pre and post imagery sources and ancillary datasets. Where disturbance is identified, it is captured and mapped a scale of 1:10,000 (or finer scale). Data is available as a raster at 10m cell Non-woody disturbance data is combined with State-wide Land and Tree Study data and the Native Vegetation Regulatory Map to produce the Rural Regulated Landcover Monitoring Report. Analysis is undertaken to prevent double counting across clearing events. For greater accuracy, SLATS non woody clearing mapping occurs over 2 mapping seasons. The data packages on SEED combine both into a single year of clearing. Non-woody disturbance is provided as a raster with the following data key: Natural Agriculture Infrastructure Forestry Links to the relevant landcover change on rural regulated land reports and spreadsheets are shown below: https://www.environment.nsw.gov.au/topics/animals-and-plants/native-vegetation/landcover-science/2021-nsw-vegetation-clearing-report#:~:text=In%202021%2C%204%2C724%20hectares%20were,a%2041%25%20increase%20on%202020. https://www.environment.nsw.gov.au/topics/animals-and-plants/native-vegetation/landcover-science/2020-landcover-change-reporting https://www.environment.nsw.gov.au/topics/animals-and-plants/native-vegetation/landcover-science/2019-landcover-change-reporting https://www.environment.nsw.gov.au/topics/animals-and-plants/native-vegetation/landcover-science/2018-landcover-change-reporting 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 (PDF 50KB) for more information.

This layer shows woody vegetation change based on the analysis of multi-date SPOT5 and Sentinel2 imagery. This analysis was done for the period 2015 and 2016. 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, SLATS data naming previously included both years in which imagery was captured, for example 2015-16. For clarity data is now named using the year in which the majority of the clearing has taken place for example 2015 The woody vegetation change is mapped using the SLATS (Statewide Land and Tree Survey) 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. The woody change data is also used for vegetation compliance analysis. Change statistics are available. 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.

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.

"This map and report (cited below) present the results of research on the rate of change of native woody vegetation in the Central New South Wales wheatbelt. The study was carried out over three years and analysed vegetation change between the 1980s and 2000. ; ; The project tested methods to map changes in native woody vegetation using direct visual inspection of readily available Landsat TM satellite imagery. NPWS mapping of native woody vegetation types within the wheatbelt provided the 1980s baseline information for the study. Clearing was identified on the satellite images and digitised. The resulting clearing maps were used to produce updated maps of remaining native woody vegetation for each monitoring period.; Systematic validation of the mapping was done by comparison with specially flown, fine-scale aerial photography. Validation results showed that the mapping consistently and accurately distinguished between clearing and areas of no-change with typical accuracy rates of approximately 95%."

"This map and report (cited below) present the results of research on the rate of change of native woody vegetation in the Central New South Wales wheatbelt. The study was carried out over three years and analysed vegetation change between the 1980s and 2000. ; ; The project tested methods to map changes in native woody vegetation using direct visual inspection of readily available Landsat TM satellite imagery. NPWS mapping of native woody vegetation types within the wheatbelt provided the 1980s baseline information for the study. Clearing was identified on the satellite images and digitised. The resulting clearing maps were used to produce updated maps of remaining native woody vegetation for each monitoring period.; Systematic validation of the mapping was done by comparison with specially flown, fine-scale aerial photography. Validation results showed that the mapping consistently and accurately distinguished between clearing and areas of no-change with typical accuracy rates of approximately 95%."

We summarized annual remote sensing land cover classifications from the U.S. Geological Survey Land Cover Monitoring, Assessment, and Projection (LCMAP) annual time series to characterize the frequency of forest change across the conterminous United States (CONUS) between 1985-2020. Tabular output includes information on 1) the area classified as forest in each State by year, 2) the forest area in each frequency class (1 - 36 years) in each State, and 3) the forest area and proportion of total forest area that has changed (or not changed) in each State over the entire time series (1985-2020).

This dataset was derived from the primary "SLATS Landsat woody change data (25m) for 1988 - 2010" raster (grid) layers used to generate the annualised woody vegetation change rates for the 2010 NSW Annual Report of Native Vegetation.(http://www.environment.nsw.gov.au/vegetation/reports.htm); ; This data describes the areas and type of woody vegetation change (loss) based on the analysis of multi-date Landsat imagery covering NSW. This data is based on a biennial LANDSAT coverage between 1988-2006 and annual coverage 2006-2010. LANDSAT Imagery 1988-2008 was processed by Geosciences Australia at 25m resolution. 2008 onwards is based on USGS processed LANDSAT at 30m resolution.; ; Note, this vector data may generate slightly different aerial statistics to those generated from the source raster data. This is due to variation caused by the data transformation and vector cleaning processes applied in generating the vector data. 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.

The Statewide Landcover and Trees Study (SLATS) monitors woody vegetation extent, clearing and regrowth using Sentinel-2 satellite imagery. This report for the 2019–20 monitoring period is the second change report in the current series of SLATS reporting which monitors and accounts for woody vegetation extent and change in Queensland, annually. The monitoring period is nominally from August 2019 to August 2020. The methodology monitors and reports change in woody vegetation extent against a 2018 woody vegetation extent baseline which is updated annually with clearing and regrowth mapping. Included are data about the clearing activity type and estimates of woody vegetation density and age, to better describe what woody vegetation currently exists, and where and how it is being cleared. Regrowth reporting is included for the first time in the 2019–20 data. The clearing data are directly comparable with the 2018–19 report but are not comparable with previous SLATS reporting up to and including the 2017–18 SLATS report.

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.